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Teacher and Teaching Behaviour and Student Motivational Outcomes: Critical Reflections on the Knowledge Base and on Future Research

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• First Online: 28 June 2023

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• Marie-Christine Opdenakker 4 , 5  

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In this chapter, (a selection of) current conceptualizations, theories, measurements, and instruments of (quality of) teacher and teaching behaviour from a variety of perspectives, namely educational and teacher effectiveness research, learning environments research and research on motivational teaching are discussed. Furthermore, attention is paid to topics such as the dimensionality of teacher and teaching behaviour, and of teaching skills, as well as the existence of teaching styles and stages in teaching skill development. In addition, context, antecedents, informant as well as (in)stability issues concerning teacher and teaching behaviour are addressed. Relevant empirical findings concerning the already mentioned issues as well as empirical findings with regard to teacher and teaching effectiveness in relation to student motivational outcomes are reviewed and discussed. Attention is paid to unique and joint effects of teacher and teaching behaviour dimensions and relative sizes of effects. In addition, differential effectiveness of teacher and teaching behaviour in relation to student background characteristics such as gender, social-economic status, cognitive ability, race and ethnicity, and prior engagement is discussed. The chapter ends with conclusions, reflections, implications and suggestions for future research directions and practice related to effective teacher and teaching behaviour based on the findings discussed before.

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Validating a model of effective teaching behaviour and student engagement: perspectives from Spanish students

Observations and student perceptions of the quality of preservice teachers’ teaching behaviour: construct representation and predictive quality.

Teaching Effectiveness Revisited Through the Lens of Practice Theories

• Teacher behaviour
• Instruments
• Differential effects

1 Introduction

How can students be motivated and stay motivated and what influences can teachers have on their students’ motivation and learning? These questions have been triggering teachers, teacher trainers and researchers for many decades. After all, it is a well-known fact that learning takes more easily place when students are motivated (Stipek, 1988 ) and this is also recognized in models of learning (e.g., Illeris, 2009 ). Interest in the effects that teachers and, in particular, their behaviour may have on students can be found in various domains of educational research such as educational and teacher effectiveness research, learning environments research and research in the domains of educational, developmental and motivational psychology. In all these domains, conceptualizations of teacher behaviour exist as well as ideas on what constitutes a good, successful, or effective teacher. This led to the construction (and refinement) of instruments to measure relevant aspects of teacher behaviour and to the formulation of several theories. Because the domains already mentioned have different backgrounds and frameworks, and operated in the past rather independently from each other, it is interesting and important to compare their conceptualizations, measurements and instruments of teacher and teaching behaviour Footnote 1 and their findings in relation to student motivational outcomes. This operation includes looking for convergence and divergence on these topics across these domains and also addressing the dimensionality of teacher quality and effectiveness, the existence of teaching styles and stages in teaching skill development, and exploring context, informant and stability issues concerning teacher and teaching behaviour). It can enlarge our knowledge on and insights in the way in which teachers may and can have an impact on their students’ motivation and how teachers’ behaviour and its effect on student motivational outcomes can be optimally investigated. In this chapter, these topics will be critically addressed and substantiated with empirical findings, and findings from the mentioned domains regarding teacher and teaching effectiveness in relation to student motivational outcomes will be discussed.

2 Conceptualizations of Teacher and Teaching Behaviour from a Variety of Perspectives

It is striking how many different terms are used in the literature to refer to classroom processes or practices and behaviour of teachers who appear to be good, successful, or effective in their teaching (Leon et al., 2017 ). For example, terms like teaching quality (Allen et al., 2011 ; Fauth et al., 2014 ; Leon et al., 2017 ), quality of teaching (Hattie, 2009 ; Teddlie et al., 2006 ), instructional quality (Klieme et al., 2009 ; Lipowsky et al., 2009 ; Rjosk et al., 2014 ), quality of instruction (Creemers, 1994 ; Opdenakker, 2020 ), teaching effectiveness (Hamre et al., 2013 ; Marsh & Roche, 1997 ; Seidel & Shavelson, 2007 ;), effective teaching (Campbell et al., 2004 ; Creemers, 1994 ; Muijs & Reynolds, 2011 ), teacher effectiveness (Campbell et al., 2004 ; Doyle, 1977 ; Kyriakides et al., 2020 ; Muijs et al., 2014 ) and classroom quality (McLean & Connor, 2015 ) are used. In addition, in some studies reference is made to effective teaching styles (Campbell et al., 2004 ; Opdenakker & Van Damme, 2006 ; Wentzel, 2002 ), instructional style (Jang et al., 2010 ), quality of teacher-student interactions (Hafen et al., 2015 ; Hamre & Pianta, 2010 ), and effective classroom management (Arens et al., 2015 ). Furthermore, some of these terms have a broader and others a narrower meaning, and sometimes it depends on who is using the term. A good example is quality of teaching (see e.g., Teddlie et al., 2006 ), which is often used with a narrower meaning than teacher effectiveness (Campbell et al., 2004 ; Muijs et al., 2014 ; Teddlie et al., 2006 ). For example, teacher effectiveness is defined by Campbell et al. ( 2004 ) as ‘the power to realize socially valued objectives agreed for teachers’ work, especially, but not exclusively, the work concerned with enabling students to learn’ (Campbell et al., 2004 , p. 4). It refers to the impact of classroom factors such as teaching methods, teaching expectations, classroom organization and the use of classroom resources (p. 3). This is a broader definition than the definition of quality of teaching by Teddlie et al. ( 2006 ). They define quality of teaching by referring to indicators such as clarity of instruction, (demonstrating) instructional skills, promoting active learning and developing metacognitive skills in students, and (having an adequate) planning of single lessons. However, broader definitions of teaching are found as well. For example, Sykes and Wilson ( 2015 ) refer to two domains namely instruction and professional role responsibilities in their framework for competent teaching, a framework that was based on an interpretive synthesis of main and contemporary currents in the research on teaching and learning. The first domain (instruction) refers to preparing and planning for high-quality instruction, attending to relational aspects of instruction, establishing and maintaining the social and academic culture, interactive teaching, and engaging in instructional improvement. The second domain of teaching (professional role responsibilities) refers to collaborating with other professionals, working with families and communities, fulfilling ethical responsibilities, and meeting legal responsibilities. In addition, Campbell et al. ( 2004 ) mention that teacher effectiveness is (often) conceptualized too narrowly in the literature and that attention should be paid to differential teacher effectiveness which takes into account that teachers may be more effective with some categories of students, some subjects and some teaching contexts than with others.

Moreover, a number of models and theories on effective teaching (e.g., the comprehensive model of educational effectiveness of Creemers, 1994 ; the dynamic model of educational effectiveness of Creemers & Kyriakides, 2008 ; Kyriakides et al., 2020 ), instruction(al) quality (e.g., the three dimensions model of instructional quality of Klieme et al., 2009 ), and (need-)supportive teaching (e.g., the self-system process model of motivational development of Connell & Wellborn, 1991 ; the self-determination theory of Ryan & Deci, 2017 ; the teaching through interactions framework cf. Hafen et al., 2015 ; Hamre et al., 2013 ) Footnote 2 have been developed. Some of these theories focus mainly on how to achieve student learning outcomes, while others focus on more general/broader outcomes (e.g., well-functioning, development) or on non-cognitive outcomes such as motivation or motivated student behaviour in the classroom, or on a diversity of outcomes (cognitive as well as on non-cognitive outcomes). In addition, depending on the research domain, theorizing got more/less attention in the past. For example, in the domain of learning environments research, the focus has always been strongly on developing instruments, while theorizing got less attention. An exception is the theoretical work of Wubbels and colleagues on interpersonal behaviour of teachers. In the next paragraph, (teacher/teaching behaviour) factors often mentioned in the above-mentioned research domains and visible in famous, influential (current) theories/models stemming from these domains and included in a listing of findings of a state-of-the-art on teacher effectiveness research (Muijs et al., 2014 ) will be discussed. (For an overview of the selected theories/models/state-of-the-art, see Table 3.1 ).

Table 3.1 reveals that the theories/models and list in the state-of-the-art on teacher effectiveness refer to a different number of relevant factors/dimensions/domains, although three of them refer to three overarching factors. However, looking into more detail into these factors and their content, it is striking that there is much in common even though the different theories/models stem from a variety of research domains and their knowledge bases are mostly separately constructed. Another observation is that, depending on the research domain, some factors are more elaborated, which often results in more separate dimensions. In the following, the research domains with corresponding theories/models will be discussed paying attention to convergences and divergences.

Teacher effectiveness research and accompanying frameworks/theories refer, first, to the importance of structured teaching (including aspects of direct instruction) (Creemers, 1994 ; Klieme et al., 2009 ; Kyriakides et al., 2020 ; Muijs et al., 2014 ; Opdenakker, 2020 ; Opdenakker & Minnaert, 2011 ; Opdenakker & Van Damme, 2006 ; Teddlie et al., 2006 ; van de Grift, 2007 ). Structured teaching entails the delivery of explicit and clear instruction as well as structuring the lessons (clearly stating goals, making the structure of the lesson explicit, paying attention to main ideas of the lesson) and also entails elements of direct instruction such as giving an orientation on the learning content, offering explicit strategy instruction and guided practice etc. There is overlap with the concept of clarity of instruction often mentioned in learning environments research Footnote 3 (den Brok et al., 2006 ), although clarity of instruction is often more narrowly conceptualized.

In addition, teacher effectiveness research also mentions the importance of good classroom management (Klieme et al., 2009 ; Kyriakides et al., 2020 ; Muijs et al., 2014 ; Opdenakker, 2020 ; Opdenakker & Minnaert, 2011 ; Teddlie et al., 2006 ; van de Grift, 2007 ), and teacher behaviour that stimulates a positive relational and learning climate in the classroom (Klieme et al., 2009 ; Kyriakides et al., 2020 ; Muijs et al., 2014 ; Opdenakker, 2020 ; Teddlie et al., 2006 ). A positive relational climate is characterized by good and frequent teacher-student interactions and good relationships characterized by mutual respect, trust and interest in each other. A good learning climate refers to a class climate that is supportive and conducive to learning (van de Grift, 2007 ). In some teaching effectiveness studies the importance of the teacher as a helpful person is stressed (Opdenakker & Minnaert, 2011 ; Teddlie et al., 2006 ). The mentioned concepts also show resemblance with factors referred to as important in learning environments research, namely of classroom management (see e.g., Back et al., 2016 ; den Brok et al., 2006 ; Fraser, 2012 ) and teachers’ interpersonal behaviour referring to proximity/communion (see e.g., den Brok et al., 2004 , 2006 ; Wubbels, 2019 ; Wubbels & Brekelmans, 2005 ). Also, the importance of teachers’ role in creating a positive psychosocial climate in the classroom and the importance of teacher involvement (Fraser, 2012 ) is emphasized in learning environments research.

Moreover, teacher effectiveness research points to the importance of making expectations about learning (and corresponding evaluation) explicit, and of having high and realistic student expectations as a teacher (Hattie, 2009 ; Muijs et al., 2014 ; van de Grift, 2007 ). The importance of providing positive and constructive feedback to students is stressed as well (Hattie, 2009 ; Klieme et al., 2009 ; Kyriakides et al., 2020 ; Muijs et al., 2014 ). Slavin ( 2021 ) points out the relevance of intentionally/(purposeful) teaching. Furthermore, teacher behaviour in line with constructivist concepts of learning (that stimulates active student involvement in their own learning and the development of metacognitive skills) is, rather recently, receiving attention as effectiveness enhancing teacher behaviour as well (Klieme et al., 2009 ; Kyriakides et al., 2020 ; Muijs et al., 2014 ; Opdenakker, 2020 ; Teddlie et al., 2006 ). Lastly, teacher effectiveness research refers to the importance of offering adaptive education/instruction and differentiation opportunities (Creemers & Kyriakides, 2008 ; Kyriakides et al., 2020 ).

Theories and literature on educational, developmental and motivation psychology refer to the same kind of factors referring to providing structure, stimulation of self-regulated learning/student participation, climate, and classroom management. See for example the Teaching through interactions framework (TTI) (and research based on this framework). In this framework (see Hafen et al., 2015 ), which combines developmental theory with classroom practices, reference is made to three overarching factors namely emotional support (which refers to the climate in classes, teacher sensitivity and teacher’s regard for student perspectives), classroom organization (which refers to, among others, behaviour management and productivity in relation to time), and instructional support (which is indicated by, among others, teachers’ approaches to help students with subject matter comprehension, facilitation of higher-level thinking skill use and metacognition, quality of teachers’ feedback and encouragement of students’ participation, and purposeful use of dialogue-structured, cumulative questioning and discussion to facilitate students’ understanding of the subject matter). The resemblance of the first factor with the already mentioned climate factor and teacher involvement in other frameworks, the second factor with classroom management, and the third factor with providing structure and the stimulation of self-regulation and participation is clear.

Related factors are visible in theories/models focusing on supporting students’ motivation and engagement such as the self-determination theory (SDT; Ryan & Deci, 2000 , 2002 , 2017 ) and the self-system process model of motivational development (Connell & Wellborn, 1991 ), a model grounded in self-determination theory. In this model/theory it is stressed that every person requires the fulfillment of three fundamental innate psychological needs in order to function well, to flourish, to be and to stay motivated, and to experience psychological growth and well-being (Ryan & Deci, 2000 ). These needs are the need to feel competent, to feel autonomous and to feel related. Three (need-supportive) factors are mentioned that can satisfy these needs, namely structure, autonomy support and teacher involvement.

Structure refers to the creation of a supportive well-structured environment and includes offering optimal challenges, instrumental help and support, and positive and rich efficacy supportive feedback to students. It also includes adjusting teaching strategies to the level of the student (Ryan & Deci, 2020 ). In addition, it refers to the amount of information that is available in the context about how to effectively achieve desired outcomes (Connell & Wellborn, 1991 ; Skinner & Belmont, 1993 ). Structure can be provided by clearly communicating expectations and goals towards students and by responding contingently, consistently, and predictably to them. It entails the provision of clear and consistent guidelines and rules in the classroom. Structure is considered to play an important role in the fulfillment of the need to feel competent (Ryan & Deci, 2020 ) and is important to promote motivation and engaged behaviour (Ryan & Deci, 2002 ). Providing structure may not be confused with controlling teacher behaviour which pressures students to think, feel or behave in a certain way or which pressures to achieve. The ‘opposite’ of structure is chaos, uncertainty, and inconsistency. Footnote 4

Autonomy support refers to supporting students to take ownership and initiative of their schoolwork (Ryan & Deci, 2020 ). It can be promoted and supported by providing students meaningful choices and tasks and by allowing them latitude in their learning activities, by making connections between school activities and students’ interests and by offering students a rationale for tasks and learning activities that must be done. It also entails attempts to understand, acknowledge, respect, and where possible, be responsive to the perspective of students, to give them a voice and to use informational language (Ryan & Deci, 2017 ). For fostering autonomy, the absence of controls and pressures and, also, of external rewards is important. Autonomy support is seen as promoting not only the satisfaction of the need to feel autonomous but contributes also to the satisfaction of the need to feel related and when it occurs along with structure, the satisfaction of competence is promoted as well. In addition, in respecting autonomy and advocating for its support, which entails, as mentioned before, respecting and attempting to appreciate the perspective of each student as well as his/her unique challenges, the importance of differences between students is acknowledged as well (Ryan & Deci, 2020 ). The ‘opposite’ of being autonomy supported is being coerced and feeling controlled (Connell & Wellborn, 1991 ; Skinner & Belmont, 1993 ). Controlling teachers are more oriented to pressure students with regard to their thinking, feeling or behaving and are not responsive to student perspectives.

The third factor, teacher involvement, is of particular importance to fulfill students’ need of relatedness and refers to creating a caring, supporting and respectful environment (Ryan & Deci, 2020 ). It entails expressing warmth and affection towards students, enjoying interactions with them, taking time for them, and being attuned and dedicate resources to them. Involvement refers to the quality of the interpersonal relationship with teachers and peers. The ‘opposite’ of involvement is rejection or neglect.

The structure factor resembles structure and classroom management factors in other frameworks, while the teacher involvement factor is familiar with (relational) climate and emotional support Footnote 5 factors in other frameworks. The autonomy support factor has connections with factors referring to the stimulation of students’ self-regulation and to teacher actions in line with constructive ideas of learning mentioned in other frameworks.

In general, it can be concluded that all these frameworks and theories mentioned and discussed in the preceding pages include combinations of factors/dimensions that were associated with different research domains in the earlier days. For example, a strong focus on instruction and instructional context is characteristic for educational research, while social dynamics of and within the class has always got much attention in developmental and learning environments research (Hamre & Pianta, 2010 ). Classroom management and organization has always been a factor that was highly focused on in research on teaching and teacher training, learning environments research (Hamre & Pianta, 2010 ), and educational psychology (Emmer & Strough, 2001 ). Overlooking the dimensions of the discussed frameworks and theories, they all have a rather broad and holistic approach to and vision on (the quality of) teacher behaviour. However, it is also clear that there are some differences regarding the degree to which the dimensions are elaborated. For example, it is obvious that instruction is quite elaborated within the models and frameworks related to teacher effectiveness research, while teachers’ role in creating a positive psychosocial classroom climate and offering emotional support is less well elaborated, in particular, in the oldest ones. In other frameworks e.g., the TTI or Need-supportive teaching framework, these dimensions are more equally elaborated.

3 Measurements and Instruments of Teacher and Teaching Behaviour

In each of the mentioned domains of research, instruments for the (reliable and valid) measurement of teacher/teaching behaviour were developed in line with theoretical perspectives, models, and knowledge bases. A comparison of these instruments reveals that they differ regarding the type of informants (teachers – self-report, student perspectives, observers, consultants/administrators), the kind of data collection method used (questionnaires, observation instruments, vignettes, etc.), and the intended educational level (preprimary, primary, secondary education). In the early developing phases of the instruments, the choices made in this respect were the logical consequence of the research traditions in the domains concerned and were often conceived as generic instruments. Later, additions were made to some of the existing instruments. For example, observation variants were added to questionnaires tapping student perceptions (or vise versa), different forms were made to map not only the current perception of teacher’s classroom behaviour/classroom environment, but also the ideal (i.e., preferred teacher behaviour/classroom environment) or the expected teacher behaviour/classroom environment. Sometimes, adaptations for other educational levels than the original were made as well. One of the most known and wide-spread used instruments are the CLASS [Classroom Assessment Scoring System] instrument (Pianta & Hamre, 2009 ; Pianta et al., 2012 ) stemming from the domain of developmental and educational psychology), the WIHIC [What Is Happening In this Class] from the domain of learning environments research Footnote 6 (Fraser et al., 1996 ), the ICALT [International Comparative Analysis of Learning and Teaching] (van de Grift, 2007 ), the ISTOF [International System for Teacher Observation and Feedback] instrument (Muijs et al., 2018 ; Opdenakker & Minnaert, 2011 ; Teddlie et al., 2006 ), both stemming from educational and teacher effectiveness research, and the TASC [Teacher As a Social Context] (Belmont et al., 1992 ), which is based on elaborations of the self-determination theory/self-system processes model of motivational development (Ryan & Deci, 2017 , 2020 ; Connell & Wellborn, 1991 ).

A comparison of these instruments reveals that, in line with the findings about the theoretical/knowledge base foundations of these instruments, the instruments share overlapping concepts and characteristics that are recognized as effective teaching behaviour in teacher effectiveness research (see Table 3.2 ). For a description and discussion of these instruments, see the Appendix.

4 Dimensionality, Stability and Best Informants of Teacher and Teaching Behaviour

4.1 dimensionality of teacher and teaching behaviour.

An important question is how the mentioned dimensions/factors/domains of the instruments described in the preceding section and the appendix should be considered. Do they refer to a one-dimensional, multidimensional or multifaced conceptualization of teaching and teacher behaviour? What evidence does validation research deliver about the theoretical conceptualizations?

In general, all the dimensions/factors/domains distinguished in the instruments are, from a theoretical point of view, considered as unique contributors to teaching and a lot of validation studies found evidence for the multidimensionality of teacher behaviour. Footnote 7 For example, a variety of studies (e.g., Allen et al., 2013 ; Hafen et al., 2015 ; Hamre et al., 2013 ; Virtanen et al., 2018 ) found evidence for the three-domain latent structure of the CLASS/CLASS-S instrument. In each of the studies, a three-factor solution (in confirmatory factor analysis) had a better fit compared to one- or two-factor solutions. The studies referred to a variety of classroom settings (ranging from preschool to high school) and to teaching in a variety of countries. Comparable findings providing evidence for the multidimensionality of teacher behaviour/teaching were found with regard to the WIHIC (e.g., Aldridge & Fraser, 2000 ; Dorman, 2003 ), the TASC (e.g., Opdenakker, 2014 ; Sierens et al., 2009 Footnote 8 ; Vansteenkiste et al., 2012 Footnote 9 ) and dimensions related to need-supportive teaching (Jang et al., 2010 Footnote 10 ), the ISTOF (student questionnaire: Opdenakker & Minnaert, 2011 ; observation instrument: for a review, see Muijs et al., 2018 ) and the ICALT (e.g., Maulana et al., 2017 , 2021 ; Maulana & Helms-Lorenz, 2016 ; van de Grift et al., 2011 Footnote 11 ).

In addition, regarding some conceptualizations/instruments, evidence was found for the usefulness of a conceptualization in terms of a circumplex model which offered the opportunity to combine dimensions in order to distinguish between teaching styles. A well-known use of the circumplex model is related to dimensions of the Questionnaire on Teacher Interaction, an instrument rooted in learning environments research (Brekelmans et al., 2011 ). Recently such an approach was successfully adopted as well by Aelterman et al. ( 2019 ) using two (of the three) Footnote 12 dimensions of need-supportive teaching in line with the SDT framework namely autonomy support and structure. Aelterman et al. ( 2019 ) collected self-reports from Belgian secondary school teachers and students using the vignette-based Situations-in-School Questionnaire and applied multidimensional scaling analyses. This resulted in a two-dimensional configuration forming a circumplex with eight subareas, namely participative and attuning, guiding and clarifying, demanding and domineering, and abandoning and awaiting. The correlations between these subareas and various outcome variables followed the expected sinusoid pattern.

Furthermore, although the instruments discussed before can differentiate between the different factors/dimensions/domains and validation studies deliver evidence for the existence of these different factors/dimensions/domains, there are also indications in the literature of positive associations between the factors/dimensions/domains. This could lead to some confusion regarding how the relationship between the dimensions should be conceptualized. Den Brok et al. ( 2019 ), reviewing instruments rooted in learning environments research, mention that correlations between dimensions of these instruments often range between 0.20 and 0.60. This indicates some overlap as well as idiosyncrasy. Regarding other instruments rooted in different theoretical frameworks, similar findings are reported. For example, Jang et al. ( 2010 ) mention, based on observation measures within the SDT framework, a positive correlation between autonomy support and structure ( r  = 0.60). Also, Sierens et al. ( 2009 ) found that autonomy support and structure (of math/Dutch language/educational science teachers as perceived by their students from grade 11–12 academic track classes) is correlated ( r  = 0.67), which is confirmed by Lietaert et al. ( 2015 ) doing research in grade-7 Dutch language general and vocational track classes ( r  = 0.71), and by Hospel and Galand ( 2016 ) in French language grade-9 vocational and general classes in the French-speaking part of Belgium ( r  = 0.60). Confirmation is also found in the study of Vansteenkiste et al. ( 2012 ) Footnote 13 who report a significant correlation ( r  = 0.54) between autonomy support and clear expectations, a subdimension of structure based on research in grade 7–12 mainly general track classes. In addition, Vansteenkiste et al. ( 2012 ) found based on cluster analysis evidence for four teaching configurations Footnote 14 of which two referred to scoring high or low on both dimensions and two configurations scoring high on one of the two dimensions. Furthermore, Lietaert et al. ( 2015 ) reported somewhat lower, but significant, correlations between teacher involvement and autonomy support and structure (respectively r  = 0.58 and r  = 0.59).

In addition, regarding the dimensions of the CLASS/CLASS-S instrument similar findings are reported (cf. Pianta et al., 2012 ). For example, Pöysä et al. ( 2019 ) mention correlations between 0.52 and 0.62 in their study on grade-7 Finnish mathematics and language art classes ( r  = 0.52 between instructional support and classroom organization, r  = 0.62 between instructional support and emotional support, and r  = 0.61 between emotional support and classroom organization), while Virtanen et al. ( 2015 ) report correlations between 0.37 and 0.75 based on observations in Finnish grade-7 literacy, history and civics, science and home economics classes ( r  = 0.37 between instructional support and classroom organization, r  = 0.75 between instructional support and emotional support, and r  = 0.48 between emotional support and classroom organization). Reyes et al. ( 2012 ) mention comparable correlations related to fifth/sixth-grade classes: r  = 0.57 between instructional support and classroom organization, r  = 0.68 between instructional support and emotional support, and r  = 0.60 between emotional support and classroom organization.

Also, regarding the dimensions of the ICALT observation instrument, clear evidence for associations between dimensions is found. Van de Grift et al. ( 2011 ) report correlations Footnote 15 between 0.55 and 0.92 with an average correlation of 0.75. Adaptive teaching has the lowest correlations with other dimensions (average correlation: 0.64) and the climate dimension the second lowest (average correlation: 0.70). The reported correlations are quite high in comparison with the mentioned ones of other instruments. One of the reasons could be that several dimensions of the ICALT refer to teacher behaviour related to instruction. Regarding the ICALT, also the one-dimensionality of the scale was explored and evidence for it was found in several studies (e.g., van de Grift et al., 2011 ; van de Grift et al., 2014 ; Maulana et al., 2021 ). Furthermore, evidence was found for a systematic hierarchy in the difficulty level of teaching activities ranging from more basic (the creation of a safe and stimulating climate, efficient classroom organization and management, the provision of clear and structured instruction) to more complex (activating teaching, adaptive teaching, and teaching learning strategies) (van de Grift et al., 2011 , 2014 ; van der Lans et al., 2018 ). This hierarchy is in line with Fuller’s theory on the development of teachers’ stages of concern (Fuller, 1969 ) and seems to be in line with ideas that novice teachers may need to reach a minimum level of competency in classroom management skills before they are able to develop in other areas of instruction (Emmer & Strough, 2001 ).

Regarding the ISTOF student questionnaire, an average correlation of 0.44 was found between factors indicating a weak-to-moderate association ( r  = 0.25 between ‘teacher as promoter of active learning and differentiation’ and ‘classroom management’, r  = 0.40 between ‘teacher as a helpful and good instructor’, r  = 0.68 between ‘teacher as a helpful and good instructor’ and ‘teacher as promoter of active learning and differentiation’ (Opdenakker & Minnaert, 2011 ). There are also indications of positive associations between the dimensions of the ISTOF observation instrument (for a discussion, see Muijs et al., 2018 ).

In general, it seems to be that the (overarching) dimensions measured with the instruments must be seen as complementary and (often) uniquely predictive of student outcomes, rather than as separate and independent of each other (Jang et al., 2010 ), and that the dimensions referring to instruction (and classroom organization and management) seem to refer to an overarching dimension referring to teacher activities with a different level of difficulty. This line of thought agrees with findings of Malmberg et al. ( 2010 ) who followed teachers from their last year of teacher education into their first 2 years of teaching practice and found different patterns of evolutions with regard the three dimensions of the CLASS-S (classroom and management skills, instructional support and emotional support). These findings call for considering multiple dimensions/domains rather than an overall indication when examining teaching, teaching quality, teacher effectiveness and teacher development.

4.2 Stability of Teacher and Teaching Behaviour

An important question, also from the perspective of obtaining good measurements of the quality of teaching and teacher behaviour, is if teaching and teacher behaviour is stable across lessons and time.

In general, not many studies have addressed this topic and in the few studies addressing (in)stability of teacher behaviour during a school year evidence is found for (small to large) changes and for, on average, mostly declining trends in the quality of teaching and student learning environment experiences from start to the end of the school year. For example, Maulana et al. ( 2016 ) reported declines in (student perceptions of) instructional behaviours (clarity and classroom management) and Opdenakker and Maulana ( 2010 ) found declines in structure, autonomy support, and, to a lesser extent, also decreases in teacher involvement in secondary education in the Netherlands. Also, Maulana et al. ( 2013 ) found evidence for a decrease in observed teacher involvement in secondary education. In line with these studies, (small) declines in the quality of interpersonal behaviour were found in secondary education (e.g., Mainhard et al., 2011 ; Opdenakker et al., 2012 ; the Netherlands) and regarding teacher involvement in primary education (Skinner & Belmont, 1993 ; New York). In contrast, research in secondary education in Indonesia revealed evidence for increasing quality during the school year (student perceptions) regarding involvement, structure, and autonomy support (Maulana & Opdenakker, 2014 ) and regarding interpersonal teacher behaviour (proximity and influence) (Maulana et al., 2014 ). A mixed picture is visible in the study of Stroet et al. ( 2015 ). They found clear decreases of observed autonomy support and teacher involvement, and a small increase in structure in prevocational classes in the Netherlands. In all studies using multilevel growth curve modelling, evidence for differences between classes/teachers regarding the trajectories were reported as well indicating deviations from the average trend.

4.3 Best Informants of Teacher and Teaching Behaviour

Scholars in learning environment and motivation research often stress the importance of tapping students’ perceptions of teachers’ teaching behaviour (e.g., den Brok et al., 2005 ; Fraser et al., 2021 ; Hamre & Pianta, 2010 ; Ryan & Deci, 2020 ) and several studies revealed evidence that students’ experiences of their teachers’ teaching are valuable and can be reliable measured (Fauth et al., 2014 : Kunter & Baumert, 2006 ). In addition, Kulik ( 2001 ) concludes in his review study on the validity of student ratings that student ratings have high validity (strong correlation with classroom observations and expert observations) and Cipriano et al. ( 2019 ) found evidence of agreements between primary school students of the same class regarding perceptions of teacher support: perceived teacher support at class level was significantly associated with individual student perceptions of teacher support.

Teacher questionnaires are also used, especially in large scale studies, to receive information on teachers’ behaviour and the characteristics of the learning environments they create in their classes (Kunter & Baumert, 2006 ). Some studies addressed the agreement between student and teacher ratings. In general, these studies report weak to moderate correlations (see for example, Cipriano et al. ( 2019 ) regarding perceptions of teacher support). Studies comparing student and observer ratings refer, broadly spoken, to moderate associations (Kunter & Baumert, 2006 ).

Furthermore, student perceptions of their teachers’ behaviour and learning environment experiences are often stronger associated with student outcomes (e.g., academic achievement or motivational outcomes) than teachers’ self-report about their own teaching (Van Damme et al., 2004 ) or ratings of external observers (De Jong & Westerhof, 2001 ; Maulana & Helms-Lorenz, 2016 ).

Hamre and Pianta ( 2010 ) addressed the importance and advantages of observational measures focused on teaching quality and stressed that these measures are better than measuring discrete teaching behaviours since these measures may be more meaningful assessments of higher order organizations of teaching behaviour and ‘tend to parse the behavioral stream into more contextually and situationally sensitive “chuncks” (p. 34).

Kunter and Baumert ( 2006 ) mention that all informants (students, teacher, observers) can have their own biases and that discrepancy between the mentioned informants can also be viewed from another perspective, namely that they can reflect perspective-specific validities. Based on their study, in which they compared student and teacher ratings of instruction, they concluded that student and teacher ratings were best suited to tapping different aspects of the learning environment. This is in line with Clausen ( 2002 ) who found, examining whether the perspectives of the three types of informants could be subsumed in a common model of instructional quality, that the data were best replicated by introducing three method factors, indicating that students, observers, and teachers tend to perceive instruction in specific ways. In addition, the method factor for students’ perceptions of instruction, showed that, although students were able to distinguish between diverse instructional aspects, their evaluation of the teacher was also shaped by a generally positive or negative attitude towards their teacher. Furthermore, Brekelmans et al. ( 2011 ) found, when examining if students and teachers use a similar frame of reference when thinking about how a teacher relates to students, that although they use a similar framework, they do not agree on the amount of teacher control/influence and affiliation/proximity in a particular class. We agree with Kunter and Baumert ( 2006 , p. 244) that ‘ because various methods have particular strengths for assessing different instructional features in research on classroom processes … great care [should] be taken in choosing a data source appropriate for the construct to be measured .’

5 Teacher and Teaching Effectiveness in Relation to Student Motivational Outcomes

In general, it can be stated that there is much evidence for the importance of the previously mentioned dimensions in relation to students’ learning and development. This is not surprising since authors of the instruments often explicitly mention that their instrument and underlying framework, model or theory is based on or contains, at least partly, dimensions and/or scales that have been shown in previous studies to be significant predictors of student outcomes (see e.g., Fraser et al., 1996 ; Hamre & Pianta, 2010 ; van de Grift, 2007 ).

However, since motivation and engagement are often seen as antecedents for learning, achievement and development, it is of great importance to explore whether the dimensions in line with the discussed frameworks and instruments are associated with motivational outcomes. Motivational outcomes refer in this review to motivation (autonomous, controlled, extrinsic, intrinsic), engagement, effort, and motivational attitudes (e.g., interest, enjoyment, pleasure, task value, subject attitude).

To find relevant empirical studies, Web of Science, PsycINFO and Google Scholar were searched (1990–2021). Studies had to address a motivational outcome (see previous paragraph, or mention ‘motivation’/‘motivational outcome’) and refer to teaching, teacher/teaching/instructional quality/effectiveness/behaviour, quality of teaching, teacher support, class/classroom experiences, learning environment, teacher-student relationship(s) or need(−)supportive teaching/style. In addition, a reference to one of the mentioned frameworks, instruments or dimensions of the frameworks/instruments had to be included and an appropriate method of analysis (e.g., account for nested data structure if necessary) had to be used. Furthermore, recent review studies on teacher/teaching effectiveness, need-supportive teaching and quality of teacher-student relationships were consulted.

First of all, evidence was found for effects of overarching or umbrella measurements of teaching quality in line with the earlier discussed frameworks and instruments on motivational outcomes. For example, research of Klem and Connell ( 2004 ) conducted in primary and secondary education found that teacher support experiences (combining teacher involvement, structure and autonomy support items) mattered with regard to students’ engagement. Tas ( 2016 ), investigating effects of teacher support on engagement (agentic, behavioral, emotional, cognitive) in Turkish middle school science classes (grade 6 and 7) and using some of the WIHIC dimensions, among others teacher support (a combination of emotional and instructional support), found positive effects of teacher support on all engagement dimensions. In addition, the study revealed that the effect of teacher support was mediated by students’ self-efficacy (except for agentic engagement).

Also, Vandenkerckhove et al. ( 2019 ), investigating the relation between weekly need-based experiences and variations (based on, among others, experiences with the teacher) and weekly academic (mal)adjustment, found positive associations between weekly variations in need satisfaction and weekly variations in engagement and autonomous motivation, and between variations in need frustration and variations in controlled motivation. In addition, research of van de Grift et al. ( 2011 , 2014 ), using the teaching skill scale (RASCH scale) based on the ICALT, delivered evidence of a positive association between teachers’ teaching skill and student engagement (at class level). Van de Grift et al. ( 2011 ) reported a correlation of 0.62. Maulana and Helms-Lorenz ( 2016 ), using a student perceptions and observation version of the ICALT, also found a relationship between the teaching skill scale (observations and student perceptions) and student engagement. However, student perceptions were more strongly associated with student engagement and when both were included in a model to predict student engagement, observations were not significant anymore.

Furthermore, also regarding distinct dimensions, effects on motivational outcomes were found (see for dimensions related to SDT the review study of Stroet et al., 2013 ; Opdenakker, 2021 ). Results regarding related dimensions will be discussed together in the next pages.

5.1 Effects of Teachers’ Emotional Support, Involvement, and Positive Teacher-Student Relationships

In general, clear evidence is found for positive associations between the quality of teacher-student relationships and (academic) engagement (for reviews see; Opdenakker, 2021 ; Roorda et al., 2011 ; Stroet et al., 2013 ). For example, Roorda et al. ( 2011 ), reviewing the influence of affective teacher–student relationships on students’ academic engagement (from preschool to high school) and using a meta-analytic approach, found evidence for medium to large associations between the quality of these relationships and (academic) engagement. Also Furrer and Skinner ( 2003 ) and King ( 2015 ), investigating the relationship between students’ relatedness to their teacher (and peers and parents) and students’ engagement found evidence for an unique effect of relatedness to their teacher and engagement, while the studies of den Brok et al. ( 2004 , 2005 , 2010 ) and Opdenakker et al. ( 2012 ) revealed positive effects of teachers’ proximity (a dimension of interpersonal behaviour) on students’ motivational and attitudinal outcomes such as (autonomous motivation, pleasure, relevance, confidence, effort, subject attitude). Furthermore, Archambault et al. ( 2017 ) found unique effects of close teacher-student relationships on behavioral engagement in Canadian third and fourth grade primary education classes (regular and special education); however, they did not find an effect on emotional engagement. Also, the study of Lam et al. ( 2012 ), investigating the relationship between teacher (mainly emotional) support (referring to teachers at school) and student engagement (composite of emotional, behavioral, and cognitive engagement) in the lower grades of secondary education in 12 countries, revealed a significant positive association between teachers’ emotional support and engagement. Likewise, Fatou and Kubiszewski ( 2018 ), studying the effect of the quality of the relationship between teachers and students (student perceptions) in grade 10–12 classes in France, found positive effects on engagement (composite of behavioral, emotional, and cognitive engagement).

Furthermore, Reyes et al. ( 2012 ), using the CLASS observation instrument, revealed that there was a positive relationship between teachers’ emotional support to their class and students’ engagement in fifth and sixth grade English language art classes even when controlled for the quality of class organization and teacher’s instructional support Footnote 16 and teacher characteristics (gender, educational attainment, teaching experience, burnout and teaching efficacy). The effects were robust for grade and gender. Furthermore, their study revealed that student engagement partially mediated the relationship between emotional support and academic achievement. Likewise, the Finnish study of Pöysä et al. ( 2019 ), using the CLASS-S, indicated that teacher’s emotional support in grade-7 mathematics and language art classes was positively associated with students’ situation-specific emotional engagement. However, they did not find significant relations with situation-specific behavioral/cognitive engagement. Virtanen et al. ( 2015 ) did not find a direct effect of emotional support on student engagement in Finnish grade 7–9 classes, however, emotional support contributed to student engagement indirectly via its effect on teachers’ organizational and instructional support. Malmberg et al. ( 2010 ), also using the CLASS-S, found that observed student engagement in English classes was higher in lessons with high emotional support, classroom organization, and instructional support.

Also, other studies investigating the effects of being in emotionally supportive classrooms report positive effects on motivational outcomes such as enjoyment, interest, and engagement (e.g., Wentzel et al., 2010 ; You & Sharkey, 2009 ; Fauth et al., 2014 ). In addition, studies using the WIHIC in primary or secondary classes in a variety of countries found evidence for positive effects of supportive teachers on attitudinal outcomes such as enjoyment related to science, math, or language subjects (e.g., Chionh & Fraser, 2009 ; Telli et al., 2006 ; Wolf & Fraser, 2008 ). Other studies adopting the SDT framework and investigating associations between student perceptions of teacher involvement and motivation or academic engagement, found evidence for the importance of teacher involvement as well. For example, research of Bieg et al. ( 2011 ) shows that students’ perception of teacher care in eighth grade was linked to higher intrinsic motivation in physics. Skinner and Belmont ( 1993 ) found evidence for the importance of student perceptions of teacher’s involvement to emotional engagement in primary education, while Lietaert et al. ( 2015 ) and Opdenakker ( 2021 ) found positive effects on, respectively, behaviour engagement and a composite measure of behavioral and emotional engagement in secondary education (respectively in Dutch language, and EFL/math classes). Also, other work of Opdenakker, Maulana, Stroet and colleagues in the Netherlands (Maulana et al., 2013 ; Opdenakker, 2013 , 2014 ; Opdenakker & Maulana, 2010 ; Stroet et al., 2015 ) indicates the importance of teacher involvement – which is important to meet students’ need to feel related to significant others – in relation to student motivational outcomes and academic engagement in primary as well as in general and prevocational secondary education.

In addition, Opdenakker and Minnaert ( 2014 ) found evidence for the importance of feeling related with the teacher on primary school students’ engagement. Also, the review study of Stroet et al. ( 2013 ) confirms these findings with regard to engagement and motivation, as well as their longitudinal study on associations between observed teacher involvement and motivational outcomes in grade-7 prevocational math classes (Stroet et al., 2015 ).

In line with this, numerous studies have found evidence for the importance of a good relational climate in classes (referring to, among others, good teacher-student relations) (For reviews, see Opdenakker, 2020 ; Roorda et al., 2011 ; Stroet et al., 2013 ). A few studies (e.g., Opdenakker, 2021 ) also paid attention to need-thwarting teacher behaviour such as teacher neglect and rejection and found negative effects on students’ engagement. Likewise, Archambault et al. ( 2017 ) found negative effects of conflictual teacher-student relationships on students’ emotional engagement (for boys only). However, they did not find an effect on behavioral engagement.

Some studies also paid attention to the possibility of differential effectiveness of teachers’ emotional support, involvement, and positive teacher-student relationships in relation to student (background) characteristics such as gender, socioeconomical status or ethnicity. According to the academic risk hypothesis (Hamre & Pianta, 2001 ), teacher support in terms of an emotionally warm and caring, low-conflict teacher–student relationship is considered to be more important for students at risk (for school failure). In line with this hypothesis, the meta-analysis of Roorda et al. ( 2011 ), investigating the effect of teachers’ emotional support/involvement on students’ engagement, revealed that this kind of teacher behaviour was more important for boys’ than for girls’ engagement, indicating a higher sensitiveness of boys. Also, Furrer and Skinner ( 2003 ) and Opdenakker ( 2021 ) found support for a higher sensitiveness of boys regarding respectively perceived relatedness with the teacher, and teachers’ emotional involvement and neglect/rejection.

Archambault et al. ( 2017 ) found that only boys seemed to be sensitive to conflictual teacher-student relationships regarding their emotional engagement and Fatou and Kubiszewski ( 2018 ) also found that only boys were sensitive to the quality of teacher-student relationships with regard to emotional engagement. However, when focusing on a composite of engagement, cognitive or behavioral engagement they did not find evidence for the differential effectiveness of teacher-student relationships in relation to gender. Also, other studies (e.g., Lam et al., 2012 ; Lietaert et al., 2015 ; Wang & Eccles, 2012 ) found no evidence for differential effectiveness regarding gender and some found that girls seemed to be more sensitive to warm and close relationships with teachers (e.g., Archambault et al., 2017 ). Likewise, research of Pöysä et al. ( 2019 ) suggested that girls benefited more from high emotional support than boys for their situation-specific emotional engagement.

Studies addressing differential effectiveness of teachers’ emotional support related to racial or ethnic differences are rather scarce and results seem to be mixed, but when differences are found they seem to be in line with the academic risk hypothesis (Wang & Eccles, 2012 ; Konold et al., 2017 ). Den Brok et al. ( 2010 ) found no evidence for differential effects of teacher proximity on students’ subject attitudes (including enjoyment, interest, and effort) related to students’ ethnicity, however they found differential effects of teachers’ interpersonal behaviour related to influence indicating that only students with a non-Dutch background (of the second generation) were sensitive to influence in relation to their engagement. Studies addressing differential effectiveness of the quality of teacher-student relationships in relation to the social background of students are scarce as well. Fatou and Kubiszewski ( 2018 ) studied the differential effectiveness of perceived quality of teacher-student relationships and found only evidence regarding cognitive engagement indicating that especially students with a more privileged social background were more sensitive.

5.2 Effects of Teachers’ Classroom Management and Organization

Many studies have reported positive effects of classroom management on student academic outcomes (Seidel & Shavelson, 2007 ). Good classroom management helps to create good preconditions for time on task that is, in turn, crucial for students’ learning and achievement (Seidel & Shavelson, 2007 ). An important question is whether good classroom management has also positive effects on motivational outcomes (such as engagement, intrinsic motivation for learning/working in class, and interest). Some researchers point to the possible detrimental effect it can have on students’ motivational development (McCaslin & Good, 1992 ), since well-managed classrooms can be quite teacher-directed and are characterized by external regulation of student behaviour.

There is surprisingly little research on the effects of classroom management on motivational outcomes (Kunter et al., 2007 ; Korpershoek et al., 2016 ). Research of e.g., Klieme et al. ( 2009 ) reports positive effects of observed classroom management (based on an observation of three lessons) on students’ intrinsic motivation (working interest; measured with an immediate posttest and controlled for interest in the subject mathematics at the beginning of the school year) in secondary education of schools in Germany and Switzerland. Also, Kunter et al. ( 2007 ), re-analyzing data regarding mathematics education from the German sample of the Third International Mathematics and Science Study (TIMSS, Beaton et al., 1996 ), found evidence for significant, but weak effects of math teachers’ classroom management: (individual) students’ perceptions of rule clarity and teacher monitoring were positively related to their math-related interest development. However, no (additional) effects were found for classroom management at class level. In addition, their study demonstrated that the effects of rule clarity and monitoring were partially mediated by students’ experiences of autonomy and competence.

From the TTI (Teaching through interactions) framework there is some evidence for the importance of classroom organization. For example, Virtanen et al. ( 2015 ), using the CLASS-S, demonstrated a positive relation between both classroom organizational (and instructional) support and student-rated, teacher-rated, and observed general behavioral engagement among lower secondary school students in Finland. Furthermore, Pöysä et al. ( 2019 ), using the CLASS-S, found that classroom organization was positively associated with students’ situation-specific behavioral/cognitive engagement in Finnish grade-7 mathematics and language art classes. However, they did not find significant relations with situation-specific emotional engagement. Also, Malmberg et al. ( 2010 ), using the CLASS-S, found evidence for the importance of the mentioned characteristic: observed student engagement was higher in lessons with high classroom organization, (and high emotional and instructional support).

Van de Grift ( 2007 ) found, using the ICALT instrument, a positive association between classroom management and observed student involvement in primary education across four European countries ( r  = 0.54). Also, van de Grift et al. ( 2017 ), using the same instrument in a study on South Korean and Dutch secondary education teachers, reported positive associations between classroom management and observed student engagement at class level (γ-coefficients between latent dimensions and engagement at class level were respectively 0.80 and 0.79).

Also, Opdenakker and Minnaert ( 2011 ), using the student perceptions questionnaire of ISTOF, reported effects of classroom management on academic engagement in primary education in the Netherlands. However, the effect disappeared when controlled for student background characteristics (gender, nationality, language spoken at home) and prior engagement. Furthermore, Maulana et al. ( 2016 ) found small, but significant, effects of perceived classroom management in secondary education on motivational aspects such as intrinsic value and self-efficacy. However, they did not find an effect on test anxiety.

In addition, Tas et al. ( 2018 ) report that it is possible to train student teachers to improve their teaching skills and, in particular, their classroom management. They found a large effect size representing student teachers’ improvement in classroom management. Furthermore, research has also established that teachers trained in classroom management principles and concepts were more likely to have engaged students compared to teachers in control groups (Emmer & Strough, 2001 ). In contrast, in a meta-analysis on classroom management interventions Korpershoek et al. ( 2016 ) did not find a significant effect of these interventions on student motivational outcomes. However, their results must be interpreted with caution since they were only related to six studies.

Studies addressing differential effectiveness of teachers’ classroom management and organization are very scarce. Pöysä et al. ( 2019 ) investigated this in relation to student gender in secondary education and did not find evidence for differential effects on student engagement. Also, Opdenakker and Minnaert ( 2011 ), studying this in primary education, did not find evidence for differential effects related to student gender, nor did they find such effects in relation to students’ prior engagement and ethnic-cultural background.

5.3 Effects of Teachers’ Instruction and Instructional Support

Numerous studies have paid attention to effects of teachers’ instruction and instructional support on student academic achievement, in particular studies grounded in teacher and educational effectiveness research, and they have found clear evidence of the importance of the quality of teachers’ instruction and instructional support (Muijs et al., 2014 ; Opdenakker, 2020 ). However, teacher effectiveness frameworks often recognize the importance of motivation and engagement as precursors for achievement. Therefore, it is also relevant to see whether characteristics of teachers’ instruction and instructional support have effects on motivational outcomes as well.

In a study of Fauth et al. ( 2014 ), which used the model of instructional quality of Klieme et al. ( 2009 ), evidence was found for the importance of cognitive activation and supportive climate (referring to teachers’ constructive feedback and encouragement as well as to teachers’ warmth and friendliness) to primary school students’ development of subject-related interest.

Also, studies rooted in the TTI framework and using the CLASS/CLASS-S instrument deliver information on the relevance of teacher behaviour related to instructional support. For example, Virtanen et al. ( 2015 ) demonstrated a positive relation between instructional support and student-rated and observed general behavioral engagement among lower secondary school students in Finland and Malmberg et al. ( 2010 ) also found that observed student engagement was higher in lessons with high instructional support. However, surprisingly, Pöysä et al. ( 2019 ), investigating relations between observed instructional support in relation to a variety of situation-specific engagement indicators in Finnish grade-7 mathematics and language art classes, did not find a significant effect of (class-level) instructional support on situation-specific engagement.

Based on self-determination theory and using the TASC (student perceptions), Lietaert et al. ( 2015 ), Opdenakker ( 2021 ), and Opdenakker and Maulana ( 2010 ) found evidence for positive effects of students’ perceptions of structure support on (growth in) academic engagement in the seventh grade (first year in secondary education) in Flanders (Belgium) and the Netherlands. Also, research of Hospel and Galand ( 2016 ), investigating effects of structure (and autonomy support) on behavioral, emotional, and cognitive engagement in secondary education in Belgium (French-speaking part), demonstrated clear positive associations with students’ engagement (all aspects). In addition, Skinner and Belmont ( 1993 ), studying relations between student perceptions of structure, autonomy support and involvement and behavioral engagement in primary education, found evidence for the importance of (unique) effects of structure, and Opdenakker and Minnaert ( 2011 , 2014 ) found, respectively, positive effects of the teacher as a helpful and good instructor and of students’ basic need fulfilment of competence by the teacher on primary school students’ engagement. Also, the study of Lazarides and Rubach ( 2017 ) in secondary school classes in Berlin (Germany) showed that support for competence predicted intrinsic motivation and effort (via students’ mastery goal orientation). Maulana et al. ( 2016 ) found positive effects of clarity of instruction on students’ intrinsic value for the subject and self-efficacy and negative effects on test anxiety in secondary education in the Netherlands. Also, Opdenakker ( 2013 , 2014 ) and Stroet et al. ( 2015 ), investigating student motivation and academic engagement in prevocational and general secondary education in the Netherlands, found evidence for the importance of structure.

In addition, the study of Opdenakker ( 2021 ) revealed negative effects of chaos and inconsistency, which is often seen as the opposite of structure, on students’ engagement. Furthermore, her study revealed evidence for differential effects of structure (but not of chaos/inconsistency) indicating that boys were more sensitive to structure than girls in relation to their engagement. However, the study of Lietaert et al. ( 2015 ) did not reveal evidence for this. Furthermore, research of Opdenakker and Minnaert ( 2014 ) found that teachers’ fulfillment of primary students’ needs to feel competent, which can be realized by offering structure, was more important for initially high academic engaged students.

Intervention studies reveal that it is possible to train teachers to successfully apply the more difficult instruction and teaching activities such as adapting instruction (more) to differences between students, and, that this training also has positive effects on student outcomes. However, research also indicates that this requires focused coaching and systematic observation of teacher’s teaching during 1 or 2 years (van de Grift et al., 2011 ).

Furthermore, a few studies addressed the topic of differential effects. For example, Opdenakker and Minnaert ( 2014 ) Footnote 17 investigated differential effects of primary school teachers’ fulfillment of the need to feel competent and found evidence that initially high academic engaged students are more sensitive. Other studies found differential effects of structure in secondary education mathematics and EFL classes for boys and girls in relation to engagement indicating a higher sensitivity of boys (Opdenakker, 2021 ). In contrast, Tucker et al. ( 2002 ) did not find gender differences in the relation between teacher structure and student engagement, nor did Lazarides and Rubach ( 2017 ) found this with regard to the relation between teachers’ support for competence and student motivational outcomes.

5.4 Learning Climate

Next to the quality of the teacher-student(s) relationship, which makes up the relational climate in classes in addition to student-student relationships, the class learning climate is often mentioned in learning and educational effectiveness research as well in theories and research on motivation, as an important class characteristic that influences students’ learning and engagement in school. Characteristics of the classroom context as well as teachers’ behaviour play a role in the creation of a good learning climate, which is often defined in terms of a stimulating and safe learning climate or a study-oriented learning climate. Evidence for the effectiveness of a study-oriented learning climate in relation to motivational outcomes is found in a diversity of studies (e.g., Dumay & Dupriez, 2007 ); Opdenakker, 2004 ; Opdenakker et al., 2005 ; Van Landeghem et al., 2002 ). Also, Telli et al. ( 2006 ), using the WIHIC, found indications that task orientation, a dimension in the WIHIC that refers to the learning climate in the class, was associated with students’ attitudes towards biology in Turkish secondary education. Van de Grift et al. ( 2017 ), using the ICALT, reported a clear positive relation between a safe and stimulating learning climate in teachers’ secondary education classes and student engagement in these classes in South Korea and the Netherlands. Likewise, Hughes and Coplan ( 2018 ), using a composite classroom climate indicator (based on the COS-instrument) referring to the degree to which the primary school teacher is supportive and creates a positive child-centered classroom, found evidence for a positive association between classroom climate and student behavioral engagement. In addition, they also found evidence for differential effects of classroom climate in relation to student gender and anxiety indicating that, in particular, boys and students with high anxious solitude were particularly susceptible to the classroom climate.

5.5 Effects of Teachers’ Autonomy Support

There is clear evidence that meeting students’ need to feel autonomous and teachers’ autonomy support is important for students’ engagement and (intrinsic or autonomous) motivation (Opdenakker & Minnaert, 2014 ; Ryan & Deci, 2020 ; Stroet et al., 2013 ). This evidence is clear regarding students’ engagement and motivation, across multiple educational settings and cultures, and across a variety of subjects (e.g., STEM, languages, physical education). For example, Hagger et al. ( 2015 ) found evidence for the importance of teachers’ autonomy support (students’ perceptions) on Pakistan secondary school students’ math engagement (homework completion), while the study of Tsai et al. ( 2008 ) revealed evidence for positive effects of autonomy-supportive teacher behaviour such as understanding and taking the perspectives of students (student perceptions) on students’ motivation and interest in math lessons. Studies of Bieg et al. ( 2011 ) and Jungert and Koestner ( 2015 ) also found evidence of this kind of teacher behaviour in relation to intrinsic motivation in STEM subjects. Also, the studies of Black and Deci ( 2000 ), Reeve and Jang ( 2006 ), and Roth et al. ( 2007 ) revealed positive effects of autonomy support on (autonomous) motivation, while Black and Deci ( 2000 ) also found positive effects on students’ perceived competence. Assor et al. ( 2002 ) found that fostering relevance (a component of autonomy support) was positively associated with student engagement. Effects of autonomy support on students’ engagement and autonomous motivation were also found in numerous other studies done e.g., in Europe (e.g., Núñez & León, 2019 ), the US (e.g., Reeve et al., 2004 ; Skinner et al., 2008 ) and Russia (Chirkov & Ryan, 2001 ), and there is also some evidence of the importance of autonomy support in more advanced educational settings (see Ryan & Deci, 2020 ).

Also, in the Netherlands and in Flanders (Belgium) research has demonstrated positive effects of autonomy-supportive teaching behaviour on students’ academic engagement in secondary education (Lietaert et al., 2015 ; Opdenakker & Maulana, 2010 ; Opdenakker, 2014 , 2021 ) and of the stimulation of active learning Footnote 18 in Dutch primary education (Opdenakker & Minnaert, 2011 ). The study of Hospel and Galand ( 2016 ) in the French-speaking part of Belgium, found evidence of (unique) effects of autonomy support on emotional (and behavioral) engagement; however, no significant effect on indicators of cognitive engagement were discovered.

Research on the differential effectiveness of autonomy support in relation to student motivational outcomes is scarce. Lietaert et al. ( 2015 ) found that only boys seemed to be sensitive to autonomy support regarding their engagement in secondary education, while Opdenakker ( 2021 ) found that girls seemed to be less sensitive than boys (but still significant sensitive) to autonomy support. However, Opdenakker ( 2021 ) found no evidence for differential effectiveness of controlling teaching behaviour, that is often seen as the opposite of autonomy support, in relation to student gender. Regarding the stimulation of active learning and differentiation, no differential effects were found related to gender, ethnic-cultural background, and prior engagement in a study on primary school students’ engagement (Opdenakker & Minnaert, 2011 ).

In some (other) studies, effects of controlling behaviour on motivational outcomes were explored as well. In general, negative effects of controlling teacher behaviour were found on autonomous motivation (Reeve & Jang, 2006 ) and engagement (Opdenakker, 2021 ). In addition, the study of Assor et al. ( 2005 ) in Israeli primary education indicated associations with motivational orientations (extrinsic motivation and amotivation), which was partially Footnote 19 mediated by negative emotions (anger, anxiety, nervousness). In addition, negative effects were found on engagement. Furthermore, evidence is found that perceptions of increases in controlling teacher behaviour are related to increases in need frustration across the school year which, in turn, relate to lower autonomous motivation, greater fear of failure, contingent self-worth and avoidance of challenges (Liu et al., 2017 ). In addition, there is some evidence that showing disrespect (a component of autonomy thwarting) is negatively associated with students’ engagement (Assor et al., 2002 ) and that this component has a unique effect (as well as fostering relevance) on students’ engagement. There is some evidence of biological mediators at work in the effects of autonomy-supportive versus controlling teacher behaviour indicating that the exposure to a controlling teacher is associated with higher cortisol values compared to a neutral or autonomy-supportive teacher (Reeve & Tseng, 2011 ), while being in learning environments characterized by autonomy support and attention to relatedness is accompanied by a higher heart rate and emotional arousal indicative of greater mobilization of energy and engagement (Streb et al., 2015 ).

Several intervention studies indicate that it is possible to help teachers to become more autonomy-supportive, with subsequent positive student outcomes such as engagement and autonomous motivation as a result (Assor et al., 2009 ; Reeve et al., 2004 ; see also meta-analysis of Su & Reeve, 2011 ).

In this context, it is relevant to mention that a lot of research using the framework of SDT delivers evidence of the importance of combining autonomy support with structure (Jang et al., 2010 ; Vansteenkiste et al., 2012 ; Sierens et al., 2009 ; Hospel & Galand, 2016 ). This means that it is important for students’ motivation and engagement that teachers not only consider and welcome students’ perspectives, feelings and thoughts, give them choices and allow them multiple approaches and ways to do learning tasks and solve problems, but that teachers also (instructionally) support and guide their students and provide them with clear expectations, instruction(s) and constructive feedback (Jang et al., 2010 ; Reeve, 2009 ; Skinner & Belmont, 1993 ; Stefanou et al., 2004 ; Vansteenkiste et al., 2006 ). The combination of high teacher autonomy support and structure has been empirically associated with not only higher autonomous motivation, but also with greater use of self-regulated learning strategies and lower test anxiety, referring to respectively cognitive and emotional engagement/disengagement (e.g., Vansteenkiste et al., 2012 ; Sierens et al., 2009 ). In addition, intervention research of, among others, Kiemer et al. ( 2018 ) and Cheon et al. ( 2020 ) reveal that it is possible to train teachers to behave more autonomy and competence supportive.

5.6 Unique or Joint Effects of Teacher Behaviour Dimensions and What Matters Most in Relation to Motivational Outcomes?

Not many studies address these topics explicitly. However, when studies include several dimensions of teacher behaviour simultaneously in the model of analysis, it is possible to make inferences about the unique effects of the dimensions in relation to the investigated outcome as well as to compare the size of effects.

Overall, there is evidence for statistically significant unique effects of the distinguished teacher behaviour dimensions in instruments discussed before on motivational outcomes (e.g., Furrer & Skinner, 2003 ; Jang et al., 2010 ; Nie & Lau, 2009 ; Opdenakker & Maulana, 2010 ; Opdenakker & Minnaert, 2011 ; Skinner et al., 2008 ; Tucker et al., 2002 ), although clear joint effects of the dimensions are also present. The existence of joint effects is not surprising since clear associations between dimensions of teacher behaviour were already mentioned in a previous section of this chapter. Finding unique effects of teacher behaviour dimensions indicates that these dimensions operate – at least partly – independent of each other and in a unique way to students’ motivational outcomes. There is also some evidence that this is the case with regard to need-supportive versus need-thwarting teacher behaviour in relation to motivational outcomes (e.g., Assor et al., 2002 ; Opdenakker, 2021 ). However, there are also a few studies that did not find unique effects for all included (positive) dimensions of teacher behaviour (e.g., the studies of Reyes et al. ( 2012 ) and Pöysä et al. ( 2019 ), using the CLASS instrument, and the study of Hospel and Galand ( 2016 ) measuring autonomy support and structure within the theoretical framework of SDT). In addition, the study of Hospel and Galand ( 2016 ) revealed that finding unique (and mutually reinforcing) effects also depends on the type of motivational outcome investigated.

This is also the case regarding the size of effects of teacher behaviour dimensions (see e.g., Skinner & Belmont, 1993 ), although there are some general tendencies as well. For example, there are some indications in studies investigating teachers’ instructional support or providing structure (including clarity of instruction) and classroom management/organization that the latter has smaller effects on motivational outcomes such as academic engagement and intrinsic value than providing structure, clear instruction or instructional support (Maulana et al., 2016 ; Opdenakker & Minnaert, 2011 ).

When comparing effects of emotional support (or positive teacher-student relationships or teacher involvement) with instructional support (or structure or clarity of instruction), results seem at first sight a bit mixed. For example, in some studies (e.g., Lietaert et al., 2015 ; Reyes et al., 2012 ; Stroet et al., 2015 ) teacher involvement is (somewhat) more important than providing structure in relation to students’ engagement (or other motivational outcomes), while in other studies (e.g, Opdenakker, 2021 ; Opdenakker & Minnaert, 2014 ) the effect of providing structure is (somewhat) larger than the effect of involvement. A deeper inspection of the mentioned studies reveals that differences in student population between the studies might be an explanation, indicating that for students of lower tracks (and with more disadvantaged backgrounds) emotional support of teachers seem to be (a bit more) important then providing structure compared to students of higher tracks (and more advantaged backgrounds) in relation to motivational outcomes, although both forms of support are important for both groups. Skinner and Belmont ( 1993 ) found, according to their path analyses, that student perceptions of teacher structure were a unique predictor of students’ behavioral engagement, while students’ perceptions of teacher involvement were a unique predictor of students’ emotional engagement. However, an inspection of the correlations revealed that differences in associations were very small, which is in line with findings of Opdenakker and Maulana ( 2010 ) in terms of explained variance by teacher involvement and structure in relation to students’ (mainly behavioural) engagement during a school year and is in line with research of de Boer et al. ( 2016 ) finding the same results with regard to intrinsic motivation of gifted students in the lower grades of secondary education in the Netherlands. In addition, their study revealed that satisfying the need to feel competent was clearly the most important need to satisfy for the intrinsic motivation of these students. Furthermore, the study indicated that teacher involvement had an additional positive effect to the effect of meeting the need to feel competent on these students’ intrinsic motivation.

6 Effects of Contexts and Other Antecedents on Teacher and Teaching Behaviour

Teachers do not operate in a contextual vacuum. In their classes, they are confronted with students with specific characteristics as individuals and as a group and with structural factors such as class size, they must operate in a particular school context with its own culture, climate, policies and leadership style, they have to behave in a particular educational system with its particular characteristics (e.g., mandated curricula; student grouping system, tracking/no-tracking, etc.), educational policies, etc. In educational effectiveness research, the importance of context is recognized for several decades. For example, educational effectiveness models such as the Comprehensive Model of Educational Effectiveness of Creemers developed in the 1990s already included context factors at class, school and above, and Reynolds, a famous educational effectiveness scholar, stated in a publication in 2000 (Reynolds, 2000 ) that it was necessary to study the relationships between processes, outcomes, and contexts to understand how different instructional variables relate to student outcomes in different contexts. However, until now not many (educational effectiveness) studies have been conducted to identify factors operating at the context level (Kyriakides et al., 2020 ). This is also the case regarding relations between school level characteristics (and class level characteristics) and teacher behaviour in classes (Opdenakker, 2020 ). Furthermore, the studies that investigated relations between school level characteristics and learning environment/teacher behaviour did not find strong associations (Opdenakker, 2020 ).

A few exceptions are found in research work Footnote 20 on the relationship between school/classroom context/group composition and learning environment characteristics (including teacher behaviour) (e.g., of Battistich et al., 1995 ; Crosnoe & Johnson, 2011 ; Johnson & Stevens, 2006 ; Maulana et al., 2016 ; Opdenakker, 2004 ; Opdenakker & Van Damme, 2006 ). In general, indications are found that classes and schools with favorable student populations (with regard to cognitive ability, SES, parental involvement or ethnical background) often have more favorable learning environments including more instructional support (see e.g., Opdenakker, 2004 , 2019 ; Opdenakker et al., 2005 ; Opdenakker & Van Damme, 2006 ), more clarity of instruction (e.g., Maulana et al., 2016 ; Opdenakker, 2019 ), and a more favorable relational climate in the class (including the relationship between teacher and students and peer relations) (Opdenakker, 2004 ; Opdenakker & Van Damme, 2006 ). There is also some evidence of a less decrease in autonomy support during the school year in classes with a favorable student (ability) composition compared to classes with a less favorable composition (Opdenakker, 2014 ). One of the reasons could be that less favorable student populations are more challenging because they are less inclined to cooperate with teachers.

In addition, also individual student characteristics seem to matter. For example, research of Skinner and Belmont ( 1993 ) revealed a positive relationship between signs of students’ engagement and the likeliness that their teachers are involved and display greater autonomy support, and more structure (contingency and consistency). Teachers respond to students who are more passive with correspondingly more neglect, coercion, and even inconsistence. When students seem to be disengaged, their teachers are less likely to provide need-supportive teaching (Escriva-Boulley et al., 2021 ), exhibit more control and less autonomy support over time (Jang et al., 2016 ). Connell and Wellborn ( 1991 ) mentioned that teachers reported themselves that they were less involved and offered less autonomy support to disaffected students.

Furthermore, school factors such as cooperation between teachers, school leadership style, constraints at work (e.g., accountability policy), and student-teacher ratio seem important. For example, research of Opdenakker and Van Damme ( 2006 , 2007 ) revealed that cooperation between teachers at school is positively related to the quality of the relational and learning climate in classes (including teacher-student relationships), and that the school leader leadership style (namely the degree to which the leader uses a participative style and is professionality-oriented with regard to the teachers) seems to be of importance for teachers’ instructional support to their classes. In addition, evidence is found for a negative relation between constraints at work (e.g., experiencing a pressuring school environment) and teachers’ psychologically controlled teaching behaviour (Soenens et al., 2012 ). In the same vein, research of Deci et al. ( 1982 ) has shown that the use of controlling teaching practices increases when teachers are under pressure (for example, when teachers are evaluated on students’ achievement level), indicating that school systems using frequent comparative achievement tests might be pushing their teachers to rely on directly controlling teaching practices. Also, research of Pelletier et al. ( 2002 ) indicates that pressures from above (e.g., when teachers must comply with a curriculum, with colleagues, and with performance standards) is associated with more controlling and less autonomy-supportive teacher behaviour because teachers become less self-determined toward teaching. Furthermore, Ryan and Deci ( 2020 ) mention negative effects of an excessive emphasis on grades, performance goals, and pressures from high-stakes tests on teachers (and students). In addition, Cipriano et al. ( 2019 ) found that student-teacher ratio at school level was negatively associated with student perceptions of teacher support. Furthermore, research of Escriva-Boulley et al. ( 2021 ) indicated that need-thwarting teacher behaviour was positively predicted by pressure to display authority and beliefs about the effectiveness of rewards, referring to a pressure at school level.

Lastly, also teacher characteristics such as teaching style, adherence to entity theory, teaching experience, teachers’ motivation to teach, teachers’ basic need satisfaction and teachers’ job satisfaction are of importance. For example, Opdenakker and Van Damme ( 2006 ) found that a learner-centered teaching style seemed to matter regarding the amount of instructional support teachers gave to their classes as well as regarding the quality of the teacher-students relationship, and Escriva-Boulley et al. ( 2021 ) found that teachers’ adherence to entity theory predicted negatively need-supportive teacher behaviour. Cipriano et al. ( 2019 ) found positive associations between teaching experience and student perceptions of teacher support. Furthermore, research of Roth et al. ( 2007 ) revealed that teachers who were more autonomously motivated to teach were perceived by their students as more autonomy-supportive (and their students were more autonomously motivated to learn). However, Opdenakker ( 2019 ) did not find an association between teachers’ motives for work and autonomy support, structure/clarity of instruction, classroom management and teacher involvement. Klassen et al. ( 2012 ) reported about studies showing that when teachers experienced more satisfaction of the need to feel related with their students, they were more engaged and reported less emotional exhaustion. However, Opdenakker ( 2019 ) did not find a relationship between feeling related or feeling autonomous and teacher behaviour, but, feeling competent and effective seemed to be positively related to classroom management. Furthermore, teachers’ job satisfaction was positively related to teachers’ involvement towards students.

Effects of teacher gender are seldom found (e.g., Maulana & Opdenakker, 2014 ; Maulana et al., 2012 , 2016 ; Opdenakker, 2014 ; Opdenakker & Maulana, 2010 ) and effects of subject taught are seldom studied, and if investigated, most of the time no effects are found (e.g., Maulana & Opdenakker, 2014 ; Maulana et al., 2012 ; Opdenakker, 2014 ; Opdenakker & Maulana, 2010 ). An exception is the study of Opdenakker et al. ( 2012 ) in which students in classes of female teachers perceived less proximity in their relationship with the teacher compared to students in classes with a male teacher. In addition, the study of Opdenakker and Van Damme ( 2007 ) revealed that male teachers tend to maintain classroom order better than their female colleagues. In the same line, the study of Van Petegem et al. ( 2005 ) indicated that classroom leadership and friendliness were more associated with male than with female teachers. Furthermore, Opdenakker ( 2019 ) found that teacher experience seems to matter only for male teachers regarding (student perceptions of) provided structure, clarity of instruction, autonomy support and teacher involvement; however, regarding classroom management, teacher experience mattered in a positive way for male and female teachers. In addition, there was evidence for differences in the average level of structure and autonomy support of math and English classes in favor of the math classes.

7 Conclusions, Reflections, Implications and Suggestions for Future Research Directions and Practice Related to Effective Teacher and Teaching Behaviour

A first finding reviewing current conceptualizations, measurements and instruments of teacher and teaching behaviour from a variety of perspectives was the number of different terms that were used to refer to classroom processes or practices and behaviour of teachers who appear to be good, successful, or effective in their teaching. A more sparing use of terms and clear definitions is preferable.

Second, the review indicated that a variety of research domains have an interest in classroom processes/practices and behaviour of teachers (and in their effects on student outcomes) and that, within these domains, instruments were developed to measure (the quality of) them. Dependent on the domain, these instruments are more/less grounded in theory; however, most of them are at least based on literature about ‘what seems to work’. When comparing the instruments (and the theories on which they were grounded), there are many similarities in terms of the content of quality practices. However, there are differences regarding the number of distinguished dimensions (sometimes named factors or domains) as well as with the names, wordings, and descriptions of the content of the dimensions leading to concepts with – to some degree – different descriptions and to different concepts with more or less the same meaning. It would be an advancement for the study of teacher behaviour and for the search for quality teaching practice if concepts were well-defined and uniformly used.

In addition, it would be a good idea to combine instruments in future research in the same study to investigate differences and similarities regarding concepts, operationalizations of concepts and effects of them on student outcomes, since this can help with further clarification and defining concepts. Furthermore, taking them together in one study also has more potential to yield a more comprehensive delineation of the phenomenon at hand. Still more work is needed regarding the conceptualization, operationalization, and the measurement of (the quality of) teaching and teacher behaviour and its dimensions. Kyriakides et al. ( 2020 ) reached a similar recommendation in their recent work on educational effectiveness research.

Third, the exploration of instruments and theories indicated that, in general, all the instruments (and theories) have in common an attention to teacher support and most of them address support in the domain of relation/emotion and the instructional domain. In most instruments and theories these are separated and in some it is conceptualized as one dimension. Based on the findings described in previous sections of this article, it is preferable to separate them not only because both measure on a conceptual level different things and (can) have different effects on (different) outcomes, but also because it is of importance to know where to work on in the context of professional development and learning.

In addition, most of the instruments/theories include a dimension (or subdimension) referring to class organization/management. Some instruments/theories also refer to other dimensions like autonomy support, cognitive activation, active learning, or attention to differences/differentiation. These dimensions are often included in the instruments to accommodate to newer understandings of learning and teaching. Since not only new theories on learning will be developed, but also learning in an online context will become more and more part of the teaching practice of teachers (due to and stimulated by the COVID-19 pandemic), it will be a challenge for researchers investigating (effects of) the behaviour of teachers and classroom processes to adapt their instruments to these new educational arrangements with corresponding teacher behaviour and teaching practice as well.

Forth, an important question addressed in one of the previous sections is if teaching (and teacher behaviour) must be considered/conceptualized as one-dimensional or as multidimensional/multifaceted. In fact, based on the findings described before, there is something to be said for both sides. Research with the ICALT instrument finds evidence for the one-dimensionality perspective, while research with other instruments often finds, although associations between the distinguished dimensions do exist, for the multidimensional/multifaceted perspective. An interesting perspective in line with the ‘more than one’ dimensionality perspective is research work on configurations (whether or not combined with the circumplex model). The results described in the preceding sections reveal that there are, at one side, important associations between the distinguished teacher behaviour dimensions (in instruments and models) and common effects of these dimensions on motivational outcomes, and, at the other side, also evidence for unique effects (on top of the common effects) of teacher behaviour dimensions. These findings emphasize the importance of the need for more research on the dimensionality of teacher behaviour/teaching and of research on configurations and person-centered research to fully account for the importance of teachers and teaching in relation to student (motivational) outcomes.

Fifth, from the rather scarce research on the (in)stability of teaching and teacher behaviour there are indications for some instability of teaching and teacher behaviour (small to large changes) during the school year. There is evidence that, on average, the quality of teaching and teacher behaviour tends to decline from start to the end of the school year. This has implications for measuring teaching and teacher behaviour within a research context, but also within an accountability context. It is relevant to address questions like when and how many times a measurement is necessary to obtain good measurements of the quality of teaching and teacher behaviour.

Furthermore, the positive side of finding indications of some instability in teaching and teacher behaviour is that it is, at least, to some degree malleable and can be (positively) nurtured and advanced by professional development and learning and by favorable context conditions. Some work done in intervention studies, discussed in the preceding sections, underscore the malleability and potential for improvement of teaching and teacher behaviour; studies paying attention to links between teaching and teacher behaviour and context conditions also underscore this statement. Given the scarce research on the topic of (in)stability, more research is needed exploring stability and change between lessons and within teachers.

Sixth, a related question has to do with who the best informants are to obtain a good indication or description of the (quality of) teaching or the behaviour of a teacher. Findings reveal that there is not a straightforward answer on this question since it also depends on the goal of the measurement. There are indications that when this goal is to explain student outcomes, student perceptions are (most) valuable (and observatory information – if possible – can be informative as well), but when the measurement is part of a professional development and learning trajectory of teachers, a combination of teacher perceptions and student perceptions seems to be more valuable as well as a combination with observer ratings. If the study is small-scale and the objective is to get a thick description of the teaching and behaviour of a teacher in a particular context and time period, then observation information as well as student perceptions are perhaps the best option. If the objective is to measure the perspectives of all participants in a teaching and learning context and to tap different aspects of the learning environment, than measuring teacher as well as student perceptions is a good option. The implications of all this are that for future research a deliberate decision is necessary about what the objectives of the study and the measurement of teaching/teacher behaviour are in order to decide who will be the best informants on teaching and teacher behaviour.

Seventh, an exploration of research on the links between teaching and teacher behaviour and student motivational outcomes revealed that teaching and teacher behaviour matter, and that the instruments discussed in the preceding sections to tap information on teaching and teacher behaviour are valuable in this respect.

Furthermore, it became clear that, in particular, supportive teacher behaviour (emotional supportive by being involved and creating warm positive relationships with students and instructional supportive by providing structure and having clear instructive lessons) is of relevance for students’ motivational outcomes. In addition, teachers’ autonomy support (by which students are valued and supported to become autonomous, active and have a hand in their own learning process) is of importance as well as the creation of a positive (study-oriented) learning climate. In contrast, conflictual teacher-student relationships and neglecting or rejecting teacher behaviour as well as controlling teacher behaviour and teacher behaviour characterized by chaos and uncertainty is harmful for students’ motivation and engagement.

Some studies also explored differential effectiveness issues in relation to student (background) characteristics such as gender, socioeconomical status or ethnicity. In general, some evidence has been found for the differential role of teacher (emotional and instructional/structure) support in relation to gender and motivational outcomes such as engagement, most of the time indicating that boys are more sensitive to teachers (involvement/emotional) support, provided structure, autonomy support, positive learning climate and teachers’ neglective or rejective behaviour). Studies addressing differential effectiveness of teachers’ (emotional) support related to racial or ethnic differences are rather scarce and results seem to be mixed, but when differences are found they seem to be in line with the academic risk hypothesis. Considering these limited (and sometimes contradictory) findings, additional research is needed to expand the knowledge base on differential effects of supportive teaching and teacher behaviour in relation to motivational outcomes.

Effects of classroom organization/management on motivational outcomes were also explored and it became clear that there is surprisingly little research on this topic. Although significant positive effects of this dimension were often found, this dimension was often not as strongly related to motivational outcomes as were the supportive dimensions of teaching and teacher behaviour. In addition, studies on differential effectiveness of this dimension were very scarce and delivered no evidence for the differential effectiveness of this dimension. For future research on the link between teaching and teacher behaviour and motivational outcomes, it seems worthwhile to explore the differential effectiveness of teaching and teacher behaviour in relation to gender. Furthermore, differential effectiveness in relation to other background characteristics, in particular from the academic risk hypothesis perspective, should be explored and perhaps a motivational risk hypothesis should be formulated.

Eight, studies investigating links between teacher behaviour, contexts and antecedents are scarce. The few studies available indicate that it is relevant to consider contextual and antecedent factors (such as student group composition and individual student characteristics, school culture, cooperation between teachers, school leadership, constraints at work, student-teacher ratio, and teacher characteristics) in research, assessments, and debates about quality of teachers and teaching since they influence how teachers do and construct teaching. This line of thought agrees with ideas and work of Devine et al. ( 2013 ). A clear understanding of the effects of context and student (group) characteristics on teaching and teaching behaviour is needed since it is not only relevant to know what is good and effective, but also what the circumstances are under which teachers can manifest teacher behaviour that is defined as good or has proven to be effective regarding students’ learning, development and particular outcomes. In addition, it is important to know when (circumstances, context, subject, or development domain) and for who (which kind of students) specific kinds of teacher behaviors or teaching styles are good and effective and to what degree. This asks for a perspective on teaching and teacher behaviour (in the classroom) that pays not only attention to teaching and teaching behaviour as being generic in nature (i.e. which can affect learning and development of all students in most contexts), but which also considers the broader context and situatedness of teaching and teachers’ behaviour, and is sensitive to complex and dynamic interactions between teacher behaviour and student characteristics/behaviour, differentiated effectiveness and the dynamic nature of goodness, effectiveness and successfulness of teaching and teacher behaviour. Such a perspective has the potential to contribute to the establishment of stronger links between research on the quality and effectiveness of teachers and teacher behaviour, and the improvement of teaching and classroom practice because by considering context and student (group) characteristics, it assumes more complex relationships between teaching/teacher behaviour and student learning/development/outcomes and as such, it assumes a more realistic model of educational practice. Otherwise stated, by adapting to the specific needs of students, teachers, or student groups, it is expected that the successful implementation of effective teaching factors or teacher behaviours will increase and that this will ultimately maximize their potential effect on students’ learning, behaviour, learning outcomes, and development.

In addition, such a perspective has the potential to help define stages of effective teaching and teacher behaviour in relation to (a diversity of) realistic educational settings and links it with equity issues as well since it takes into account differential effectiveness in relation to student (group) characteristics. The dynamic model of educational effectiveness of Creemers and Kyriakides ( 2008 ) can be seen as one of the first attempts to develop such a perspective in relation to teacher effectiveness. However, more research and theoretical work is needed to elaborate on the mentioned perspective in relation to (dimensions, dimensionality, and stages of) teaching and teacher behaviour in a diversity of educational settings (including educational levels and stages of schooling) and regarding a diversity of student outcomes and development. This will offer a more fine-grained conceptualization of effective teaching and teacher behaviour, and a more fine-grained insight in the (differential) effectiveness and successfulness of teaching and teacher behaviour, and in the underlying mechanisms and the conditions under which they can operate and contribute to equity in education. Such a perspective has the potential to address the complex nature of (effective) teaching in a more realistic way compared to most current perspectives. In addition to theoretical work, research is needed to investigate effects of characteristics and circumstances of above school level contexts such as educational systems on teaching and teacher behaviour. To realize this, international studies are also needed.

The literature reviewed in the preceding sections gives an overview of current conceptualizations, theories, operationalizations, instruments and research addressing (the quality of) teaching and teacher behaviour and provides clear evidence of the importance of teaching and teacher behaviour in relation to (the development) of student motivational outcomes such as autonomous and intrinsic motivation and student engagement. Teachers’ emotional support, involvement, quality of relationship with students, instruction, provision of structure/instructional support, the learning climate they create in their classes, their autonomy support and, to a lesser extent, also their classroom management and organization are key features accounting for links with students’ motivational outcomes. In addition, evidence is delivered that teachers seem to matter even more for specific students (such as boys and vulnerable students). Positive is the finding from intervention studies that teachers can be trained to become better and more supportive teachers. Together these findings endorse the importance of investing in teacher education and teacher professionalization and to focus on the just mentioned teacher and teaching behaviour dimensions since they can stimulate students’ (development of) autonomous and intrinsic motivation and engagement for school, which are important for students’ achievements in school and later life. The discussed instruments to measure teacher and teaching behaviour can be helpful tools to get an idea of current practices of teachers and to have a starting point for discussions about current and future practice with and between (student) teachers.

There is from a research point of view, however, still a lot of work to do and much about teachers’ significance (in a positive and a negative way) towards the development of students’ motivation and engagement is not well-understood yet. Continued efforts are needed to integrate findings and research from the variety of domains discussed above to produce new research and new research findings that can help to further our understanding of development processes related to motivation and engagement (and other student outcomes) and of ways in which teachers can help (and can be helped) to ameliorate, facilitate and avoid the hindering of these developments. In addition, the use of more holistic approaches to the study of teaching and teacher behaviour (e.g., the search for configurations) is important as well as the adoption of experimental designs within real classroom settings to study and test (normative) configurations of teaching, teaching strategies and (the improvement of) teacher behaviour. Lastly, it is essential to remember that what happens in classrooms is dependent upon complex interactions between teachers and students, each with its own individual characteristics, the context they are in, and time. This implies the use of more complex models such as cross-lagged panel and dynamic longitudinal designs in future research and further theory development as well.

In this chapter the terms teacher and teaching behaviour are used. In fact, teacher behaviour is a broader concept than teaching behaviour and it can include teaching behaviour. Nevertheless, it was opted to mention teaching behaviour in addition to teacher behaviour because it depends on the theoretical framework which concept is used in publications (and I wanted to stay as close as possible to the concepts used by authors in publications) and because it is informative to know if or that teaching behaviours of teachers are addressed in theoretical frameworks, conceptualizations and other relevant topics discussed in this chapter.

Hamre et al. ( 2013 ) also use the term teacher effectiveness.

The instruments that were constructed within the learning environments research tradition to make the characteristics of the learning environments visible and to get an impression of the quality of the psychosocial climate the teachers had created in their classrooms, deliver a good illustration of this emphasis. For an overview and description of de most famous instruments, see Fraser ( 2012 , 2019 ).

Recently, SDT researchers have begun to see and study these need-supportive and their need-thwarting “opposites” as separate dimensions (Opdenakker, 2021 ; Reeve et al., 2014 ). Furthermore, it is recognized that little support for the needs will lead to experiences of low/deprived need satisfaction, while a more direct thwarting of individuals’ needs lead to need frustration experiences (Ryan & Deci, 2017 ).

This familiarity between teacher involvement of the SDT and emotional support of the TTI is also recognized in Virtanen et al. ( 2018 ).

Another famous instrument is the CES (Moos & Trickett, 1974 ). Due to word constraints and because the CES is older than the WIHIC, this instrument was not included in this review.

However, there are also a few exceptions related to the CLASS as well as the ISTOF instrument. For a discussion of the first, see Virtanen et al. ( 2018 ), and for the second, see Muijs et al. ( 2018 ).

In this study, only autonomy support and structure were included. Confirmatory factor analysis indicated a significantly better fit for the two-factor model compared to the one-factor model.

In this study, a short version with an adaptation of the dimension ‘structure’ was used.

Jang et al. ( 2010 ) distinguished, in an observation instrument, between autonomy support and structure and found evidence based on confirmatory factor analysis that a two-factor model had a significant better fit than a one-factor model. However, they also explored how both dimensions relate to each other (antagonistic, curvilinear, independent) and found that both relate in al linear way.

In this study, primary teachers of the Netherlands, Flanders (Belgium), Germany, Slovakia, Croatia, and Scotland were observed.

The third dimension, namely teacher involvement, which relates to relatedness support, should be studied as well in relation to the circumplex model, since need-supportive teaching relates to three dimensions in order to fulfill the three basic psychological needs of feeling autonomous, competent and related. This view is underscored by Vansteenkiste et al. ( 2020 ).

They used the autonomy support dimension of the short version of the TASC (Dutch translation). For the dimension ‘clear expectations’, the ‘clarity of expectations’ of the Structure scale of the TASC (Belmont et al., 1988 ) was used as a source of inspiration. This scale was elaborated by (formulating additional) items on expectations regarding (1) the learning material and tests, and (2) desirable behaviour in class.

To some degree the configurations deliver evidence for the distinctness of the dimensions, although also evidence is found for a positive relation between them (since two out of four configurations refer to scoring in the same way on both dimensions). Moreover, the authors mention that they did not find strong evidence for unique correlates of both dimensions, albeit some relevant exceptions were found as well. Yet, several exceptions deserve being discussed.

The reported correlations are LISREL based φ-coefficients.

The effects of the quality of class organization and instructional support were not significant when included in the model together with emotional support and the mentioned teacher (and nonmentioned student) characteristics. This was the case for engagement and achievement and is contrary to studies showing that, at least, instructional support matters to academic achievement (Hamre & Pianta, 2005 ; Mashburn et al., 2008 ). One possible explanation that the authors mention is that instructional support and class organization may not have fully captured because they used a CLASS version developed primarily for lower elementary classrooms.

In addition, they found differential effects of teachers’ overall fulfillment of students’ psychological basic needs on engagement indicating that Dutch-speaking students were more sensitive.

It also included attention to differentiation (and was one of the dimensions of the ISTOF student questionnaire).

The mediation seemed to be stronger for girls compared to boys.

An overview of this research with regard to Flanders (Belgium) and the Netherlands of the last three decades can be found in Opdenakker ( 2020 ).

Depending on the publication (e.g., van de Grift, 2007 ; Maulana et al., 2021 ) also the wordings ‘categories’, ‘dimensions’ or ‘scales’ are used. Opportunities to learn, monitoring pupils’ results and special measures for struggling learners, were not addressed in the ICALT because they were not observable in (almost) each lesson and/or most important decisions were taken at school level.

In the original version, this belonged to the domain ‘clear instruction’ (see e.g., van de Grift, 2007 ), which is renamed as ‘clarity of instruction’ in more recent publications (see e.g., van de Grift et al., 2014 ; Maulana et al., 2021 ).

In their article as well as in the article of Muijs et al. ( 2018 ), a detailed discussion can be found on how the ISTOF instrument was developed.

Aelterman, N., Vansteenkiste, M., Haerens, L., Soenens, B., Fontaine, J. R. J., & Reeve, J. (2019). Toward an integrative and fine-grained insight in motivating and demotivating teaching styles: The merits of a circumplex approach. Educational Psychology, 111 (3), 497–521. https://doi.org/10.1037/edu0000293

Article   Google Scholar  

Aldridge, J. M., & Fraser, B. J. (2000). A cross-cultural study of classroom learning environments in Australia and Taiwan. Learning Environments Research, 3 , 101–134. https://doi.org/10.1023/A:1026599727439

Allen, J. P., Pianta, R. C., Gregory, A., Mikami, A. Y., & Lun, J. (2011). An interaction-based approach to enhancing secondary school instruction and student achievement. Science, 333 (6045), 1034–1037. https://doi.org/10.1126/science.1207998

Allen, J., Gregory, A., Mikami, A., Lun, J., Hamre, B., & Pianta, R. (2013). Observations of effective teacher–Student interactions in secondary school classrooms: Predicting student achievement with the Classroom Assessment Scoring System–Secondary. School Psychology Review, 42 , 76–98. https://doi.org/10.1080/02796015.2013.12087492

Anderman, L. H., & Midgley, C. (1998). Motivation and middle school students. ERIC Digest , EDO-PS-98-5.

Google Scholar  

Archambault, I., Vandenbossche-Makombo, J., & Fraser, S. L. (2017). Students’ oppositional behaviors and engagement in school: The differential role of the student-teacher relationship. Journal of Child and Family Studies, 26 , 1702–1712. https://doi.org/10.1007/s10826-017-0691-y

Arens, A. K., Morin, A. J. S., & Watermann, R. (2015). Relations between classroom disciplinary problems and student motivation: Achievement as a potential mediator? Learning and Instruction, 39 , 184–193. https://doi.org/10.1016/j.learninstruc.2015.07.001

Assor, A., Kaplan, H., & Roth, G. (2002). Choice is good, but relevance is excellent: Autonomy-enhancing and suppressing teacher behaviours predicting students’ engagement in schoolwork. British Journal of Educational Psychology, 72 (2), 261–278. https://doi.org/10.1348/000709902158883

Assor, A., Kaplan, H., Kanat-Maymon, Y., & Roth, G. (2005). Directly controlling teacher behaviors as predictors of poor motivation and engagement in girls and boys: The role of anger and anxiety. Learning and Instruction, 15 , 397–413. https://doi.org/10.1016/j.learninstruc.2005.07.008

Assor, A., Kaplan, H., Feinberg, O., & Tal, K. (2009). Combining vision with voice: A learning and implementation structure promoting teachers’ internalization of practices based on self-determination theory. Theory and Research in Education, 7 (2), 234–243. https://doi.org/10.1177/1477878509104328

Back, L. T., Polk, E., Keys, C. B., & McMahon, S. D. (2016). Classroom management, school staff relations, school climate, and academic achievement: Testing a model with urban high schools. Learning Environment Research, 19 , 397–410. https://doi.org/10.1007/s10984-016-9213-x

Battistich, V., Solomon, D., Kim, D.-I., Watson, M., & Schaps, E. (1995). Schools as communities, poverty levels of student populations, and students’ attitudes, motives, and performance: A multilevel analysis. American Educational Research Journal, 32 (3), 627–658. https://doi.org/10.2307/1163326

Beaton, A. E., Mullis, I. V. S., Martin, M. O., Gonzalez, E. J., Kelly, D. L., & Smith, T. A. (1996). Mathematics achievement in the middle school years: IEA’s Third International Mathematics and Science Study (TIMSS) . Boston College.

Belmont, M., Skinner, E., Wellborn, J., & Connell, J. (1988). Teacher as social context: A measure of student perceptions of teacher provision of involvement, structure, and autonomy support (Tech. rep. no. 102). University of Rochester.

Belmont, M., Skinner, E., Wellborn, J., & Connell, J. (1992). Teacher as social context (TASC). Two measures of teacher provision of involvement, structure, and autonomy support (Technical Report) . University of Rochester.

Bieg, S., Backes, S., & Mittag, W. (2011). The role of intrinsic motivation for teaching, teachers’ care and autonomy support in students’ self-determined motivation. Journal for Educational Research Online, 3 (1), 122–140.

Black, A. E., & Deci, E. L. (2000). The effects of instructors’ autonomy support and students’ autonomous motivation on learning organic chemistry: A self-determination theory perspective. Science Education, 84 (6), 740–756. https://doi.org/10.1002/1098-237X(200011)

Brekelmans, M., Mainhard, T., den Brok, P., & Wubbels, T. (2011). Teacher control and affiliation: Do students and teachers agree? Journal of Classroom Interaction, 46 (1), 17–26.

Campbell, J., Kyriakides, L., Muijs, D., & Robinson, W. (2004). Assessing teacher effectiveness: Developing a differentiated model . RoutledgeFalmer. https://doi.org/10.4324/9780203403709

Book   Google Scholar  

Cheon, S. H., Reeve, J., & Vansteenkiste, M. (2020). When teachers learn how to provide classroom structure in an autonomy-supportive way: Benefits to teachers and their students. Teaching and Teacher Education, 90 , 103004. https://doi.org/10.1016/j.tate.2019.103004

Chionh, Y. H., & Fraser, B. J. (2009). Classroom environment, achievement, attitudes and self-esteem in geography and mathematics in Singapore. International Research in Geographical and Environmental Education, 18 (1), 29–44. https://doi.org/10.1080/10382040802591530

Chirkov, V. I., & Ryan, R. M. (2001). Parent and teacher autonomy-support in Russian and U.S. adolescents: Common effects on Well-being and academic motivation. Journal of Cross-Cultural Psychology, 32 (5), 618–635. https://doi.org/10.1177/0022022101032005006

Cipriano, C., Barnes, T. N., Pieloch, K. A., Rivers, S. E., & Brackett, M. (2019). A multilevel approach to understanding student and teacher perceptions of classroom support during early adolescence. Learning Environments Research, 22 , 209–228. https://doi.org/10.1007/s10984-018-9274-0

Clausen, M. (2002). Unterrichtsqualität: Eine Frage der Perspektive ? [Instructional quality: A question of perspectives?] Waxmann.

Connell, J. P., & Wellborn, J. G. (1991). Competence, autonomy, and relatedness: A motivational analysis of self-system processes. In M. R. Gunnar & L. A. Sroufe (Eds.), The Minnesota symposia on child psychology, vol. 23. Self processes and development (pp. 43–77). Lawrence Erlbaum Associates.

Creemers, B. (1994). The effective classroom . Cassell.

Creemers, B. P. M., & Kyriakides, L. (2008). The dynamics of educational effectiveness: A contribution to policy, practice and theory in contemporary schools . Routledge. https://doi.org/10.4324/9780203939185

Crosnoe, R., & Johnson, M. K. (2011). Research on adolescence in the twenty-first century. Annual Review of Sociology, 37 , 439–460. https://doi.org/10.1146/annurev-soc-081309-150008

de Boer, G., Opdenakker, M.-C., & Minnaert, A. (2016, August). Learning environments triggering gifted students’ motivation: A study on students’ perception of teacher behavior, the relation with their teacher, and their motivation . Paper presented at the international conference on motivation (ICM).

De Jong, R., & Westerhof, K. J. (2001). The quality of student ratings of teacher behaviour. Learning Environments Research, 4 , 51–85. https://doi.org/10.1023/A:1011402608575

Deci, E.L., Speigel, N.H., Ryan, R.M., Koestner, R., & Kauffman, M. (1982). The effects of performance standards on teaching styles: The behavior of controlling teachers. Journal of Educational Psychology , 74, 852–859. https://doi.org/0022-0663/82/7406-Q8B2J00.75.

den Brok, P., Brekelmans, M., & Wubbels, T. (2004). Interpersonal teacher behaviour and student outcomes. School Effectiveness and School Improvement, 15 , 407–442. https://doi.org/10.1080/09243450512331383262

den Brok, P., Levy, J., Brekelmans, M., & Wubbels, T. (2005). The effect of teacher interpersonal behaviour on student subject-specific motivation. Journal of Classroom Interaction, 40 , 20–33.

den Brok, P., Bergen, T., & Brekelmans, M. (2006). Convergence and divergence between students’ and teachers’ perceptions of instructional behaviour in Dutch secondary education. In D. Fisher & M. S. Khine (Eds.), Contemporary approaches to research on learning environments: World views (pp. 125–160). World Scientific.

Chapter   Google Scholar  

den Brok, P., van Tartwijk, J., Wubbels, T., & Veldman, I. (2010). The differential effect of the teacher-student interpersonal relationship on student outcomes for students with different ethnic backgrounds. British Journal of Educational Psychology, 80 , 199–221. https://doi.org/10.1348/000709909X465632

den Brok, P., Mainhard, T., & Wubbels, T. (2019). Developments in quantitative methods and analyses for studying learning environments. In D. Zandvlied & B. J. Fraser (Eds.), Thirty years of learning environments; looking back and looking forward (pp. 41–58). Brill/Sense. https://doi.org/10.1163/9789004387720_003

Devine, D., Fahi, D., & McGillicuddy, D. (2013). What is ‘good’ teaching? Teacher beliefs and practices about their teaching. Irish Educational Studies, 32 (1), 83–108. https://doi.org/10.1080/03323315.2013.773228

Dorman, J. P. (2003). Cross-national validation of the what is happening in this class? (WIHIC) questionnaire using confirmatory factor analysis. Learning Environments Research, 6 , 231–245. https://doi.org/10.1023/A:1027355123577

Doyle, W. (1977). Paradigms for research on teacher effectiveness. Review of Research in Education, 5 (1), 163–198. https://doi.org/10.3102/0091732X005001163

Dumay, X., & Dupriez, V. (2007). Accounting for class effect using the TIMSS 2003 eighth-grade database: Net effect of group composition, net effect of class process, and joint effect. School Effectiveness and School Improvement, 18 , 383–408. https://doi.org/10.1080/09243450601146371

Emmer, E. T., & Strough, L. (2001). Classroom management: A critical part of educational psychology, with implications for teacher education. Educational Psychologist, 36 (2), 103–112. https://doi.org/10.1207/S15326985EP3602_5

Escriva-Boulley, G., Haerens, L., Tessier, D., & Sarrazin, P. (2021). Antecedents of primary school teachers’ need-supportive and need-thwarting styles in physical education. European Physical Education Review, 1–20 , 961–980. https://doi.org/10.1177/1356336X211004627

Fatou, N., & Kubiszewski, V. (2018). Are perceived school climate dimensions predictive of students’ engagement? Social Psychology of Education, 21 , 427–446. https://doi.org/10.1007/s11218-017-9422-x

Fauth, B., Decristan, J., Rieser, S., Klieme, E., & Büttner, G. (2014). Student ratings of teaching quality in primary school: Dimensions and prediction of student outcomes. Learning and Instruction, 29 , 1–9. https://doi.org/10.1016/j.learninstruc.2013.07.001

Fraser, B. J. (2012). Classroom environment . Routledge.

Fraser, B. J. (2019). Milestones in the evolution of the learning environments field over the past three decades. In D. Zandvliet & B. J. Fraser (Eds.), Thirty years of learning environments; looking back and looking forward (pp. 1–19). Brill/Sense.

Fraser, B. J., McRobbie, C. J., & Fisher, D. L. (1996, April). Development, validation and use of personal and class forms of a new classroom environment instrument . Paper presented at the annual meeting of the American Educational Research Association.

Fraser, B. J., McLure, F. I., & Koul, R. B. (2021). Assessing classroom emotional climate in stem classrooms: Developing and validating a questionnaire. Learning Environments Research, 24 , 1–21. https://doi.org/10.1007/s10984-020-09316-z

Fuller, F. F. (1969). Concerns of teachers: A developmental conceptualization. American Educational Research Journal, 6 , 207–226. https://doi.org/10.3102/00028312006002207

Furrer, C., & Skinner, E. (2003). Sense of relatedness as a factor in children’s academic engagement and performance. Journal of Educational Psychology, 95 , 148–162. https://doi.org/10.1037/0022-0663.95.1.148

Hafen, C. A., Hamre, B., Allen, J. P., Bell, C., Gitomer, D., & Pianta, R. C. (2015). Teaching through interactions in secondary school classrooms: Revisiting the factor structure and practical application of the classroom assessment scoring system-secondary. Journal of Early Adolescence, 35 , 651–680. https://doi.org/10.1177/0272431614537117

Hagger, M. S., Sultan, S., Hardcastle, S. J., & Chatzisarantis, N. L. D. (2015). Perceived autonomy support and autonomous motivation toward mathematics activities in educational and out-of-school contexts is related to mathematics homework behavior and attainment. Contemporary Educational Psychology, 41 , 111–123. https://doi.org/10.1016/j.cedpsych.2014.12.002

Hamre, B. K., & Pianta, R. C. (2001). Early teacher–child relationships and the trajectory of children’s school outcomes through eighth grade. Child Development, 72 , 625–638. https://doi.org/10.1111/1467-8624.00301

Hamre, B., & Pianta, R. (2005). Can instructional and emotional support in the first-grade classroom make a difference for children at risk of school failure? Child Development, 76 , 949–967. https://doi.org/10.1111/j.1467-8624.2005.00889.x

Hamre, B. K., & Pianta, R. C. (2010). Classroom environments and developmental processes. In J. L. Meece & J. S. Eccles (Eds.), Handbook of research on schools, schooling and human development (pp. 25–41). Routledge.

Hamre, B. K., Pianta, R. C., Downer, J. T., DeCoster, J., Mashburn, A. J., Jones, S. M., et al. (2013). Teaching through interactions: Testing a developmental framework of teacher effectiveness in over 4,000 classrooms. The Elementary School Journal, 113 (4), 461–487. https://doi.org/10.1086/669616

Hattie, J. (2009). Visible learning: A synthesis of over 800 meta-analyses relating to achievement . Routledge.

Hospel, V., & Galand, B. (2016). Are both classroom autonomy support and structure equally important for students’ engagement? A multilevel analysis. Learning and Instruction, 41 , 1–10. https://doi.org/10.1016/j.learninstruc.2015.09.001

Hughes, K., & Coplan, R. J. (2018). Why classroom climate matters for children high in anxious solitude: A study of differential susceptibility. School Psychology Quarterly, 33 , 94–102. https://doi.org/10.1037/spq0000201

Illeris, K. (2009). Contemporary theories of learning: Learning theorists ... In their own words . Routledge.

Jang, H., Reeve, J., & Deci, E. L. (2010). Engaging students in learning activities: It is not autonomy support or structure but autonomy support and structure. Journal of Educational Psychology, 102 , 588–600. https://doi.org/10.1037/a0019682

Jang, H., Kim, E. J., & Reeve, J. (2016). Why students become more engaged or more disengaged during the semester: A self-determination theory dual-process model. Learning and Instruction, 43 , 27–38. https://doi.org/10.1016/J.LEARNINSTRUC.2016.01.002

Johnson, B., & Stevens, J. J. (2006). Student achievement and elementary teachers’ perceptions of school climate. Learning Environments Research, 9 (2), 111–122. https://doi.org/10.1007/s10984-006-9007-7

Jungert, T., & Koestner, R. (2015). Science adjustment, parental and teacher autonomy support and the cognitive orientation of science students. Educational Psychology, 35 (3), 361–376. https://doi.org/10.1080/01443410.2013.828826

Kiemer, K., Gröschner, A., Kunter, M., & Seidel, T. (2018). Instructional and motivational classroom discourse and their relationship with teacher autonomy and competence support – findings from teacher professional development. European Journal of Psychology of Education, 33 (2), 377–402. https://doi.org/10.1007/s10212-016-0324-7

King, R. B. (2015). Sense of relatedness boosts engagement, achievement, and Well-being: A latent growth model study. Contemporary Educational Psychology, 41 , 26–38. https://doi.org/10.1016/j.cedpsych.2015.04.002

Klassen, R. M., Perry, N. E., & Frenzel, A. C. (2012). Teachers’ relatedness with students: An underemphasized component of teachers’ basic psychological needs. Journal of Educational Psychology, 104 (1), 150–165. https://doi.org/10.1037/a0026253

Klem, A. M., & Connell, J. P. (2004). Relationships matter: Linking teacher support to student engagement and achievement. Journal of School Health, 74 (7), 262–273. https://doi.org/10.1111/j.1746-1561.2004.tb08283.x

Klieme, E., Pauli, C., & Reusser, K. (2009). The Pythagoras study: Investigating effects of teaching and learning in Swiss and German mathematics classrooms. In T. Janik & T. Seidel (Eds.), The power of video studies in investigating teaching and learning in the classroom (pp. 137–160). Waxmann.

Konold, T., Cornell, D., Shukla, K., & Huang, F. (2017). Racial/ethnic differences in perceptions of school climate and its association with student engagement and peer aggression. Journal of Youth and Adolescence, 46 , 1289–1303. https://doi.org/10.1007/s10964-016-0576-1

Korpershoek, H., Harms, T., de Boer, H., van Kuijk, M., & Doolaard, S. (2016). A meta-analysis of the effects of classroom management strategies and classroom management programs on students’ academic, behavioral, emotional, and motivational outcomes. Review of Educational Research, 86 (3), 643–680. https://doi.org/10.3102/0034654315626799

Kulik, J. A. (2001). Student ratings: Validity, utility, and controversy. New Directions for Institutional Research, 109 , 9–25. https://doi.org/10.1002/ir.1

Kunter, M., & Baumert, J. (2006). Who is the expert? Construct and criteria validity of student and teacher ratings of instruction. Learning Environments Research, 9 , 231–251. https://doi.org/10.1007/s10984-006-9015-7

Kunter, M., Baumert, J., & Köller, O. (2007). Effective classroom management and the development of subject-related interest. Learning and Instruction, 17 , 494–509. https://doi.org/10.1016/j.learninstruc.2007.09.002

Kyriakides, L., Creemers, B., & Panayiotou, A. (2020). Developing and testing theories of educational effectiveness addressing the dynamic nature of education. In J. Hall, A. Lindorff, & P. Sammons (Eds.), International perspectives in educational effectiveness research (pp. 33–69). Springer. https://doi.org/10.1007/978-3-030-44810-3_3

Lam, S.-F., Jimerson, S., Kikas, E., Cefai, C., Veiga, F. H., Nelson, B., et al. (2012). Do girls and boys perceive themselves as equally engaged in school? The results of an international study from 12 countries. Journal of School Psychology, 50 (1), 77–94. https://doi.org/10.1016/j.jsp.2011.07.004

Lazarides, R., & Rubach, C. (2017). Instructional characteristics in mathematics classrooms: Relationships to achievement goal orientation and student engagement. Mathematics Education Research Journal, 29 , 201–217. https://doi.org/10.1007/s13394-017-0196-4

Leon, J., Medina-Garrido, E., & Núñez, J. L. (2017). Teaching quality in math class: The development of a scale and the analysis of its relationship with engagement and achievement. Frontiers in Psychology, 8 (895), 1–14. https://doi.org/10.3389/fpsyg.2017.00895

Leyva, D., Weiland, C., Barata, M., Yoshikawa, H., Snow, C., & Treviño, E. (2015). Teacher–child interactions in Chile and their associations with prekindergarten outcomes. Child Development, 86 , 781–799. https://doi.org/10.1111/cdev.12342

Lietaert, S., Roorda, D., Laevers, F., Verschueren, K., & De Fraine, B. (2015). The gender gap in student engagement: The role of teachers’ autonomy support, structure, and involvement. British Journal of Educational Psychology, 85 , 498–518. https://doi.org/10.1111/bjep.12095

Lindorff, A., Sammons, P., & Hall, J. (2020). International perspectives in educational effectiveness research: A historical overview. In J. Hall, A. Lindorff, & P. Sammons (Eds.), International perspectives in educational effectiveness research (pp. 9–31). Springer. https://doi.org/10.1007/978-3-030-44810-3_2

Lipowsky, F., Rakoczy, K., Pauli, C., Drollinger-Vetter, B., Klieme, E., & Reusser, K. (2009). Quality of geometry instruction and its short-term impact on students’ understanding of the Pythagorean theorem. Learning and Instruction, 19 , 527–537. https://doi.org/10.1016/j.learninstruc.2008.11.001

Liu, J., Bartholomew, K., & Chung, P. K. (2017). Perceptions of teachers’ interpersonal styles and Well-being and ill-being in secondary school physical education students: The role of need satisfaction and need frustration. School Mental Health, 9 (4), 360–371. https://doi.org/10.1007/s12310-017-9223-6

Mainhard, M. T., Brekelmans, M., den Brok, P., & Wubbels, T. (2011). The development of the classroom social climate during the first months of the school year. Contemporary Educational Psychology, 36 , 190–200. https://doi.org/10.1016/j.cedpsych.2010.06.002

Malmberg, L.-E., Hagger, H., Burn, K., Mutton, T., & Colls, H. (2010). Observed classroom quality during teacher education and two years of professional practice. Journal of Educational Psychology, 102 , 916–932. https://doi.org/10.1037/a0020920

Marsh, H. W., & Roche, L. A. (1997). Making students’ evaluations of teaching effectiveness effective. American Psychologist, 52 , 1187–1197. https://doi.org/10.1037//0003-066x.52.11.1187

Mashburn, A. J., Pianta, R. C., Hamre, B. K., Downer, J. T., Barbarin, O. A., Bryant, D., et al. (2008). Measures of classroom quality in prekindergarten and children’s development of academic, language, and social skills. Child Development, 79 , 732–749. https://doi.org/10.1111/j.1467-8624.2008.01154.x

Maulana, R., & Helms-Lorenz, M. (2016). Observations and student perceptions of the quality of preservice teachers’ teaching behaviour: Construct representation and predictive quality. Learning Environments Research, 19 , 335–357. https://doi.org/10.1007/s10984-016-9215-8

Maulana, R., & Opdenakker, M.-C. (2014). Do teacher-student interpersonal relationships deteriorate over time? An investigation of within-year changes and links with autonomous motivation in Indonesia. In D. Zandvliet, P. den Brok, T. Mainhard, & J. van Tartwijk (Eds.), Interpersonal relationships in education: From theory to practice (pp. 133–158). Sense. https://doi.org/10.1007/978-94-6209-701-8_9

Maulana, R., Opdenakker, M.-C., den Brok, P., & Bosker, R. (2012). Teacher-student interpersonal relationships during the first year of secondary education: A multilevel growth curve analysis. In T. Wubbels, P. den Brok, J. van Tartwijk, & J. Levy (Eds.), Interpersonal relationships in education: An overview of contemporary research (pp. 207–224). Sense.

Maulana, R., Opdenakker, M.-C., Stroet, K., & Bosker, R. (2013). Changes in teachers’ involvement versus rejection and links with academic motivation during the first year of secondary education: A multilevel growth curve analysis. Journal of Youth and Adolescence, 42 , 1348–1371. https://doi.org/10.1007/s10964-013-9921-9

Maulana, R., Opdenakker, M.-C., & Bosker, R. (2014). Teacher-student interpersonal relationships do change and affect academic motivation: A multilevel growth curve modeling. British Journal of Educational Psychology, 84 , 459–482. https://doi.org/10.1111/bjep.12031

Maulana, R., Opdenakker, M.-C., & Bosker, R. (2016). Teachers’ instructional behaviors as important predictors of academic motivation: Changes and links across the school year. Learning and Individual Differences, 50 , 147–156. https://doi.org/10.1016/j.lindif.2016.07.019

Maulana, R., Helms-Lorenz, M., & van de Grift, W. (2017). Validating a model of effective teaching behaviour of pre-service teachers. Teachers and Teaching, 23 (4), 471–493. https://doi.org/10.1080/13540602.2016.1211102

Maulana, R., et al. (2021). Observed teaching behaviour in secondary education across six countries: Measurement invariance and indication of cross-national variations. School Effectiveness and School Improvement, 32 (1), 64–95. https://doi.org/10.1080/09243453.2020.1777170

McCaslin, M., & Good, T. L. (1992). Compliant cognition: The misalliance of management and instructional goals in current school reform. Educational Researcher, 21 (3), 4–17. https://doi.org/10.3102/0013189X021003004

McLean, L., & Connor, C. M. (2015). Depressive symptoms in third-grade teachers: Relations to classroom quality and student achievement. Child Development, 86 , 945–954. https://doi.org/10.1111/cdev.12344

Moos, R. H., & Trickett, E. J. (1974). Classroom climate scale manual . Consulting Psychologists Press.

Muijs, D., & Reynolds, D. (2011). Effective teaching. Evidence and practice . Sage.

Muijs, R. D., Kyriakides, L., van der Werf, G., Creemers, B. P. M., Timperley, H., & Earl, L. (2014). State of the art – Teacher effectiveness and professional learning. School Effectiveness and School Improvement, 25 (2), 231–256. https://doi.org/10.1080/09243453.2014.885451

Muijs, D., Reynolds, D., Sammons, P., Kyriakides, L., Creemers, B. P. M., & Teddlie, C. (2018). Assessing individual lessons using a generic teacher observation instrument: How useful is the international system for teacher observation and feedback (ISTOF)? ZDM – Mathematics Education, 50 , 395–406. https://doi.org/10.1007/s11858-018-0921-9

Nie, Y., & Lau, S. (2009). Complementary roles of care and behavioral control in classroom management: The self-determination theory perspective. Contemporary Educational Psychology, 34 , 185–194. https://doi.org/10.1016/j.cedpsych.2009.03.001

Núñez, J. L., & León, J. (2019). Determinants of classroom engagement: A prospective test based on self-determination theory. Teachers and Teaching, 25 (2), 147–159. https://doi.org/10.1080/13540602.2018.1542297

Opdenakker, M.-C. (2004). Leerling in wonderland? Een onderzoek naar het effect van leerling-, lesgroep-, leerkracht- en schoolkenmerken op prestaties voor wiskunde in het secundair onderwijs [Student in wonderland? A study on the effect of student, class, teacher, and school characteristics on mathematics achievement in secondary education]. Acco.

Opdenakker, M.-C. (2013, April) . Effects on students’ motivation: Does the pedagogical approach of traditional, social-constructivist and combined-approach schools matter? Paper presented at the annual meeting of the AERA.

Opdenakker, M. C. J. L. (2014). Leerkracht-leerlingrelaties vanuit een motivationeel perspectief: het belang van betrokken en ondersteunende docenten [Teacher-student relations from a motivational perspective: The importance of involved and supportive teachers]. Pedagogische Studien, 91 , 332–351.

Opdenakker, M.-C. (2019, August). Quality of learning environments over time: Relationships with teacher characteristics. In J. Stang (Chair), Importance of teacher characteristics for instructional quality. Symposium conducted at the EARLI-conference.

Opdenakker, M.-C. (2020). Three decades of educational effectiveness research in Belgium and The Netherlands: Key studies, main research topics and findings. In J. Hall, A. Lindorff, & P. Sammons (Eds.), International perspectives in educational effectiveness research (pp. 231–286). Springer. https://doi.org/10.1007/978-3-030-44810-3_10

Opdenakker, M.-C. (2021). Need-supportive and need-thwarting teacher behavior: Their importance to boys’ and girls’ academic engagement and procrastination behavior. Frontiers in Psychology, 12 (628064), 1–17. https://doi.org/10.3389/fpsyg.2021.628064

Opdenakker, M-C., & Maulana, R. (2010, April). Teacher-student relationships and academic engagement: How do they develop and link? Paper presented at the international conference on interpersonal relationships in education (ICIRE).

Opdenakker, M.-C., & Minnaert, A. (2011). Relationship between learning environment characteristics and academic engagement. Psychological Reports, 109 , 259–284. https://doi.org/10.2466/09.10.11.PR0.109.4.259-284

Opdenakker, M.-C., & Minnaert, A. (2014). Learning environment experiences in primary education: Their importance to academic engagement. In D. Zandvliet, P. den Brok, T. Mainhard, & J. van Tartwijk (Eds.), Interpersonal relationships in education: From theory to practice (pp. 183–194). Sense. https://doi.org/10.1007/978-94-6209-701-8_11

Opdenakker, M.-C., & Van Damme, J. (2006). Teacher characteristics and teaching styles as effectiveness enhancing factors of classroom practice. Teaching and Teacher Education, 22 , 1–21. https://doi.org/10.1016/j.tate.2005.07.008

Opdenakker, M.-C., & Van Damme, J. (2007). Do school context, student composition and school leadership affect school practice and outcomes in secondary education? British Educational Research Journal, 33 , 179–206. https://doi.org/10.1080/01411920701208233

Opdenakker, M.-C., Van Damme, J., & Minnaert, A. (2005). Are there equal opportunities in our classes and schools? An investigation into the relationship between class composition, indicators of the learning environment and the class climate, effort, and achievement of classes . University of Leuven.

Opdenakker, M.-C., Maulana, R., & den Brok, P. (2012). Teacher-student interpersonal relationships and academic motivation within one school year: Developmental changes and linkage. School Effectiveness and School Improvement, 23 , 95–119. https://doi.org/10.1080/09243453.2011.619198

Pakarinen, E., Lerkkanen, M., Poikkeus, A., Kiuru, N., Siekkinen, M., Rasku-Puttonen, H., & Nurmi, J. (2010). A validation of the classroom assessment scoring system in Finnish kindergartens. Early Education and Development, 21 , 95–124. https://doi.org/10.1080/10409280902858764

Pelletier, L. G., Séguin-Lévesque, C., & Legault, L. (2002). Pressure from above and pressure from below as determinants of teachers’ motivation and teaching behaviors. Journal of Educational Psychology, 94 (1), 186–196. https://doi.org/10.1037/0022-0663.94.1.18

Pianta, R., & Hamre, B. K. (2009). Conceptualization, measurement, and improvement of classroom processes: Standardized observation can leverage capacity. Educational Researcher, 38 (2), 109–119. https://doi.org/10.3102/0013189X09332374

Pianta, R. C., Hamre, B. K., & Mintz, S. L. (2012). The CLASS-Secondary manual . University of Virginia.

Pöysä, S., Vasalampi, K., Muotka, J., Lerkkanen, M.-K., Poikkeus, A.-M., & Nurmi, J.-E. (2019). Teacher–student interaction and lower secondary school students’ situational engagement. British Journal of Educational Psychology, 89 , 374–392. https://doi.org/10.1111/bjep.12244

Reeve, J. M. (2009). Why teachers adopt a controlling motivating style toward students and how they can become more autonomy supportive. Educational Psychologist, 44 (3), 159–175. https://doi.org/10.1080/00461520903028990

Reeve, J. M., & Jang, H. (2006). What teachers say and do to support students’ autonomy during a learning activity. Journal of Educational Psychology, 98 (1), 209–218. https://doi.org/10.1037/0022-0663.98.1.129

Reeve, J., & Tseng, C.-M. (2011). Cortisol reactivity to a teacher’s motivating style: The biology of being controlled versus supporting autonomy. Motivation and Emotion, 35 (1), 63–74. https://doi.org/10.1007/s11031-011-9204-2

Reeve, J., Jang, H., Carrell, D., Jeon, S., & Barch, J. (2004). Enhancing students’ engagement by increasing autonomy support. Motivation & Emotion, 28 , 147–169. https://doi.org/10.1023/b:moem.0000032312.95499.6f

Reeve, J., Vansteenkiste, M., Assor, A., Ahmad, I., Cheon, S. H., Jang, H., et al. (2014). The beliefs that underlie autonomy-supportive and controlling teaching: A multinational investigation. Motivation and Emotion, 38 , 93–110. https://doi.org/10.1007/s11031-013-9367-0

Reyes, M. R., Brackett, M. A., Rivers, S. E., White, M., & Salovey, P. (2012). Classroom emotional climate, student engagement, and academic achievement. Journal of Educational Psychology, 104 , 700–712. https://doi.org/10.1037/a0027268

Reynolds, D. (2000). School effectiveness: The international dimension. In C. Teddlie & D. Reynolds (Eds.), International handbook of school effectiveness research (pp. 232–256). Falmer.

Rjosk, C., Richter, D., Hochweber, J., Lüdtke, O., Klieme, E., & Stanat, P. (2014). Socioeconomic and language minority classroom composition and individual reading achievement: The mediating role of instructional quality. Learning and Instruction, 32 , 63–72. https://doi.org/10.1016/j.learninstruc.2014.01.007

Roorda, D., Koomen, H., Spilt, J., & Oort, F. (2011). The influence of affective teacher–student relationships on students’ school-engagement and achievement: A meta-analytic approach. Review of Educational Research, 81 , 493–529. https://doi.org/10.3102/0034654311421793

Roth, G., Assor, A., Kanat-Maymon, Y., & Kaplan, H. (2007). Autonomous motivation for teaching: How self-determined teaching may lead to self-determined learning. Journal of Educational Psychology, 99 , 761–774. https://doi.org/10.1037/0022-0663.99.4.761

Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and Well-being. American Psychologist, 55 , 68–78. https://doi.org/10.1037/0003-066x.55.1.68

Ryan, R. M., & Deci, E. L. (2002). An overview of self-determination theory: An organismic-dialectical perspective. In E. L. Deci & R. M. Ryan (Eds.), Handbook of self-determination research (pp. 3–33). University Press.

Ryan, R. M., & Deci, E. L. (2017). Self-determination theory: Basic psychological needs in motivation, development, and wellness . The Guilford Press. https://doi.org/10.1521/978.14625/28806

Ryan, R. M., & Deci, E. L. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. Contemporary Educational Psychology, 61 , 101860. https://doi.org/10.1016/j.cedpsych.2020.101860

Seidel, T., & Shavelson, R. J. (2007). Teaching effectiveness research in the past decade: The role of theory and research design in disentangling meta-analysis results. Review of Educational Research, 77 , 454–499. https://doi.org/10.3102/0034654307310317

Sierens, E., Vansteenkiste, M., Goossens, L., Soenens, B., & Dochy, F. (2009). The synergistic relationship of perceived autonomy support and structure in the prediction of self-regulated learning. British Journal of Educational Psychology, 79 (1), 57–68. https://doi.org/10.1348/000709908X304398

Skinner, E., & Belmont, M. J. (1993). Motivation in the classroom: Reciprocal effect of teacher behavior and student engagement across the school year. Journal of Educational Psychology, 85 , 571–581. https://doi.org/10.1037/0022-0663.85.4.571

Skinner, E. A., Furrer, C., Marchand, G., & Kindermann, T. (2008). Engagement and disaffection in the classroom: Part of a larger motivational dynamic? Journal of Educational Psychology, 100 , 765–781. https://doi.org/10.1037/a0012840

Slavin, R. E. (2021). Educational psychology: Theory and practice (13th ed.). Pearson.

Soenens, B., Sierens, E., Vansteenkiste, M., Goossens, L., & Dochy, F. (2012). Psychologically controlling teaching: Examining outcomes, antecedents, and mediators. Journal of Educational Psychology, 104 , 108–120. https://doi.org/10.1037/a0025742

Stefanou, C. R., Perencevich, K. C., DiCintio, M., & Turner, J. C. (2004). Supporting autonomy in the classroom: Ways teachers encourage student decision making and ownership. Educational Psychologist, 39 (2), 97–110. https://doi.org/10.1207/s15326985ep3902_2

Stipek, D. J. (1988). Motivation to learn . Prentice Hall.

Streb, J., Keis, O., Lau, K., Hille, L., Spitzer, M., & Sosic-Vasic, Z. (2015). Emotional engagement in kindergarten and school children: A self- determination theory perspective. Trends in Neuroscience and Education, 4 (4), 102–107. https://doi.org/10.1016/j.tine.2015.11.001

Stroet, K., Opdenakker, M.-C., & Minnaert, A. (2013). Effects of need supportive teaching on early adolescents’ motivation and engagement: A review of the literature. Educational Research Review, 9 , 65–87. https://doi.org/10.1016/j.edurev.2012.11.003

Stroet, K., Opdenakker, M.-C., & Minnaert, A. (2015). What motivates early adolescents for school? A longitudinal analysis of associations between observed teaching and motivation. Contemporary Educational Psychology, 42 , 129–140. https://doi.org/10.1016/j.cedpsych.2015.06.002

Su, Y.-L., & Reeve, J. (2011). A meta-analysis of the effectiveness of intervention programs designed to support autonomy. Educational Psychology Review, 23 (1), 159–188. https://doi.org/10.1007/s10648-010-9142-7

Sykes, G., & Wilson, S. (2015). How teachers teach: Mapping the terrain of practice . Educational Testing Service.

Tas, Y. (2016). The contribution of perceived classroom learning environment and motivation to student engagement in science. European Journal of Psychology of Education, 31 , 557–577. https://doi.org/10.1007/s10212-016-0303-z

Tas, T., Houtveen, T., van de Grift, W., & Willemsen, M. (2018). Learning to teach: Effects of classroom observation, assignment of appropriate lesson preparation templates and stage focused feedback. Studies in Educational Evaluation, 58 , 8–16. https://doi.org/10.1016/j.stueduc.2018.05.005

Teddlie, C., Creemers, B., Kyriakides, L., Muijs, D., & Yu, F. (2006). The international system for teacher observation and feedback: Evolution of an international study of teacher effectiveness constructs. Educational Research and Evaluation, 22 , 561–582. https://doi.org/10.1080/13803610600874067

Telli, S., Cakiroglu, J., & den Brok, P. (2006). Turkish secondary education students’ perceptions of their classroom learning environment and their attitude towards biology. In D. L. Fisher & M. S. Khine (Eds.), Contemporary approaches to research on learning environments: World views (pp. 517–542). World Scientific.

Tsai, Y.-M., Kunter, M., Lüdtke, O., Trautwein, U., & Ryan, R. M. (2008). What makes lessons interesting? The role of situational and individual factors in three school subjects. Journal of Educational Psychology, 100 (2), 460–472. https://doi.org/10.1037/0022-0663.100.2.460

Tucker, C. M., Zayco, R. A., Herman, K. C., Reinke, W. M., Trujillo, M., Carraway, K., et al. (2002). Teacher and child variables as predictors of academic engagement among low-income African American children. Psychology in the Schools, 39 , 477–488. https://doi.org/10.1002/pits.10038

Van Damme, J., Opdenakker, M.-C., & Van den Broeck, A. (2004, May). Do classes and schools have an effect on attitudes towards mathematics? Paper presented at the first IEA international research conference.

van de Grift, W. (2007). Quality of teaching in four European countries: A review of the literature and application of an assessment instrument. Educational Research, 49 (2), 127–152. https://doi.org/10.1080/00131880701369651

van de Grift, W. J. C. M. (2014). Measuring teaching quality in several European countries. School Effectiveness and School Improvement, 25 (3), 295–311. https://doi.org/10.1080/09243453.2013.794845

van de Grift, W., van der Wal, M., & Torenbeek, M. (2011). Ontwikkeling in de pedagogische didactische vaardigheid van leraren in het basisonderwijs [Development in teaching skills]. Pedagogische Studiën, 88 , 416–432.

van de Grift, W., Helms-Lorenz, M., & Maulana, R. (2014). Teaching skills of student teachers: Calibration of an evaluation instrument and its value in predicting student academic engagement. Studies in Educational Evaluation, 43 , 150–159. https://doi.org/10.1016/j.stueduc.2014.09.003

van de Grift, W. J. C. M., Chun, S., Maulana, R., Lee, O., & Helms-Lorenz, M. (2017). Measuring teaching quality and student engagement in South Korea and The Netherlands. School Effectiveness and School Improvement, 28 (3), 337–349. https://doi.org/10.1080/09243453.2016.1263215

van der Lans, R. M., van de Grift, W. J. C. M., & van Veen, K. (2018). Developing an instrument for teacher feedback: Using the Rasch model to explore teachers’ development of effective teaching strategies and behaviors. The Journal of Experimental Education, 86 (2), 247–264. https://doi.org/10.1080/00220973.2016.1268086

Van Landeghem, G., Van Damme, J., Opdenakker, M.-C., De Fraine, B., & Onghena, P. (2002). The effect of schools and classes on noncognitive outcomes. School Effectiveness and School Improvement, 13 , 429–451. https://doi.org/10.1076/sesi.13.4.429.10284

Van Petegem, K., Creemers, B. P. M., Rosseel, Y., & Aelterman, A. (2005). Relationships between teacher characteristics, interpersonal teacher behaviour and teacher wellbeing. Journal of Classroom Interaction, 40 (2), 34–43.

Vandenkerckhove, B., Soenens, B., Van der Kaap-Deeder, J., Brenning, K., Luyten, P., & Vansteenkiste, M. (2019). The role of weekly need-based experiences and self-criticism in predicting weekly academic (mal)adjustment. Learning and Individual Differences, 69 , 69–83. https://doi.org/10.1016/j.lindif.2018.11.009

Vansteenkiste, M., Lens, W., & Deci, E. L. (2006). Intrinsic versus extrinsic goal contents in self-determination theory: Another look at the quality of academic motivation. Educational Psychologist, 41 (1), 19–31. https://doi.org/10.1207/s15326985ep4101_4

Vansteenkiste, M., Sierens, E., Goossens, L., Soenens, B., Dochy, F., Mouratidis, A., et al. (2012). Identifying configurations of perceived teacher autonomy support and structure: Associations with self-regulated learning, motivation and problem behavior. Learning and Instruction, 22 (6), 431–439. https://doi.org/10.1016/j.learninstruc.2012.04.002

Vansteenkiste, M., Ryan, R. M., & Soenens, B. (2020). Psychological need theory: Advancements, critical themes, and future directions. Motivation and Emotion, 44 , 1–31. https://doi.org/10.1007/s11031-019-09818-1

Virtanen, T. E., Lerkkanen, M.-K., Poikkeus, A.-M., & Kuorelahti, M. (2015). The relationship between classroom quality and students’ engagement in secondary school. Educational Psychology, 35 (8), 963–983. https://doi.org/10.1080/01443410.2013.822961

Virtanen, T. E., Pakarinen, E., Lerkkanen, M.-K., Poikkeus, A.-M., Siekkinen, M., & Nurmi, J.-E. (2018). A validation study of classroom assessment scoring system secondary in the Finnish school context. Journal of Early Adolescence, 38 (6), 849–880. https://doi.org/10.1177/0272431617699944

Wang, M. T., & Eccles, J. S. (2012). Social support matters: Longitudinal effects of social support on three dimensions of school engagement from middle to high school. Child Development, 83 (3), 877–895. https://doi.org/10.1111/j.1467-8624.2012.01745.x

Wentzel, K. R. (2002). Are effective teachers like good parents? Teaching styles and student adjustment in early adolescence. Child Development, 73 , 287–301. https://doi.org/10.1111/1467-8624.00406

Wentzel, K. R., Battle, A., Russell, S. L., & Looney, L. B. (2010). Social supports from teachers and peers as predictors of academic and social motivation. Contemporary Educational Psychology, 35 , 193–202. https://doi.org/10.1016/j.cedpsych.2010.03.002

Wolf, S. J., & Fraser, B. J. (2008). Learning environment, attitudes and achievement among middle-school science students using inquiry-based laboratory activities. Research in Science Education, 38 , 321–341. https://doi.org/10.1007/s11165-007-9052-y

Wubbels, T. (2019). My journey in the learning environments research community. Research on teacher-student interactions and relationships. In D. Zandvliet & B. J. Fraser (Eds.), Thirty years of learning environments; looking back and looking forward (pp. 20–40). Brill/Sense. https://doi.org/10.1163/9789004387720_002

Wubbels, T., & Brekelmans, M. (2005). Two decades of research on teacher–student relationships in class. International Journal of Educational Research, 43 , 6–24. https://doi.org/10.1016/j.ijer.2006.03.003

You, S., & Sharkey, J. (2009). Testing a developmental–ecological model of student engagement: A multilevel latent growth curve analysis. Educational Psychology, 29 (6), 659–684. https://doi.org/10.1080/01443410903206815

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1.1 Appendix Instruments Tapping Teacher Behaviour

1.1.1 classroom assessment scoring system (class).

Observation instrument based on the Teaching Trough Interactions Framework (Hafen et al., 2015 ; Hamre et al., 2013 ) and originally validated in the USA (variants for pre-K, primary and secondary education). Nowadays widely used and validated in a diversity of cultural contexts outside the USA (except for the latest version for secondary education) such as South America (Leyva et al., 2015 ) and Europe (Pakarinen et al., 2010 ).

Focus is on the patterns of interactions between teachers and students in class (because they are seen as central drivers for student learning). Support in and organization of classrooms is scored, but reference is made to teachers’ behaviour related to three domains.

Emotional support : the existence of warm and caring relationships between teacher and students and enjoyment and emotional connections between teacher and students, and among students (positive classroom climate); availability of a responsive teacher who has regard for student perspectives and is sensitive to and tries to meet students’ academic, affective, and social needs, who helps students resolve problems and who supports positive relations between students. A highly emotional supportive teacher has warm emotional connections with students and cares for them and consistently encourages students, provides comfort and reassurance and acts while considering their interest, motivation, and points of view.

Classroom organization : routines and procedures related to the organization of the classroom and the management of students’ behaviour, time, and attention during classroom time. High scores refer to the existence of consistent schedules, established routines, a well-organized classroom, appropriate guidance, and the creation of a learning environment that is characterized by stability, predictability, and supportiveness for learning.

Instructional support : teacher’s actions to support students’ learning and engagement and to maximize their learning opportunities. It entails the way in which the teacher implements the curriculum to promote cognitive development, makes concepts and skills relevant to students’ lives, encourages students to learn by asking questions and providing students with appropriate help and feedback that acknowledges their students’ effort. Teacher activities to help students understand the content and the stimulation of higher order thinking and the deleverage of opportunities to applicate knowledge in novel contexts are included as well.

1.1.2 What Is Happening In this Class (WIHIC)

Student perception questionnaire (Fraser et al., 1996 ) (56 items) with roots in learning environments research; combines salient scales from existing questionnaires (available in the nineties) with new dimensions which became relevant at the end of the nineties; measures seven dimensions including student involvement. Four dimensions refer to a caring learning environment namely student cohesiveness, teacher support, cooperation, and equity. The other dimensions are investigation and task orientation. The original questionnaire was constructed and validated in Australia, but the final version was validated in a variety of other countries (e.g., Greece, Australia; Turkey; Asian countries e.g., Taiwan, Brunei, Singapore, Korea, China; Jordan; South-Africa; Myanmar, India, UAE) and was used for international comparisons of science classes. In contrast to other instruments discussed in this review, not all the items (and dimensions) are formulated in terms of teacher behaviour.

Student cohesiveness : the extent to which students know each other and have positive and supportive relationships with each another.

Teacher support : taking a personal interest in students (and their feelings), befriending and helping them when they have trouble with schoolwork.

Cooperation : extent to which students cooperate with each other (e.g., on assignments) during class activities.

E quity : equal treatment by the teacher regarding encouragement, help, and opportunities to be included in discussions.

Task orientation : students’ attitudes towards the completion of planned activities and staying on the subject matter (including importance to get a certain amount of work done or to understand class work) and knowing the class goals.

Involvement : students’ attentive interest and participation in class (e.g., giving opinions during class discussions, asking questions)” and teachers’ activation of students’ involvement (by asking questions or asking to explain things).

Investigation : extent to which there is emphasis on skills of inquiry and if they are used in problem solving and investigation.

1.1.3 International Comparative Analysis of Learning and Teaching (ICALT) Instrument

Observation instrument originally developed in and for an international context to investigate the quality of teaching (van de Grift, 2007 ; Maulana et al., 2021 ) by members of the inspectorate of the Netherlands, Belgium (Flanders), England and Germany (Lower Saxony); based on mainly earlier reviews of educational/teacher effectiveness research and existing observation instruments teaching quality evaluation. Although originally developed for evaluation purposes and inspectors’ use during classroom visits in primary education, it is valid to use in secondary education (and in a variety of other countries, see Maulana et al., 2021 ; van de Grift, 2014 ; van de Grift et al., 2017 ) as well, as recent research reveals (e.g., Maulana et al., 2017 ).

The high-inference event sampling instrument consists of 32 high-inference observable teaching acts belonging to six domains of teaching behaviour and are accompanied with 120 low-inference observable teaching activities which are considered as examples of good practices associated with the corresponding high-inference teaching act. The original ICALT distinguishes between five observable domains Footnote 21 (with standards and corresponding indicators of good and effective teaching), namely efficient safe and stimulating learning climate, efficient classroom management, clear instruction, teaching learning strategies and adaptive teaching (adapting instruction and assignments) (van de Grift, 2007 ). In the adapted version (see e.g., van de Grift et al., 2014 ), a sixth dimension, namely activating teaching was added.

Safe and stimulating learning climate : a relaxed class atmosphere and mutual respect, and an orderly climate and intellectually stimulating environment in which there is an achievement-oriented attitude, and the self-confidence of students is encouraged by positive teacher expectations .

Efficient classroom management : starting and finishing the lesson on time, having efficient transitions between lessons, maintaining order and efficient handling of students’ misconduct, and no waste of time during the lesson.

Clear instruction/clarity of instruction : setting clear lesson objectives (and checking whether they are achieved/whether students understand the learning material), having a clear lesson structure and well-structured lessons, explaining subject matter, tools and tasks clearly, and following guidelines for direct or explicit instruction.

Teaching learning strategies : provision of temporary forms of support or scaffolds to students to help them bridging the gap between present and needed skills for achievement improvement; includes teaching cognitive and metacognitive strategies.

Adaptive teaching : adaptation of teaching to student differences (being attentive to diversity of student backgrounds and personalities) to better meet students’ learning needs and to optimize the learning potential of each student, in particular weal students. Adaptation can refer to additional instruction and learning time and can be realized by using the principles of pre-teaching and re-teaching.

Activating teaching Footnote 22 : asking questions aiming to stimulate active learning, intensive instructions and teacher behaviour aimed at the activation of students’ prior knowledge and making use of ‘advance organizers’ (Maulana et al., 2021 ).

1.1.4 The International System for Teacher Observation and Feedback (ISTOF) Instruments

Originally an observation instrument developed by an international team (and country teams) of 20 participating countries (with at least some representation of regions including North and South America, Europe, East Asia, South Asia, Southeast Asia, and Africa) during the International System for Teacher Observation and Feedback (ISTOF) project (Teddlie et al., 2006 ). Footnote 23 In the development phase, an iterative Delphi technique drawing on expert opinion and review was used to ensure cross-cultural relevance and validity (Muijs et al., 2018 ). Later, the ISTOF instrument has been validated and used in other country settings as well (see for a discussion, Lindorff et al., 2020 ; Muijs et al., 2018 ).

The ISTOF instrument draws on teacher/educational effectiveness research evidence and frameworks and expert opinion and is aimed at measuring teacher effectiveness in a reliable and valid way in an international context and providing opportunities for cross-country comparisons as well as possibilities for providing meaningful feedback to teachers (Teddlie et al., 2006 ; Kyriakides et al., 2020 ). The final observation instrument consists of seven (observable) components with for each component two to four indicators and for each indicator two items (45 high-inference items in total). The validity and reliability of the instrument were successfully established in a range of different contexts internationally (Muijs et al., 2018 ). However, in some studies the seven-components structure was not found indicating that the structure seems to be to some degree subject to variation across studies. and in some studies evidence was found for an overarching higher-order effectiveness factor as well (for a discussion, see Muijs et al., 2018 ).

The seven components are classroom climate, classroom management, clarity of instruction, instructional skills, promoting active learning and developing metacognitive skills, differentiation and inclusion, and assessment and evaluation. The first two belong to the overarching/super-component classroom environment, the next four ones to quality of teaching, and the last two to adaptive teaching (Teddlie et al., 2006 ).

Classroom climate : classroom environment created by the teacher in which all students are valued, the teacher interacts with all students, communicates high expectations and initiates active interaction and participation of the students.

Classroom management : teachers’ effective dealing with misbehaviour and disruption, maximization of learning time and clarity of rules.

Clarity of instruction : well-structured lessons, clear explanation of the lesson purpose, clear communication and regularly checking for understanding by the teacher.

Instructional skills : teacher’s ability to engage students, possession of good questioning skills and use of various teaching methods and strategies.

Promoting active learning and developing metacognitive skills : teacher’s help to students to develop problem-solving and metacognitive strategies, giving students opportunities to be active learners, fostering critical thinking and connecting course material to students’ real-world experiences.

Differentiation and inclusion : taking full account of student differences (e.g., by offering additional opportunities for practice for students who need them or by differentiating regarding the scope of assignments) and creating an environment in which all students are involved.

Assessment and evaluation : degree to which the assessment is aligned with goals and objectives and the teacher gives explicit, detailed, and constructive feedback.

In general, the ISTOF observation instrument contains components referring to more traditional approaches to teaching and learning as well as to more recent approaches. For example, classroom climate, classroom management and clarity of instruction are explicitly related to established teacher effectiveness models and research supporting direct or explicit instruction, while the components promoting active learning and metacognition, and differentiation have a link to constructivist approaches which underscore the importance of self-regulated learning (Muijs et al., 2018 ); the component instructional skills entail elements of both traditions.

In addition to and in close alignment with the observation instrument, Van Damme and Opdenakker developed for Flanders (Belgium) a student questionnaire (Opdenakker, 2020 ). This questionnaire was slightly adapted for use in the Netherlands as well (see, Opdenakker & Minnaert, 2011 ). The student questionnaire (46 items) revealed to have a three-factor structure and the quality of the instrument regarding the reliability of the scale scores was good. The three factors are the teacher as a helpful and good instructor (having good instructional skills, offering help and clear instruction), the teacher as promoter of active learning and differentiation, and the teacher as manager and organizer of classroom activities. Examples of items are for the teacher as a helpful and good instructor , ‘When students encounter difficulties with the subject matter, they get help and are told what they can do to overcome these difficulties,’ ‘The lessons are well structured and organized,’ and ‘The instruction is clear and understandable.’ Examples of items for the teacher as promoter of active learning and differentiation are, ‘Examples given by students are used during class,’ ‘We are invited to give our personal opinions on certain subjects,’ and ‘Our class is divided into different groups according to the tasks given to the students.’ Examples of items referring to the qualities of the teacher as manager and organizer of classroom activities are, ‘Our classroom is often out of control’ (reverse scored), and ‘Most of the students are disturbed when misbehaviour occurs in our classroom.’ The first mentioned factor can be interpreted as an indicator of (instructional) support and involvement of the teacher, the second one as an additional indicator of support (instructional and autonomy), and the last factor as an indicator of classroom management (Opdenakker & Minnaert, 2011 ).

1.1.5 The Teacher as a Social Context (TASC) Instruments

Questionnaires originally developed at the University of Rochester (USA) in line with the theoretical frameworks of the self-determination theory (Ryan & Deci, 2020 ) and the self-system process model of motivational development of Connell and Wellborn ( 1991 ). Simultaneously, a teacher and student version (for each a short and long version) were developed. Translations/adaptations and validation studies have been performed for a variety of countries (e.g., Belgium (Flanders), the Netherlands, Spain, Portugal, Indonesia) and evidence for the validity and reliability of measurements based on the TASC were reported. The long version of the student questionnaire will be addressed here (Belmont et al., 1992 ).

The original long-version student questionnaire consists of 52 items and taps student perceptions of teacher support and involvement referring to three dimensions: teacher involvement (14 items), structure (15 items), and autonomy support (12 items).

Teacher involvement : teacher’s affection and attunement towards the student as well as teacher’s dedication of resources and dependability towards the student.

Structure : teacher’s help and support, adjustment and monitoring of the student, teacher’s clear communication of expectations and teacher’s contingency.

Autonomy support : approaching the student with respect, paying attention to the relevance of school activities and content for the student, offering choice with regard to learning and tasks and avoiding controlling behaviour and language towards the student.

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Opdenakker, MC. (2023). Teacher and Teaching Behaviour and Student Motivational Outcomes: Critical Reflections on the Knowledge Base and on Future Research. In: Maulana, R., Helms-Lorenz, M., Klassen, R.M. (eds) Effective Teaching Around the World . Springer, Cham. https://doi.org/10.1007/978-3-031-31678-4_3

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Teacher Lore Concerning Teaching English Language Learners in Urban Schools: A Reciprocal Determinist Analysis , Helen Clare Colby

The Emergence of Teacher Self in the Elementary Classroom , Chelsea Cole

Exploring Teacher Beliefs of Adolescent Developmental Needs Through Positive Student Comments of their Teachers , Elizabeth Bowers Hinchcliff

Teaching Second-Grade Students to Write Expository Text , Angenette Cox Imbler

Exploring Dialogue Journals as a Context for Connecting with and Supporting the Emotional Lives of Fourth Graders , Samantha Simone Johnson

The Effect of Ethnic Identity on Motivation to bePhysically Active in Schools in Hawai’i , Nathan A. K. Kahaiali'i

Ninth-Grade Students' Motivation for Reading and Course Choice , McKenna Lyn Simmons

Theses/Dissertations from 2019 2019

Uncovering One Teacher's Knowledge of Arts Integration for Developing English Learners' Reading Comprehension: A Self-Study , Tina RaLinn McCulloch

A Content Analysis of Scientific Practices in a Fourth-Grade Commercial Literacy Program , Hailey A. Oswald

Reading Fluency and GoNoodle© Brain Breaks Among Elementary-Aged Children , Hannah Jeanne Wold

Theses/Dissertations from 2018 2018

Friendship and Language: How Kindergarteners Talk About Making Friends in a Two-Way Immersion School , Sionelle Nicole Beller

Lunchtime Experiences and Students' Sense of Belonging in Middle School , Anna Elisabeth Hinton

Perceptions of School Uniforms in Relation to Socioeconomic Statuses , Aaron B. Jones

The Operationalization of the Theoretical Antecedents of Collective Teacher Efficacy , Kathryn A. Larsen

Teacher Experiences in Highly Impacted Schools That Produce Happiness , Brittany Nicole Lund

Identifying Elements of Voice and Fostering Voice Development in First-Grade Science Writing , McKenna Lucille Maguet

Promoting Pleasure in Reading Through Sustained Silent Reading: A Self-Study of Teacher Practices , Kimberly Turley McKell

Sixth-Grade Elementary and Seventh- and Eighth-Grade Middle School Teachers' Knowledge and Beliefs About Science Literacy , Melissa P. Mendenhall

Building Procedural Fluency from Conceptual Understanding in Equivalence of Fractions: A Content Analysis of a Textbook Series , Mark S. Nance

Ethnic Identity and School Belonging Among Pacific Islander High School Students , Mari N. Oto

Self-Study of a Teacher's Practices of and Experience with Emotion Regulation , Lauren Elyse Paravato

Cultural Connections in the Classroom and Pacific Islander Students Value of Reading , Lyndsai K. Sylva

Theses/Dissertations from 2017 2017

Parent Perception of Systemic Success in Physical Education: A Study of Advocacy in Action , Rachel Valletta Griffiths

Theses/Dissertations from 2016 2016

Student Self-Assessment: Teachers' Definitions, Reasons, and Beliefs , Christopher Daren Andrews

What is Being Said about Historical Literacy in Literacy and Social Studies Journals: A Content Analysis , Kiera Beddes

A High School Biology Teacher's Development Through a New Teaching Assignment Coupled with Teacher-Led Professional Development , Lorien Young Francis

Emotions in Teaching: Self-Compassion , Stacey Freeman

Physical Activity Rates and Motivational Profiles of Adolescents While Keeping a Daily Leisure-Time Physical Activity Record , Matthew Osden Fullmer

Distraction, Enjoyment, and Motivation During an Indoor Cycling Unit of High School Physical Education , Kelsey Higginson

A Look at the Reliability of an Early Childhood Expository Comprehension Measure , Alta Adamma McDonald

Invisible Students: A Case Study of Friendless Students During the First Year of Junior High , Rachel E. Neeley

Picture Books as Mentor Texts for 10th-Grade Struggling Writers , David Willett Premont

Effects of Fourth- and First-Grade Cross-Age Tutoring on Mathematics Anxiety , Camille Margarett Rougeau

An Analysis of Support for Elementary Engineering Education Offered in the Science Teacher Journal Science and Children , Tawnicia Meservy Stocking

Theses/Dissertations from 2015 2015

Dyad Reading Experiences of Second-Grade English Learners with Fiction and Nonfiction Texts , Michelle Lynn Klvacek

Orchestrating Mathematical Discussions: A Novice Teacher's Implementation of Five Practices to Develop Discourse Orchestration in a Sixth-Grade Classroom , Jeffrey Stephen Young

Theses/Dissertations from 2014 2014

Parent Reasons for Enrollment at One Dual-Language Chinese Immersion Elementary School Program , Aaron W. Andersen

Effects of Teacher-to-Student Relatedness on Adolescent Male Motivation in Weight-Training Classes , Zack E. Beddoes

The Effects of Music on Physical Activity Rates of Junior High Physical Education Students , Lindsey Kaye Benham

What Matters Most? The Everyday Priorities of Teachers of English Language Learners , Johanna Boone

PE Central: A Possible Online Professional Development Tool , Amber M. Hall

Determining the Reliability of an Early Expository Comprehension Assessment , Tammie Harding

The Relationship Between Health-Related Fitness Knowledge, Perceived Competence, Self-Determination, and Physical Activity Behaviors of High School Students , Elizabeth Bailey Haslem

Supporting Ongoing Language and Literacy Development of Adolescent English Language Learners , Jason T. Jay

Components of Effective Writing Content Conferences in a Sixth-Grade Classroom , Paul Ricks

Online Student Discussions in a Blended Learning Classroom: Reconciling Conflicts Between a Flipped Instruction Model and Reform-Based Mathematics , Lewis L. Young

Theses/Dissertations from 2013 2013

An Investigation of the Effects of Integrating Science and Engineering Content and Pedagogy in an Elementary School Classroom , Katie Nicole Barth

Alignment Between Secondary Biology Textbooks and Standards for Teaching English Learners: A Content Analysis , Joseph H. Hanks

Content Analysis of New Teacher Induction and Mentoring Documents in Five Partnership Districts: Reflections and Acknowledgments of Complexity , Carol S. Larsen

Stories of Success: Three Latino Students Talk About School , Carol Ann Litster

Effects of Fourth- and Second-Grade Cross-Age Tutoring on Spelling Accuracy and Writing Fluency , Rebekkah J. Mitchell

The United States Growth over 16 Years of Student Correct Responses on the TIMSS: Are We Really That Far Behind? , Jacob Michael Zonts

Theses/Dissertations from 2012 2012

A Content Analysis of Family Structure in Newbery Medal and Honor Books, 1930 -- 2010 , Shannon Marie Despain

A Content Analysis of Inquiry in Third Grade Science Textbooks , Rebecca Adams Lewis

Science Self-Efficacy and School Transitions: Elementary School to Middle School and Middle School to High School , Brandi Lue Lofgran

Balancing Support and Challenge within the Mentoring Relationship , Tiffanie Joy Miley

Explicitly Teaching Multiple Modes of Representation in Science Discourse: The Impact on Middle School Science Student Learning , Ryan Nixon

Navigating the Changing Face of Beginning Reading Instruction: Am I Right Back Where I Started? , DeAnna M. Perry

Teacher Definitions of Integration in Primary Grades , Jeanne Sperry Prestwich

Effective Professional Development: A Study of a Teacher-Initiated, Interdisciplinary Professional Learning Community , Mary Ann Quantz

Theses/Dissertations from 2011 2011

An Examination of the Effects of Using Systematic and Engaging Early Literacy to Teach Tier 3 Students to Read Consonant-Vowel-Consonant (CVC) Words , Esther Marshall

Two Marginalized Adolescents Using the Internet to Complete an Inquiry Project , Jennifer Thomas

Describing the Reading Motivation of Four Second-Grade Students with Varying Abilities. , Kathy Jane White

Theses/Dissertations from 2010 2010

Establishing Reliability of Reading Comprehension Ratings of Fifth-Grade Students' Oral Retellings , Laura Elizabeth Bernfeld

The Nature of Classroom Instruction and Physical Environments That Support Elementary Writing , Monica Thomas Billen

Understanding the Tensions That Exist Between Two Co-Teachers Education Classroom Using Positioning , Garth Gagnier

A Challenging and Rewarding Process: Implementing Critical Literacy Instruction in a Middle School Classroom , Amy Michelle Geilman

The Nature of Transfer from the Concepts and Vocabulary Taught in a Character Education Unit to Students Classroom Discourse , Marianne E. Gill

Mathematics Vocabulary and English Learners: A Study of Students' Mathematical Thinking , Hilary Hart

Adolescent Literate Identity Online: Individuals and the Discourse of a Class Wiki , Amanda J. McCollum

The Stories of Three High School English Teachers Involved in a Collaborative Study Group , Marjoire Ralph

Narrating the Literate Identities of Five Ninth Grade Boys on the School Landscape , Mary Frances Rice

Comparing the Pedagogical Thinking of More Successful and Less Successful Adult ESL Instructors Using Stimulated Recall , Jason Paul Roberts

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Effect of Teacher's Behaviour on Student's Academic Performance and Personality

2022, Global Scientific Journals

This study was designed to find out the effect on a student's personality and his/her academic career or achievement due to a teacher's behaviour and attitude. The main purpose of this paper is to focus on the major issues related to teachers' behaviour, to study the factors affecting students' personalities, academic achievement, and careers, and then to recommend suggestions for handling these problems effectively. It is very important to find out the characteristics and significance of teachers' behaviour and its effect on the academic achievement and personality of students. Therefore, teachers' positive behaviour and interaction with students play a critical role in strengthening the potential required for better academic achievement and personality development of students. Hence, the purpose of the study was to examine the effect on students' academic achievement and personality as a result of the teacher's behaviour.

Related Papers

Journal of Physical Education Research (JOPER)

An interrogative study was conducted with the purpose to evaluate the impact of teacher personality on student's academic performance. In this regard, structured and pre-tested professional attitude scale (PAS) was designed to include demographics, socioeconomic aspects and to set research objectives. The target population was the students of sports sciences and physical education studying in different universities of Pakistan. Statistical Package for Social Sciences (SPSS-20) was used for the analysis of data. Regression as Statistical tool used for the purpose to evaluate the impact of teacher personality on the academic performance of the students. After analysis it was found that the personality of teacher is among the key components of teacher's professional attitude affecting significantly on the academic performance of the students.

zubaria khalid

Psychology and Education: A Multidisciplinary Journal

Psychology and Education

Teachers as professional leaders perform a crucial role in establishing positive behavior and qualities among learners. This descriptive research aimed to shed light to these questions determine the influence of teacher's personality and behavior on the respondents' character building in terms of their performance of their academic duties, acceptance of additional duties in class, and interaction with fellow students/teachers/non-teaching staff of the school. To provide understanding on the problem this study employed the use of self-made survey questionnaire and sought the help of 100 participants from the local of the study Antipolo City Senior High School. The results of the study revealed that in terms of performing their academic duties gained an overall mean of 3.56 with a verbal interpretation of Very Satisfactory while in terms of accepting additional duties in class and of interaction with fellow students/teachers/nonteaching staff obtained an overall mean of 3.19 and 3.17 respectively with the verbal interpretation of Satisfactory. Also, the results showed that there is significant difference on the influence of teacher's personality and behavior on the respondents' character building in terms of the given parameters.

Acta Technologica Dubnicae

Milan Jozek

There is something in everyone that does not change. The personality of a teacher or an educator stays in the centre of educational work. The personal contact and dialogic disposition of a teacher helps to form the personal potential of a human being to overcome the difficulties and contribute to the optimal functioning in a social environment. The process of learning and the growth of personality belong to a category of interpersonal relationships. A very strong emphasis is placed on the so called “methods of dialogue“, which can not only reduce destructive influences, but also teaches us how to accept criticism in a non-offensive way. Everything should take place in an open climate without judgement.

zahra bayani

The study of teacher's personality and the extent of student learning will always have to turn to one another for help and the one will not invalidate the other. Education plays main role in all aspects of life. By providing the quality education we can produce quality products. The decisions and actions of a teacher affect the learning process. The major purpose of present study is to investigate the effects of teacher’s personality traits on the learning of the exceptional students, to examine the learning achievement of the exceptional students as a result of teacher’s behavior, to clarify the relationship between teacher’s personality and input learning and finally to recommend strategies for the improvement of teacher's personality in exceptional schools. The theoretical framework of this study is based on Brophy's Key Behaviors Contribution to Effective Teaching, Ryans and Johnson Personality Traits.

Journal of Organisation & Human Behaviour

Publishing India Group

This study sought to investigate the relationship between students' personality types and their academic achievement in Colleges of Teachers' Education, Western Ethiopia. Three colleges of teachers' education, namely DambiDollo, Shambu, and Nekemte, were selected by purposive sampling technique. The study employed correlation research design. The sample size was 351 trainees. A standard questionnaire was used as the instrument for collecting data from the students, while interviews were conducted with the teachers. Validity of the instruments was checked through experts in research and piloting. Quantitative data analysis was carried out using descriptive and inferential statistics such as percentages, mean, standard deviation, Pearson correlation, regression, and one-way ANOVA test. The study established that neuroticism and extroversion were negatively related to academic achievement, whereas conscientiousness, agreeableness, and openness have a positive association with academic achievement. Conscientiousness personality type was the best and strongest individual predictor of academic achievement at the colleges of teachers' training. Therefore, it is important to institutionalise the trait of conscientious during the initial years of education, by presenting appropriate conscientious role models or encouraging conscientious people. Findings of this study emphasise the necessity of informing curriculum developers of the personality traits and individual differences of learners, to help them take such differences into account and be more flexible while developing educational curriculums.

Elementary Education Online

Syed Hyder R A Z A Shah

The aim of the research is to know the effects of teachers' personality on character building of students at secondary level in Sanghar. A quantitative method is used for the research in which questionnaire is adopted as research tool. A random, sampling technique is used to collected data from 120 teachers of secondary schools. Collected data is analyzed by Statistical packages for social sciences (SPSS) 20 th version. Descriptive statistics is done to get results. The study is based on the three main objectives. The first and foremost objective is to find out types of teachers' personality in government and private secondary schools at secondary level at Sanghar. The next objective is to know significance differences between government and private secondary schools teachers' personality while building character at secondary level in Sanghar. The last objective is to understand effects of teachers' personality on students' character building at secondary level at Sanghar. The results revealed that conscientiousness had got the highest mean (M=4.21) and agreeableness lowest mean i.e. (M= 3.21) in government school teachers. Whereas the type of teachers' personality among Private secondary school teachers is openness to experience is highest mean M=4.58 and neuroticism is lowest mean i.e. M= 3.77. This change is because of difference in teaching system in specific and curriculum in general. The result of independent t-test suggests that there is significant difference between government and private school teachers' personality building students' character in Sanghar. Last but not least, teachers' personality greatly affects students' character building. The results of the study also revealed that teachers' personality greatly affect students' character. The research also declared that private secondary school teachers are more careful about their personality as well as students' character building than government teachers.

Journal of Interdisciplinary Cycle Research Volume XIII, Issue IV, April/2021 ISSN NO: 0022-1945

Dr SHRUTI TIWARI

The teacher is an employee of the educational establishment, having qualified for the teaching and education of their students. Teacher play significant role in students career and life ., he is obliged to conscientiously carry out the tasks of teaching and educational and charitable. Teacher will call the person responsible for the conduct and coordination of work in the classroom. In the study researcher wants to know teacher personality impact on students. The teacher educator could feel the satisfaction of relevant professional work, enjoy his progress in many areas of development, as well as the appropriate contact with parents and legal guardians must meet specific conditions relating to his personality. Emotional involvement of the teacher, his serenity, creativity and openness to children and young people, as well as their parents, triggers analogous reactions, that is, a positive attitude and the need for cognitive activity.

ACE Research Propellor

Prakash Srinivasan

IJAR Indexing

This study aimed to determine the relationships of big five personality traits and students? academic performance of College of Teacher Education at Laguna State Polytechnic University Los Ba?os Campus, Los Ba?os, Laguna ,1st semester Academic Year 2016-2017. The hypothesis stating that no significant relationship between the personality traits and the academic performance of the respondents was determined at ).05 level of significance. Employing correlational research design. The respondents of the study were the 219 Bachelor of Secondary Education (BSEd) and Bachelor of Elementary Education students (BEEd) from second year, third year and fourth year level. A valid survey questionnaire on determining the level of big five personality traits of the respondents which was adapted from Chowdburry?s Individual Level of Big Five Personality Test. Pearson r was used to determine the significant relationship between students? big five personality traits and their? academic performance. Most of the respondents GWA range from 1.50 to 1.74 consist of 70 of 31.96% while there were 10 or 4.57% got a GWA of 2.01 above. The results describe that openness, conscientiousness and extraversion show negative correlation while agreeableness and neuroticism show positive correlation but the relationship between variables are all weak such that the null hypothesis stating that there is no significant relationship between the said variables is rejected with the p-value range from of 0. 0001 to 0.0018 which is lower than the level of significance of 0.05. A significant relationship was found between the level of big five personality traits and of students? academic performance. The results describe that the trait reflects \'open-mindedness\' and interest in culture. High scorers tend to be imaginative, creative, and to seek out cultural and educational experiences. Low scorers are more down-to-earth, less interested in art and more practical in nature. Most of the students who have taken this test, their score on this dimnsion (25.31) is relatively low. The students score on conscientiousness (29.68) is about average. High scorers are methodical, well organized and dutiful. Low scorers are less careful, less focused. In extraversion their scores (27.79) is about average wherein high in extraversion are energetic and seek out the company of others. Low scorers (introverts) tend to be more quiet and reserved. In Agreeableness , student? score on this dimension (29.94) is about average it reflects how they tend to interact with others. People high in agreeableness tend to be trusting, friendly and cooperative. Low scorers tend to be more aggressive and less cooperative. In Neuroticism (22.40) which is relatively low, this trait reflects the tendency to experience negative thoughts and feelings. High scorers are prone to insecurity and emotional distress. Low scorers tend to be more relaxed, less emotional and less prone to distress. The researcher concluded that all of the personality traits show significant relationship in the academic. Based on the conclusions the researchers recommended instructors or teachers must take into consideration thoe students traits as one of the factors affecting students? performance. Seminars on personality development and moral values may be conducted by the College to deepen the students understanding on the importance of having good traits as future educators. Further study is also recommended by the researchers since it is limited only in the College of Teacher Education.

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Teacher and Teaching Effects on Students’ Attitudes and Behaviors

David blazar.

Harvard Graduate School of Education

Matthew A. Kraft

Brown University

Associated Data

Research has focused predominantly on how teachers affect students’ achievement on tests despite evidence that a broad range of attitudes and behaviors are equally important to their long-term success. We find that upper-elementary teachers have large effects on self-reported measures of students’ self-efficacy in math, and happiness and behavior in class. Students’ attitudes and behaviors are predicted by teaching practices most proximal to these measures, including teachers’ emotional support and classroom organization. However, teachers who are effective at improving test scores often are not equally effective at improving students’ attitudes and behaviors. These findings lend empirical evidence to well-established theory on the multidimensional nature of teaching and the need to identify strategies for improving the full range of teachers’ skills.

1. Introduction

Empirical research on the education production function traditionally has examined how teachers and their background characteristics contribute to students’ performance on standardized tests ( Hanushek & Rivkin, 2010 ; Todd & Wolpin, 2003 ). However, a substantial body of evidence indicates that student learning is multidimensional, with many factors beyond their core academic knowledge as important contributors to both short- and long-term success. 1 For example, psychologists find that emotion and personality influence the quality of one’s thinking ( Baron, 1982 ) and how much a child learns in school ( Duckworth, Quinn, & Tsukayama, 2012 ). Longitudinal studies document the strong predictive power of measures of childhood self-control, emotional stability, persistence, and motivation on health and labor market outcomes in adulthood ( Borghans, Duckworth, Heckman, & Ter Weel, 2008 ; Chetty et al., 2011 ; Moffitt et. al., 2011 ). In fact, these sorts of attitudes and behaviors are stronger predictors of some long-term outcomes than test scores ( Chetty et al., 2011 ).

Consistent with these findings, decades worth of theory also have characterized teaching as multidimensional. High-quality teachers are thought and expected not only to raise test scores but also to provide emotionally supportive environments that contribute to students’ social and emotional development, manage classroom behaviors, deliver accurate content, and support critical thinking ( Cohen, 2011 ; Lampert, 2001 ; Pianta & Hamre, 2009 ). In recent years, two research traditions have emerged to test this theory using empirical evidence. The first tradition has focused on observations of classrooms as a means of identifying unique domains of teaching practice ( Blazar, Braslow, Charalambous, & Hill, 2015 ; Hamre et al., 2013 ). Several of these domains, including teachers’ interactions with students, classroom organization, and emphasis on critical thinking within specific content areas, aim to support students’ development in areas beyond their core academic skill. The second research tradition has focused on estimating teachers’ contribution to student outcomes, often referred to as “teacher effects” ( Chetty Friedman, & Rockoff, 2014 ; Hanushek & Rivkin, 2010 ). These studies have found that, as with test scores, teachers vary considerably in their ability to impact students’ social and emotional development and a variety of observed school behaviors ( Backes & Hansen, 2015 ; Gershenson, 2016 ; Jackson, 2012 ; Jennings & DiPrete, 2010 ; Koedel, 2008 ; Kraft & Grace, 2016 ; Ladd & Sorensen, 2015 ; Ruzek et al., 2015 ). Further, weak to moderate correlations between teacher effects on different student outcomes suggest that test scores alone cannot identify teachers’ overall skill in the classroom.

Our study is among the first to integrate these two research traditions, which largely have developed in isolation. Working at the intersection of these traditions, we aim both to minimize threats to internal validity and to open up the “black box” of teacher effects by examining whether certain dimensions of teaching practice predict students’ attitudes and behaviors. We refer to these relationships between teaching practice and student outcomes as “teaching effects.” Specifically, we ask three research questions:

• To what extent do teachers impact students’ attitudes and behaviors in class?
• To what extent do specific teaching practices impact students’ attitudes and behaviors in class?
• Are teachers who are effective at raising test-score outcomes equally effective at developing positive attitudes and behaviors in class?

To answer our research questions, we draw on a rich dataset from the National Center for Teacher Effectiveness of upper-elementary classrooms that collected teacher-student links, observations of teaching practice scored on two established instruments, students’ math performance on both high- and low-stakes tests, and a student survey that captured their attitudes and behaviors in class. We used this survey to construct our three primary outcomes: students’ self-reported self-efficacy in math, happiness in class, and behavior in class. All three measures are important outcomes of interest to researchers, policymakers, and parents ( Borghans et al., 2008 ; Chetty et al., 2011 ; Farrington et al., 2012 ). They also align with theories linking teachers and teaching practice to outcomes beyond students’ core academic skills ( Bandura, Barbaranelli, Caprara, & Pastorelli, 1996 ; Pianta & Hamre, 2009 ), allowing us to test these theories explicitly.

We find that upper-elementary teachers have substantive impacts on students’ self-reported attitudes and behaviors in addition to their math performance. We estimate that the variation in teacher effects on students’ self-efficacy in math and behavior in class is of similar magnitude to the variation in teacher effects on math test scores. The variation of teacher effects on students’ happiness in class is even larger. Further, these outcomes are predicted by teaching practices most proximal to these measures, thus aligning with theory and providing important face and construct validity to these measures. Specifically, teachers’ emotional support for students is related both to their self-efficacy in math and happiness in class. Teachers’ classroom organization predicts students’ reports of their own behavior in class. Errors in teachers’ presentation of mathematical content are negatively related to students’ self-efficacy in math and happiness in class, as well as students’ math performance. Finally, we find that teachers are not equally effective at improving all outcomes. Compared to a correlation of 0.64 between teacher effects on our two math achievement tests, the strongest correlation between teacher effects on students’ math achievement and effects on their attitudes or behaviors is 0.19.

Together, these findings add further evidence for the multidimensional nature of teaching and, thus, the need for researchers, policymakers, and practitioners to identify strategies for improving these skills. In our conclusion, we discuss several ways that policymakers and practitioners may start to do so, including through the design and implementation of teacher evaluation systems, professional development, recruitment, and strategic teacher assignments.

2. Review of Related Research

Theories of teaching and learning have long emphasized the important role teachers play in supporting students’ development in areas beyond their core academic skill. For example, in their conceptualization of high-quality teaching, Pianta and Hamre (2009) describe a set of emotional supports and organizational techniques that are equally important to learners as teachers’ instructional methods. They posit that, by providing “emotional support and a predictable, consistent, and safe environment” (p. 113), teachers can help students become more self-reliant, motivated to learn, and willing to take risks. Further, by modeling strong organizational and management structures, teachers can help build students’ own ability to self-regulate. Content-specific views of teaching also highlight the importance of teacher behaviors that develop students’ attitudes and behaviors in ways that may not directly impact test scores. In mathematics, researchers and professional organizations have advocated for teaching practices that emphasize critical thinking and problem solving around authentic tasks ( Lampert, 2001 ; National Council of Teachers of Mathematics [NCTM], 1989 , 2014 ). Others have pointed to teachers’ important role of developing students’ self-efficacy and decreasing their anxiety in math ( Bandura et al., 1996 ; Usher & Pajares, 2008 ; Wigfield & Meece, 1988 ).

In recent years, development and use of observation instruments that capture the quality of teachers’ instruction have provided a unique opportunity to examine these theories empirically. One instrument in particular, the Classroom Assessment Scoring System (CLASS), is organized around “meaningful patterns of [teacher] behavior…tied to underlying developmental processes [in students]” ( Pianta & Hamre, 2009 , p. 112). Factor analyses of data collected by this instrument have identified several unique aspects of teachers’ instruction: teachers’ social and emotional interactions with students, their ability to organize and manage the classroom environment, and their instructional supports in the delivery of content ( Hafen et al., 2015 ; Hamre et al., 2013 ). A number of studies from developers of the CLASS instrument and their colleagues have described relationships between these dimensions and closely related student attitudes and behaviors. For example, teachers’ interactions with students predicts students’ social competence, engagement, and risk-taking; teachers’ classroom organization predicts students’ engagement and behavior in class ( Burchinal et al., 2008 ; Downer, Rimm-Kaufman, & Pianta, 2007 ; Hamre, Hatfield, Pianta, & Jamil, 2014 ; Hamre & Pianta, 2001 ; Luckner & Pianta, 2011 ; Mashburn et al., 2008 ; Pianta, La Paro, Payne, Cox, & Bradley, 2002 ). With only a few exceptions (see Downer et al., 2007 ; Hamre & Pianta, 2001 ; Luckner & Pianta, 2011 ), though, these studies have focused on pre-kindergarten settings.

Additional content-specific observation instruments highlight several other teaching competencies with links to students’ attitudes and behaviors. For example, in this study we draw on the Mathematical Quality of Instruction (MQI) to capture math-specific dimensions of teachers’ classroom practice. Factor analyses of data captured both by this instrument and the CLASS identified two teaching skills in addition to those described above: the cognitive demand of math activities that teachers provide to students and the precision with which they deliver this content ( Blazar et al., 2015 ). Validity evidence for the MQI has focused on the relationship between these teaching practices and students’ math test scores ( Blazar, 2015 ; Kane & Staiger, 2012 ), which makes sense given the theoretical link between teachers’ content knowledge, delivery of this content, and students’ own understanding ( Hill et al., 2008 ). However, professional organizations and researchers also describe theoretical links between the sorts of teaching practices captured on the MQI and student outcomes beyond test scores ( Bandura et al., 1996 ; Lampert, 2001 ; NCTM, 1989 , 2014 ; Usher & Pajares, 2008 ; Wigfield & Meece, 1988 ) that, to our knowledge, have not been tested.

In a separate line of research, several recent studies have borrowed from the literature on teachers’ “value-added” to student test scores in order to document the magnitude of teacher effects on a range of other outcomes. These studies attempt to isolate the unique effect of teachers on non-tested outcomes from factors outside of teachers’ control (e.g., students’ prior achievement, race, gender, socioeconomic status) and to limit any bias due to non-random sorting. Jennings and DiPrete (2010) estimated the role that teachers play in developing kindergarten and first-grade students’ social and behavioral outcomes. They found within-school teacher effects on social and behavioral outcomes that were even larger (0.21 standard deviations [sd]) than effects on students’ academic achievement (between 0.12 sd and 0.15 sd, depending on grade level and subject area). In a study of 35 middle school math teachers, Ruzek et al. (2015) found small but meaningful teacher effects on students’ motivation between 0.03 sd and 0.08 sd among seventh graders. Kraft and Grace (2016) found teacher effects on students’ self-reported measures of grit, growth mindset and effort in class ranging between 0.14 and 0.17 sd. Additional studies identified teacher effects on students’ observed school behaviors, including absences, suspensions, grades, grade progression, and graduation ( Backes & Hansen, 2015 ; Gershenson, 2016 ; Jackson, 2012 ; Koedel, 2008 ; Ladd & Sorensen, 2015 ).

To date, evidence is mixed on the extent to which teachers who improve test scores also improve other outcomes. Four of the studies described above found weak relationships between teacher effects on students’ academic performance and effects on other outcome measures. Compared to a correlation of 0.42 between teacher effects on math versus reading achievement, Jennings and DiPrete (2010) found correlations of 0.15 between teacher effects on students’ social and behavioral outcomes and effects on either math or reading achievement. Kraft and Grace (2016) found correlations between teacher effects on achievement outcomes and multiple social-emotional competencies were sometimes non-existent and never greater than 0.23. Similarly, Gershenson (2016) and Jackson (2012) found weak or null relationships between teacher effects on students’ academic performance and effects on observed schools behaviors. However, correlations from two other studies were larger. Ruzek et al. (2015) estimated a correlation of 0.50 between teacher effects on achievement versus effects on students’ motivation in math class. Mihaly, McCaffrey, Staiger, and Lockwood (2013) found a correlation of 0.57 between middle school teacher effects on students’ self-reported effort versus effects on math test scores.

Our analyses extend this body of research by estimating teacher effects on additional attitudes and behaviors captured by students in upper-elementary grades. Our data offer the unique combination of a moderately sized sample of teachers and students with lagged survey measures. We also utilize similar econometric approaches to test the relationship between teaching practice and these same attitudes and behaviors. These analyses allow us to examine the face validity of our teacher effect estimates and the extent to which they align with theory.

3. Data and Sample

Beginning in the 2010–2011 school year, the National Center for Teacher Effectiveness (NCTE) engaged in a three-year data collection process. Data came from participating fourth-and fifth-grade teachers (N = 310) in four anonymous, medium to large school districts on the East coast of the United States who agreed to have their classes videotaped, complete a teacher questionnaire, and help collect a set of student outcomes. Teachers were clustered within 52 schools, with an average of six teachers per school. While NCTE focused on teachers’ math instruction, participants were generalists who taught all subject areas. This is important, as it allowed us to isolate the contribution of individual teachers to students’ attitudes and behaviors, which is considerably more challenging when students are taught by multiple teachers. It also suggests that the observation measures, which assessed teachers’ instruction during math lessons, are likely to capture aspects of their classroom practice that are common across content areas.

In Table 1 , we present descriptive statistics on participating teachers and their students. We do so for the full NCTE sample, as well as for a subsample of teachers whose students were in the project in both the current and prior years. This latter sample allowed us to capture prior measures of students’ attitudes and behaviors, a strategy that we use to increase internal validity and that we discuss in more detail below. 2 When we compare these samples, we find that teachers look relatively similar with no statistically significant differences on any observable characteristic. Reflecting national patterns, the vast majority of elementary teachers in our sample are white females who earned their teaching credential through traditional certification programs. (See Hill, Blazar, & Lynch, 2015 for a discussion of how these teacher characteristics were measured.)

Participant Demographics

Students in our samples look similar to those in many urban districts in the United States, where roughly 68% are eligible for free or reduced-price lunch, 14% are classified as in need of special education services, and 16% are identified as limited English proficient; roughly 31% are African American, 39% are Hispanic, and 28% are white ( Council of the Great City Schools, 2013 ). We do observe some statistically significant differences between student characteristics in the full sample versus our analytic subsample. For example, the percentage of students identified as limited English proficient was 20% in the full sample compared to 14% in the sample of students who ever were part of analyses drawing on our survey measures. Although variation in samples could result in dissimilar estimates across models, the overall character of our findings is unlikely to be driven by these modest differences.

3.1. Students’ Attitudes and Behaviors

As part of the expansive data collection effort, researchers administered a student survey with items (N = 18) that were adapted from other large-scale surveys including the TRIPOD, the MET project, the National Assessment of Educational Progress (NAEP), and the Trends in International Mathematics and Science Study (TIMSS) (see Appendix Table 1 for a full list of items). Items were selected based on a review of the research literature and identification of constructs thought most likely to be influenced by upper-elementary teachers. Students rated all items on a five-point Likert scale where 1 = Totally Untrue and 5 = Totally True.

We identified a parsimonious set of three outcome measures based on a combination of theory and exploratory factor analyses (see Appendix Table 1 ). 3 The first outcome, which we call Self-Efficacy in Math (10 items), is a variation on well-known constructs related to students’ effort, initiative, and perception that they can complete tasks. The second related outcome measure is Happiness in Class (5 items), which was collected in the second and third years of the study. Exploratory factor analyses suggested that these items clustered together with those from Self-Efficacy in Math to form a single construct. However, post-hoc review of these items against the psychology literature from which they were derived suggests that they can be divided into a separate domain. As above, this measure is a school-specific version of well-known scales that capture students’ affect and enjoyment ( Diener, 2000 ). Both Self-Efficacy in Math and Happiness in Class have relatively high internal consistency reliabilities (0.76 and 0.82, respectively) that are similar to those of self-reported attitudes and behaviors explored in other studies ( Duckworth et al., 2007 ; John & Srivastava, 1999 ; Tsukayama et al., 2013 ). Further, self-reported measures of similar constructs have been linked to long-term outcomes, including academic engagement and earnings in adulthood, even conditioning on cognitive ability ( King, McInerney, Ganotice, & Villarosa, 2015 ; Lyubomirsky, King, & Diener, 2005 ).

The third and final construct consists of three items that were meant to hold together and which we call Behavior in Class (internal consistency reliability is 0.74). Higher scores reflect better, less disruptive behavior. Teacher reports of students’ classroom behavior have been found to relate to antisocial behaviors in adolescence, criminal behavior in adulthood, and earnings ( Chetty et al., 2011 ; Segal, 2013 ; Moffitt et al., 2011 ; Tremblay et al., 1992 ). Our analysis differs from these other studies in the self-reported nature of the behavior outcome. That said, other studies also drawing on elementary school students found correlations between self-reported and either parent- or teacher-reported measures of behavior that were similar in magnitude to correlations between parent and teacher reports of student behavior ( Achenbach, McConaughy, & Howell, 1987 ; Goodman, 2001 ). Further, other studies have found correlations between teacher-reported behavior of elementary school students and either reading or math achievement ( r = 0.22 to 0.28; Miles & Stipek, 2006 ; Tremblay et al., 1992 ) similar to the correlation we find between students’ self-reported Behavior in Class and our two math test scores ( r = 0.24 and 0.26; see Table 2 ). Together, this evidence provides both convergent and consequential validity evidence for this outcome measure. For all three of these outcomes, we created final scales by reverse coding items with negative valence and averaging raw student responses across all available items. 4 We standardized these final scores within years, given that, for some measures, the set of survey items varied across years.

Descriptive Statistics for Students' Academic Performance, Attitudes, and Behaviors

For high-stakes math test, reliability varies by district; thus, we report the lower bound of these estimates. Self-Efficacy in Math, Happiness in Class, and Behavior in Class are measured on a 1 to 5 Likert Scale. Statistics were generated from all available data.

3.2. Student Demographic and Test Score Information

Student demographic and achievement data came from district administrative records. Demographic data include gender, race/ethnicity, free- or reduced-price lunch (FRPL) eligibility, limited English proficiency (LEP) status, and special education (SPED) status. These records also included current- and prior-year test scores in math and English Language Arts (ELA) on state assessments, which we standardized within districts by grade, subject, and year using the entire sample of students.

The project also administered a low-stakes mathematics assessment to all students in the study. Internal consistency reliability is 0.82 or higher for each form across grade levels and school years ( Hickman, Fu, & Hill, 2012 ). We used this assessment in addition to high-stakes tests given that teacher effects on two outcomes that aim to capture similar underlying constructs (i.e., math achievement) provide a unique point of comparison when examining the relationship between teacher effects on student outcomes that are less closely related (i.e., math achievement versus attitudes and behaviors). Indeed, students’ high- and low-stake math test scores are correlated more strongly ( r = 0.70) than any other two outcomes (see Table 1 ). 5

3.3. Mathematics Lessons

Teachers’ mathematics lessons were captured over a three-year period, with an average of three lessons per teacher per year. 6 Trained raters scored these lessons on two established observational instruments, the CLASS and the MQI. Analyses of these same data show that items cluster into four main factors ( Blazar et al., 2015 ). The two dimensions from the CLASS instrument capture general teaching practices: Emotional Support focuses on teachers’ interactions with students and the emotional environment in the classroom, and is thought to increase students’ social and emotional development; and Classroom Organization focuses on behavior management and productivity of the lesson, and is thought to improve students’ self-regulatory behaviors ( Pianta & Hamre, 2009 ). 7 The two dimensions from the MQI capture mathematics-specific practices: Ambitious Mathematics Instruction focuses on the complexity of the tasks that teachers provide to their students and their interactions around the content, thus corresponding to the set of professional standards described by NCTM (1989 , 2014 ) and many elements contained within the Common Core State Standards for Mathematics ( National Governors Association Center for Best Practices, 2010 ); Mathematical Errors identifies any mathematical errors or imprecisions the teacher introduces into the lesson. Both dimensions from the MQI are linked to teachers’ mathematical knowledge for teaching and, in turn, to students’ math achievement ( Blazar, 2015 ; Hill et al., 2008 ; Hill, Schilling, & Ball, 2004 ). Correlations between dimensions range from roughly 0 (between Emotional Support and Mathematical Errors ) to 0.46 (between Emotional Support and Classroom Organization ; see Table 3 ).

Descriptive Statistics for CLASS and MQI Dimensions

Intraclass correlations were adjusted for the modal number of lessons. CLASS items (from Emotional Support and Classroom Organization) were scored on a scale from 1 to 7. MQI items (from Ambitious Instruction and Errors) were scored on a scale from 1 to 3. Statistics were generated from all available data.

We estimated reliability for these metrics by calculating the amount of variance in teacher scores that is attributable to the teacher (the intraclass correlation [ICC]), adjusted for the modal number of lessons. These estimates are: 0.53, 0.63, 0.74, and 0.56 for Emotional Support, Classroom Organization, Ambitious Mathematics Instruction , and Mathematical Errors , respectively (see Table 3 ). Though some of these estimates are lower than conventionally acceptable levels (0.7), they are consistent with those generated from similar studies ( Kane & Staiger, 2012 ). We standardized scores within the full sample of teachers to have a mean of zero and a standard deviation of one.

4. Empirical Strategy

4.1. estimating teacher effects on students’ attitudes and behaviors.

Like others who aim to examine the contribution of individual teachers to student outcomes, we began by specifying an education production function model of each outcome for student i in district d , school s , grade g , class c with teacher j at time t :

OUTCOME idsgict is used interchangeably for both math test scores and students’ attitudes and behaviors, which we modeled in separate equations as a cubic function of students’ prior achievement, A it −1 , in both math and ELA on the high-stakes district tests 8 ; demographic characteristics, X it , including gender, race, FRPL eligibility, SPED status, and LEP status; these same test-score variables and demographic characteristics averaged to the class level, X ¯ it c ; and district-by-grade-by-year fixed effects, τ dgt , that account for scaling of high-stakes test. The residual portion of the model can be decomposed into a teacher effect, µ j , which is our main parameter of interest and captures the contribution of teachers to student outcomes above and beyond factors already controlled for in the model; a class effect, δ jc , which is estimated by observing teachers over multiple school years; and a student-specific error term,. ε idsgjct 9

The key identifying assumption of this model is that teacher effect estimates are not biased by non-random sorting of students to teachers. Recent experimental ( Kane, McCaffrey, Miller, & Staiger, 2013 ) and quasi-experimental ( Chetty et al., 2014 ) analyses provide strong empirical support for this claim when student achievement is the outcome of interest. However, much less is known about bias and sorting mechanisms when other outcomes are used. For example, it is quite possible that students were sorted to teachers based on their classroom behavior in ways that were unrelated to their prior achievement. To address this possibility, we made two modifications to equation (1) . First, we included school fixed effects, ω s , to account for sorting of students and teachers across schools. This means that estimates rely only on between-school variation, which has been common practice in the literature estimating teacher effects on student achievement. In their review of this literature, Hanushek and Rivkin (2010) propose ignoring the between-school component because it is “surprisingly small” and because including this component leads to “potential sorting, testing, and other interpretative problems” (p. 268). Other recent studies estimating teacher effects on student outcomes beyond test scores have used this same approach ( Backes & Hansen, 2015 ; Gershenson, 2016 ; Jackson, 2012 ; Jennings & DiPrete, 2010 ; Ladd & Sorensen, 2015 ; Ruzek et al., 2015 ). Another important benefit of using school fixed effects is that this approach minimizes the possibility of reference bias in our self-reported measures ( West et al., 2016 ; Duckworth & Yeager, 2015 ). Differences in school-wide norms around behavior and effort may change the implicit standard of comparison (i.e. reference group) that students use to judge their own behavior and effort.

Restricting comparisons to other teachers and students within the same school minimizes this concern. As a second modification for models that predict each of our three student survey measures, we included OUTCOME it −1 on the right-hand side of the equation in addition to prior achievement – that is, when predicting students’ Behavior in Class , we controlled for students’ self-reported Behavior in Class in the prior year. 10 This strategy helps account for within-school sorting on factors other than prior achievement.

Using equation (1) , we estimated the variance of µ j , which is the stable component of teacher effects. We report the standard deviation of these estimates across outcomes. This parameter captures the magnitude of the variability of teacher effects. With the exception of teacher effects on students’ Happiness in Class , where survey items were not available in the first year of the study, we included δ jc in order to separate out the time-varying portion of teacher effects, combined with peer effects and any other class-level shocks. The fact that we are able to separate class effects from teacher effects is an important extension of prior studies examining teacher effects on outcomes beyond test scores, many of which only observed teachers at one point in time.

Following Chetty et al. (2011) , we estimated the magnitude of the variance of teacher effects using a direct, model-based estimate derived via restricted maximum likelihood estimation. This approach produces a consistent estimator for the true variance of teacher effects ( Raudenbush & Bryk, 2002 ). Calculating the variation across individual teacher effect estimates using Ordinary Least Squares regression would bias our variance estimates upward because it would conflate true variation with estimation error, particularly in instances where only a handful of students are attached to each teachers. Alternatively, estimating the variation in post-hoc predicted “shrunken” empirical Bayes estimates would bias our variance estimate downward relative to the size of the measurement error (Jacob & Lefgren, 2005).

4.2. Estimating Teaching Effects on Students’ Attitudes and Behaviors

We examined the contribution of teachers’ classroom practices to our set of student outcomes by estimating a variation of equation (1) :

This multi-level model includes the same set of control variables as above in order to account for the non-random sorting of students to teachers and for factors beyond teachers’ control that might influence each of our outcomes. We further included a vector of their teacher j ’s observation scores, OBSER VAT ^ ION l J , − t . The coefficients on these variables are our main parameters of interest and can be interpreted as the change in standard deviation units for each outcome associated with exposure to teaching practice one standard deviation above the mean.

One concern when relating observation scores to student survey outcomes is that they may capture the same behaviors. For example, teachers may receive credit on the Classroom Organization domain when their students demonstrate orderly behavior. In this case, we would have the same observed behaviors on both the left and right side of our equation relating instructional quality to student outcomes, which would inflate our teaching effect estimates. A related concern is that the specific students in the classroom may influence teachers’ instructional quality ( Hill et al., 2015 ; Steinberg & Garrett, 2016 ; Whitehurst, Chingos, & Lindquist, 2014 ). While the direction of bias is not as clear here – as either lesser- or higher-quality teachers could be sorted to harder to educate classrooms – this possibility also could lead to incorrect estimates. To avoid these sources of bias, we only included lessons captured in years other than those in which student outcomes were measured, denoted by – t in the subscript of OBSER VAT ^ ION l J , − t . To the extent that instructional quality varies across years, using out-of-year observation scores creates a lower-bound estimate of the true relationship between instructional quality and student outcomes. We consider this an important tradeoff to minimize potential bias. We used predicted shrunken observation score estimates that account for the fact that teachers contributed different numbers of lessons to the project, and fewer lessons could lead to measurement error in these scores ( Hill, Charalambous, & Kraft, 2012 ). 11

An additional concern for identification is the endogeneity of observed classroom quality. In other words, specific teaching practices are not randomly assigned to teachers. Our preferred analytic approach attempted to account for potential sources of bias by conditioning estimates of the relationship between one dimension of teaching practice and student outcomes on the three other dimensions. An important caveat here is that we only observed teachers’ instruction during math lessons and, thus, may not capture important pedagogical practices teachers used with these students when teaching other subjects. Including dimensions from the CLASS instrument, which are meant to capture instructional quality across subject areas ( Pianta & Hamre, 2009 ), helps account for some of this concern. However, given that we were not able to isolate one dimension of teaching quality from all others, we consider this approach as providing suggestive rather than conclusive evidence on the underlying causal relationship between teaching practice and students’ attitudes and behaviors.

4.3. Estimating the Relationship Between Teacher Effects Across Multiple Student Outcomes

In our third and final set of analyses, we examined whether teachers who are effective at raising math test scores are equally effective at developing students’ attitudes and behaviors. To do so, we drew on equation (1) to estimate µ̂ j for each outcome and teacher j . Following Chetty et al., 2014 ), we use post-hoc predicted “shrunken” empirical Bayes estimates of µ̂ j derived from equation (1) . Then, we generated a correlation matrix of these teacher effect estimates.

Despite attempts to increase the precision of these estimates through empirical Bayes estimation, estimates of individual teacher effects are measured with error that will attenuate these correlations ( Spearman, 1904 ). Thus, if we were to find weak to moderate correlations between different measures of teacher effectiveness, this could identify multidimensionality or could result from measurement challenges, including the reliability of individual constructs ( Chin & Goldhaber, 2015 ). For example, prior research suggests that different tests of students’ academic performance can lead to different teacher rankings, even when those tests measure similar underlying constructs ( Lockwood et al., 2007 ; Papay, 2011 ). To address this concern, we focus our discussion on relative rankings in correlations between teacher effect estimates rather than their absolute magnitudes. Specifically, we examine how correlations between teacher effects on two closely related outcomes (e.g., two math achievement tests) compare with correlations between teacher effects on outcomes that aim to capture different underlying constructs. In light of research highlighted above, we did not expect the correlation between teacher effects on the two math tests to be 1 (or, for that matter, close to 1). However, we hypothesized that these relationships should be stronger than the relationship between teacher effects on students’ math performance and effects on their attitudes and behaviors.

5.1. Do Teachers Impact Students’ Attitudes and Behaviors?

We begin by presenting results of the magnitude of teacher effects in Table 4 . Here, we observe sizable teacher effects on students’ attitudes and behaviors that are similar to teacher effects on students’ academic performance. Starting first with teacher effects on students’ academic performance, we find that a one standard deviation difference in teacher effectiveness is equivalent to a 0.17 sd or 0.18 sd difference in students’ math achievement. In other words, relative to an average teacher, teachers at the 84 th percentile of the distribution of effectiveness move the medium student up to roughly the 57 th percentile of math achievement. Notably, these findings are similar to those from other studies that also estimate within-school teacher effects in large administrative datasets ( Hanushek & Rivkin, 2010 ). This suggests that our use of school fixed effects with a more limited number of teachers observed within a given school does not appear to overly restrict our identifying variation. In Online Appendix A , where we present the magnitude of teacher effects from alternative model specifications, we show that results are robust to models that exclude school fixed effects or replace school fixed effects with observable school characteristics. Estimated teacher effects on students’ self-reported Self-Efficacy in Math and Behavior in Class are 0.14 sd and 0.15 sd, respectively. The largest teacher effects we observe are on students’ Happiness in Class , of 0.31 sd. Given that we do not have multiple years of data to separate out class effects for this measure, we interpret this estimate as the upward bound of true teacher effects on Happiness in Class. Rescaling this estimate by the ratio of teacher effects with and without class effects for Self-Efficacy in Math (0.14/0.19 = 0.74; see Online Appendix A ) produces an estimate of stable teacher effects on Happiness in Class of 0.23 sd, still larger than effects for other outcomes.

Teacher Effects on Students' Academic Performance, Attitudes, and Behaviors

Notes: Cells contain estimates from separate multi-level regression models.

All effects are statistically significant at the 0.05 level.

5.2. Do Specific Teaching Practices Impact Students’ Attitudes and Behaviors?

Next, we examine whether certain characteristics of teachers’ instructional practice help explain the sizable teacher effects described above. We present unconditional estimates in Table 5 Panel A, where the relationship between one dimension of teaching practice and student outcomes is estimated without controlling for the other three dimensions. Thus, cells contain estimates from separate regression models. In Panel B, we present conditional estimates, where all four dimensions of teaching quality are included in the same regression model. Here, columns contain estimates from separate regression models. We present all estimates as standardized effect sizes, which allows us to make comparisons across models and outcome measures. Unconditional and conditional estimates generally are quite similar. Therefore, we focus our discussion on our preferred conditional estimates.

Teaching Effects on Students' Academic Performance, Attitudes, and Behaviors

In Panel A, cells contain estimates from separate regression models. In Panel B, columns contain estimates from separate regression models, where estimates are conditioned on other teaching practices. All models control for student and class characteristics, school fixed effects, and district-by-grade-by-year fixed effects, and include and teacher random effects. Models predicting all outcomes except for Happiness in Class also include class random effects.

We find that students’ attitudes and behaviors are predicted by both general and content-specific teaching practices in ways that generally align with theory. For example, teachers’ Emotional Support is positively associated with the two closely related student constructs, Self-Efficacy in Math and Happiness in Class . Specifically, a one standard deviation increase in teachers’ Emotional Support is associated with a 0.14 sd increase in students’ Self-Efficacy in Math and a 0.37 sd increase in students’ Happiness in Class . These finding makes sense given that Emotional Support captures teacher behaviors such as their sensitivity to students, regard for students’ perspective, and the extent to which they create a positive climate in the classroom. As a point of comparison, these estimates are substantively larger than those between principal ratings of teachers’ ability to improve test scores and their actual ability to do so, which fall in the range of 0.02 sd and 0.08 sd ( Jacob & Lefgren, 2008 ; Rockoff, Staiger, Kane, & Taylor, 2012 ; Rockoff & Speroni, 2010 ).

We also find that Classroom Organization , which captures teachers’ behavior management skills and productivity in delivering content, is positively related to students’ reports of their own Behavior in Class (0.08 sd). This suggests that teachers who create an orderly classroom likely create a model for students’ own ability to self-regulate. Despite this positive relationship, we find that Classroom Organization is negatively associated with Happiness in Class (−0.23 sd), suggesting that classrooms that are overly focused on routines and management are negatively related to students’ enjoyment in class. At the same time, this is one instance where our estimate is sensitive to whether or not other teaching characteristics are included in the model. When we estimate the relationship between teachers’ Classroom Organization and students’ Happiness in Class without controlling for the three other dimensions of teaching quality, this estimate approaches 0 and is no longer statistically significant. 12 We return to a discussion of the potential tradeoffs between Classroom Organization and students’ Happiness in Class in our conclusion.

Finally, we find that the degree to which teachers commit Mathematical Errors is negatively related to students’ Self-Efficacy in Math (−0.09 sd) and Happiness in Class (−0.18 sd). These findings illuminate how a teacher’s ability to present mathematics with clarity and without serious mistakes is related to their students’ perceptions that they can complete math tasks and their enjoyment in class.

Comparatively, when predicting scores on both math tests, we only find one marginally significant relationship – between Mathematical Errors and the high-stakes math test (−0.02 sd). For two other dimensions of teaching quality, Emotional Support and Ambitious Mathematics Instruction , estimates are signed the way we would expect and with similar magnitudes, though they are not statistically significant. Given the consistency of estimates across the two math tests and our restricted sample size, it is possible that non-significant results are due to limited statistical power. 13 At the same time, even if true relationships exist between these teaching practices and students’ math test scores, they likely are weaker than those between teaching practices and students’ attitudes and behaviors. For example, we find that the 95% confidence intervals relating Classroom Emotional Support to Self-Efficacy in Math [0.068, 0.202] and Happiness in Class [0.162, 0.544] do not overlap with the 95% confidence intervals for any of the point estimates predicting math test scores. We interpret these results as indication that, still, very little is known about how specific classroom teaching practices are related to student achievement in math. 14

In Online Appendix B , we show that results are robust to a variety of different specifications, including (1) adjusting observation scores for characteristics of students in the classroom, (2) controlling for teacher background characteristics (i.e., teaching experience, math content knowledge, certification pathway, education), and (3) using raw out-of-year observation scores (rather than shrunken scores). This suggests that our approach likely accounts for many potential sources of bias in our teaching effect estimates.

5.3. Are Teachers Equally Effective at Raising Different Student Outcomes?

In Table 6 , we present correlations between teacher effects on each of our student outcomes. The fact that teacher effects are measured with error makes it difficult to estimate the precise magnitude of these correlations. Instead, we describe relative differences in correlations, focusing on the extent to which teacher effects within outcome type – i.e., teacher effects on the two math achievement tests or effects on students’ attitudes and behaviors – are similar or different from correlations between teacher effects across outcome type. We illustrate these differences in Figure 1 , where Panel A presents scatter plots of these relationships between teacher effects within outcome type and Panel B does the same across outcome type. Recognizing that not all of our survey outcomes are meant to capture the same underlying construct, we also describe relative differences in correlations between teacher effects on these different measures. In Online Appendix C , we find that an extremely conservative adjustment that scales correlations by the inverse of the square root of the product of the reliabilities leads to a similar overall pattern of results.

Scatter plots of teacher effects across outcomes. Solid lines represent the best-fit regression line.

Correlations Between Teacher Effects on Students' Academic Performance, Attitudes, and Behaviors

Standard errors in parentheses. See Table 4 for sample sizes used to calculate teacher effect estimates. The sample for each correlation is the minimum number of teachers between the two measures.

Examining the correlations of teacher effect estimates reveals that individual teachers vary considerably in their ability to impact different student outcomes. As hypothesized, we find the strongest correlations between teacher effects within outcome type. Similar to Corcoran, Jennings, and Beveridge (2012) , we estimate a correlation of 0.64 between teacher effects on our high- and low-stakes math achievement tests. We also observe a strong correlation of 0.49 between teacher effects on two of the student survey measures, students’ Behavior in Class and Self-Efficacy in Math . Comparatively, the correlations between teacher effects across outcome type are much weaker. Examining the scatter plots in Figure 1 , we observe much more dispersion around the best-fit line in Panel B than in Panel A. The strongest relationship we observe across outcome types is between teacher effects on the low-stakes math test and effects on Self-Efficacy in Math ( r = 0.19). The lower bound of the 95% confidence interval around the correlation between teacher effects on the two achievement measures [0.56, 0.72] does not overlap with the 95% confidence interval of the correlation between teacher effects on the low-stakes math test and effects on Self-Efficacy in Math [−0.01, 0.39], indicating that these two correlations are substantively and statistically significantly different from each other. Using this same approach, we also can distinguish the correlation describing the relationship between teacher effects on the two math tests from all other correlations relating teacher effects on test scores to effects on students’ attitudes and behaviors. We caution against placing too much emphasis on the negative correlations between teacher effects on test scores and effects on Happiness in Class ( r = −0.09 and −0.21 for the high- and low-stakes tests, respectively). Given limited precision of this relationship, we cannot reject the null hypothesis of no relationship or rule out weak, positive or negative correlations among these measures.

Although it is useful to make comparisons between the strength of the relationships between teacher effects on different measures of students’ attitudes and behaviors, measurement error limits our ability to do so precisely. At face value, we find correlations between teacher effects on Happiness in Class and effects on the two other survey measures ( r = 0.26 for Self-Efficacy in Math and 0.21 for Behavior in Class ) that are weaker than the correlation between teacher effects on Self-Efficacy in Math and effects on Behavior in Class described above ( r = 0.49). One possible interpretation of these findings is that teachers who improve students’ Happiness in Class are not equally effective at raising other attitudes and behaviors. For example, teachers might make students happy in class in unconstructive ways that do not also benefit their self-efficacy or behavior. At the same time, these correlations between teacher effects on Happiness in Class and the other two survey measures have large confidence intervals, likely due to imprecision in our estimate of teacher effects on Happiness in Class . Thus, we are not able to distinguish either correlation from the correlation between teacher effects on Behavior in Class and effects on Self-Efficacy in Math .

6. Discussion and Conclusion

6.1. relationship between our findings and prior research.

The teacher effectiveness literature has profoundly shaped education policy over the last decade and has served as the catalyst for sweeping reforms around teacher recruitment, evaluation, development, and retention. However, by and large, this literature has focused on teachers’ contribution to students’ test scores. Even research studies such as the Measures of Effective Teaching project and new teacher evaluation systems that focus on “multiple measures” of teacher effectiveness ( Center on Great Teachers and Leaders, 2013 ; Kane et al., 2013 ) generally attempt to validate other measures, such as observations of teaching practice, by examining their relationship to estimates of teacher effects on students’ academic performance.

Our study extends an emerging body of research examining the effect of teachers on student outcomes beyond test scores. In many ways, our findings align with conclusions drawn from previous studies that also identify teacher effects on students’ attitudes and behaviors ( Jennings & DiPrete, 2010 ; Kraft & Grace, 2016 ; Ruzek et al., 2015 ), as well as weak relationships between different measures of teacher effectiveness ( Gershenson, 2016 ; Jackson, 2012 ; Kane & Staiger, 2012 ). To our knowledge, this study is the first to identify teacher effects on measures of students’ self-efficacy in math and happiness in class, as well as on a self-reported measure of student behavior. These findings suggest that teachers can and do help develop attitudes and behaviors among their students that are important for success in life. By interpreting teacher effects alongside teaching effects, we also provide strong face and construct validity for our teacher effect estimates. We find that improvements in upper-elementary students’ attitudes and behaviors are predicted by general teaching practices in ways that align with hypotheses laid out by instrument developers ( Pianta & Hamre, 2009 ). Findings linking errors in teachers’ presentation of math content to students’ self-efficacy in math, in addition to their math performance, also are consistent with theory ( Bandura et al., 1996 ). Finally, the broad data collection effort from NCTE allows us to examine relative differences in relationships between measures of teacher effectiveness, thus avoiding some concerns about how best to interpret correlations that differ substantively across studies ( Chin & Goldhaber, 2015 ). We find that correlations between teacher effects on student outcomes that aim to capture different underlying constructs (e.g., math test scores and behavior in class) are weaker than correlations between teacher effects on two outcomes that are much more closely related (e.g., math achievement).

6.2. Implications for Policy

These findings can inform policy in several key ways. First, our findings may contribute to the recent push to incorporate measures of students’ attitudes and behaviors – and teachers’ ability to improve these outcomes – into accountability policy (see Duckworth, 2016 ; Miller, 2015 ; Zernike, 2016 for discussion of these efforts in the press). After passage of the Every Student Succeeds Act (ESSA), states now are required to select a nonacademic indicator with which to assess students’ success in school ( ESSA, 2015 ). Including measures of students’ attitudes and behaviors in accountability or evaluation systems, even with very small associated weights, could serve as a strong signal that schools and educators should value and attend to developing these skills in the classroom.

At the same time, like other researchers ( Duckworth & Yeager, 2015 ), we caution against a rush to incorporate these measures into high-stakes decisions. The science of measuring students’ attitudes and behaviors is relatively new compared to the long history of developing valid and reliable assessments of cognitive aptitude and content knowledge. Most existing measures, including those used in this study, were developed for research purposes rather than large-scale testing with repeated administrations. Open questions remain about whether reference bias substantially distorts comparisons across schools. Similar to previous studies, we include school fixed effects in all of our models, which helps reduce this and other potential sources of bias. However, as a result, our estimates are restricted to within-school comparisons of teachers and cannot be applied to inform the type of across-school comparisons that districts typically seek to make. There also are outstanding questions regarding the susceptibility of these measures to “survey” coaching when high-stakes incentives are attached. Such incentives likely would render teacher or self-assessments of students’ attitudes and behaviors inappropriate. Some researchers have started to explore other ways to capture students’ attitudes and behaviors, including objective performance-based tasks and administrative proxies such as attendance, suspensions, and participation in extracurricular activities ( Hitt, Trivitt, & Cheng, 2016 ; Jackson, 2012 ; Whitehurst, 2016 ). This line of research shows promise but still is in its early phases. Further, although our modeling strategy aims to reduce bias due to non-random sorting of students to teachers, additional evidence is needed to assess the validity of this approach. Without first addressing these concerns, we believe that adding untested measures into accountability systems could lead to superficial and, ultimately, counterproductive efforts to support the positive development of students’ attitudes and behaviors.

An alternative approach to incorporating teacher effects on students’ attitudes and behaviors into teacher evaluation may be through observations of teaching practice. Our findings suggest that specific domains captured on classroom observation instruments (i.e., Emotional Support and Classroom Organization from the CLASS and Mathematical Errors from the MQI) may serve as indirect measures of the degree to which teachers impact students’ attitudes and behaviors. One benefit of this approach is that districts commonly collect related measures as part of teacher evaluation systems ( Center on Great Teachers and Leaders, 2013 ), and such measures are not restricted to teachers who work in tested grades and subjects.

Similar to Whitehurst (2016) , we also see alternative uses of teacher effects on students’ attitudes and behaviors that fall within and would enhance existing school practices. In particular, measures of teachers’ effectiveness at improving students’ attitudes and behaviors could be used to identify areas for professional growth and connect teachers with targeted professional development. This suggestion is not new and, in fact, builds on the vision and purpose of teacher evaluation described by many other researchers ( Darling-Hammond, 2013 ; Hill & Grossman, 2013 ; Papay, 2012 ). However, in order to leverage these measures for instructional improvement, we add an important caveat: performance evaluations – whether formative or summative – should avoid placing teachers into a single performance category whenever possible. Although many researchers and policymakers argue for creating a single weighted composite of different measures of teachers’ effectiveness ( Center on Great Teachers and Leaders, 2013 ; Kane et al., 2013 ), doing so likely oversimplifies the complex nature of teaching. For example, a teacher who excels at developing students’ math content knowledge but struggles to promote joy in learning or students’ own self-efficacy in math is a very different teacher than one who is middling across all three measures. Looking at these two teachers’ composite scores would suggest they are similarly effective. A single overall evaluation score lends itself to a systematized process for making binary decisions such as whether to grant teachers tenure, but such decisions would be better informed by recognizing and considering the full complexity of classroom practice.

We also see opportunities to maximize students’ exposure to the range of teaching skills we examine through strategic teacher assignments. Creating a teacher workforce skilled in most or all areas of teaching practice is, in our view, the ultimate goal. However, this goal likely will require substantial changes to teacher preparation programs and curriculum materials, as well as new policies around teacher recruitment, evaluation, and development. In middle and high schools, content-area specialization or departmentalization often is used to ensure that students have access to teachers with skills in distinct content areas. Some, including the National Association of Elementary School Principals, also see this as a viable strategy at the elementary level ( Chan & Jarman, 2004 ). Similar approaches may be taken to expose students to a collection of teachers who together can develop a range of academic skills, attitudes and behaviors. For example, when configuring grade-level teams, principals may pair a math teacher who excels in her ability to improve students’ behavior with an ELA or reading teacher who excels in his ability to improve students’ happiness and engagement. Viewing teachers as complements to each other may help maximize outcomes within existing resource constraints.

Finally, we consider the implications of our findings for the teaching profession more broadly. While our findings lend empirical support to research on the multidimensional nature of teaching ( Cohen, 2011 ; Lampert, 2001 ; Pianta & Hamre, 2009 ), we also identify tensions inherent in this sort of complexity and potential tradeoffs between some teaching practices. In our primary analyses, we find that high-quality instruction around classroom organization is positively related to students’ self-reported behavior in class but negatively related to their happiness in class. Our results here are not conclusive, as the negative relationship between classroom organization and students’ happiness in class is sensitive to model specification. However, if there indeed is a negative causal relationship, it raises questions about the relative benefits of fostering orderly classroom environments for learning versus supporting student engagement by promoting positive experiences with schooling. Our own experience as educators and researchers suggests this need not be a fixed tradeoff. Future research should examine ways in which teachers can develop classroom environments that engender both constructive classroom behavior and students’ happiness in class. As our study draws on a small sample of students who had current and prior-year scores for Happiness in Class , we also encourage new studies with greater statistical power that may be able to uncover additional complexities (e.g., non-linear relationships) in these sorts of data.

Our findings also demonstrate a need to integrate general and more content-specific perspectives on teaching, a historical challenge in both research and practice ( Grossman & McDonald, 2008 ; Hamre et al., 2013 ). We find that both math-specific and general teaching practices predict a range of student outcomes. Yet, particularly at the elementary level, teachers’ math training often is overlooked. Prospective elementary teachers often gain licensure without taking college-level math classes; in many states, they do not need to pass the math sub-section of their licensure exam in order to earn a passing grade overall ( Epstein & Miller, 2011 ). Striking the right balance between general and content-specific teaching practices is not a trivial task, but it likely is a necessary one.

For decades, efforts to improve the quality of the teacher workforce have focused on teachers’ abilities to raise students’ academic achievement. Our work further illustrates the potential and importance of expanding this focus to include teachers’ abilities to promote students’ attitudes and behaviors that are equally important for students’ long-term success.

Supplementary Material

Acknowledgments.

The research reported here was supported in part by the Institute of Education Sciences, U.S. Department of Education, through Grant R305C090023 to the President and Fellows of Harvard College to support the National Center for Teacher Effectiveness. The opinions expressed are those of the authors and do not represent views of the Institute or the U.S. Department of Education. Additional support came from the William T. Grant Foundation, the Albert Shanker Institute, and Mathematica Policy Research’s summer fellowship.

Appendix Table 1

Factor Loadings for Items from the Student Survey

Notes: Estimates drawn from all available data. Loadings of roughly 0.4 or higher are highlighted to identify patterns.

1 Although student outcomes beyond test scores often are referred to as “non-cognitive” skills, our preference, like others ( Duckworth & Yeager, 2015 ; Farrington et al., 2012 ), is to refer to each competency by name. For brevity, we refer to them as “attitudes and behaviors,” which closely characterizes the measures we focus on in this paper.

2 Analyses below include additional subsamples of teachers and students. In analyses that predict students’ survey response, we included between 51 and 111 teachers and between 548 and 1,529 students. This range is due to the fact that some survey items were not available in the first year of the study. Further, in analyses relating domains of teaching practice to student outcomes, we further restricted our sample to teachers who themselves were part of the study for more than one year, which allowed us to use out-of-year observation scores that were not confounded with the specific set of students in the classroom. This reduced our analysis samples to between 47 and 93 teachers and between 517 and 1,362 students when predicting students’ attitudes and behaviors, and 196 teachers and 8,660 students when predicting math test scores. Descriptive statistics and formal comparisons of other samples show similar patterns as those presented in Table 1 .

3 We conducted factor analyses separately by year, given that additional items were added in the second and third years to help increase reliability. In the second and third years, each of the two factors has an eigenvalue above one, a conventionally used threshold for selecting factors ( Kline, 1994 ). Even though the second factor consists of three items that also have loadings on the first factor between 0.35 and 0.48 – often taken as the minimum acceptable factor loading ( Field, 2013 ; Kline, 1994 ) – this second factor explains roughly 20% more of the variation across teachers and, therefore, has strong support for a substantively separate construct ( Field, 2013 ; Tabachnick & Fidell, 2001 ). In the first year of the study, the eigenvalue on this second factor is less strong (0.78), and the two items that load onto it also load onto the first factor.

4 Depending on the outcome, between 4% and 8% of students were missing a subset of items from survey scales. In these instances, we created final scores by averaging across all available information.

5 Coding of items from both the low- and high-stakes tests also identify a large degree of overlap in terms of content coverage and cognitive demand ( Lynch, Chin, & Blazar, 2015 ). All tests focused most on numbers and operations (40% to 60%), followed by geometry (roughly 15%), and algebra (15% to 20%). By asking students to provide explanations of their thinking and to solve non-routine problems such as identifying patterns, the low-stakes test also was similar to the high-stakes tests in two districts; in the other two districts, items often asked students to execute basic procedures.

6 As described by Blazar (2015) , capture occurred with a three-camera, digital recording device and lasted between 45 and 60 minutes. Teachers were allowed to choose the dates for capture in advance and directed to select typical lessons and exclude days on which students were taking a test. Although it is possible that these lessons were unique from a teachers’ general instruction, teachers did not have any incentive to select lessons strategically as no rewards or sanctions were involved with data collection or analyses. In addition, analyses from the MET project indicate that teachers are ranked almost identically when they choose lessons themselves compared to when lessons are chosen for them ( Ho & Kane, 2013 ).

7 Developers of the CLASS instrument identify a third dimension, Classroom Instructional Support . Factor analyses of data used in this study showed that items from this dimension formed a single construct with items from Emotional Support ( Blazar et al., 2015 ). Given theoretical overlap between Classroom Instructional Support and dimensions from the MQI instrument, we excluded these items from our work and focused only on Classroom Emotional Support.

8 We controlled for prior-year scores only on the high-stakes assessments and not on the low-stakes assessment for three reasons. First, including prior low-stakes test scores would reduce our full sample by more than 2,200 students. This is because the assessment was not given to students in District 4 in the first year of the study (N = 1,826 students). Further, an additional 413 students were missing fall test scores given that they were not present in class on the day it was administered. Second, prior-year scores on the high- and low-stakes test are correlated at 0.71, suggesting that including both would not help to explain substantively more variation in our outcomes. Third, sorting of students to teachers is most likely to occur based on student performance on the high-stakes assessments since it was readily observable to schools; achievement on the low-stakes test was not.

9 An alternative approach would be to specify teacher effects as fixed, rather than random, which relaxes the assumption that teacher assignment is uncorrelated with factors that also predict student outcomes ( Guarino, Maxfield, Reckase, Thompson, & Wooldridge, 2015 ). Ultimately, we prefer the random effects specification for three reasons. First, it allows us to separate out teacher effects from class effects by including a random effect for both in our model. Second, this approach allows us to control for a variety of variables that are dropped from the model when teacher fixed effects also are included. Given that all teachers in our sample remained in the same school from one year to the next, school fixed effects are collinear with teacher fixed effects. In instances where teachers had data for only one year, class characteristics and district-by-grade-by-year fixed effects also are collinear with teacher fixed effects. Finally, and most importantly, we find that fixed and random effects specifications that condition on students’ prior achievement and demographic characteristics return almost identical teacher effect estimates. When comparing teacher fixed effects to the “shrunken” empirical Bayes estimates that we employ throughout the paper, we find correlations between 0.79 and 0.99. As expected, the variance of the teacher fixed effects is larger than the variance of teacher random effects, differing by the shrinkage factor. When we instead calculate teacher random effects without shrinkage by averaging student residuals to the teacher level (i.e., “teacher average residuals”; see Guarino et al, 2015 for a discussion of this approach) they are almost identical to the teacher fixed effects estimates. Correlations are 0.99 or above across outcome measures, and unstandardized regression coefficients that retain the original scale of each measure range from 0.91 sd to 0.99 sd.

10 Adding prior survey responses to the education production function is not entirely analogous to doing so with prior achievement. While achievement outcomes have roughly the same reference group across administrations, the surveys do not. This is because survey items often asked about students’ experiences “in this class.” All three Behavior in Class items and all five Happiness in Class items included this or similar language, as did five of the 10 items from Self-Efficacy in Math . That said, moderate year-to-year correlations of 0.39, 0.38, and 0.53 for Self-Efficacy in Math , Happiness in Class , and Behavior in Class , respectively, suggest that these items do serve as important controls. Comparatively, year-to-year correlations for the high- and low-stakes tests are 0.75 and 0.77.

11 To estimate these scores, we specified the following hierarchical linear model separately for each school year: OBSER VAT ^ ION lj , − t = γ j + ε ljt The outcome is the observation score for lesson l from teacher j in years other than t ; γ j is a random effect for each teacher, and ε ljt is the residual. For each domain of teaching practice and school year, we utilized standardized estimates of the teacher-level residual as each teacher’s observation score in that year. Thus, scores vary across time. In the main text, we refer to these teacher-level residual as OBSER VAT ^ ION l J , − t rather than γ ̂ J for ease of interpretation for readers.

12 One explanation for these findings is that the relationship between teachers’ Classroom Organization and students’ Happiness in Class is non-liner. For example, it is possible that students’ happiness increases as the class becomes more organized, but then begins to decrease in classrooms with an intensive focus on order and discipline. To explore this possibility, we first examined the scatterplot of the relationship between teachers’ Classroom Organization and teachers’ ability to improve students’ Happiness in Class . Next, we re-estimated equation (2) including a quadratic, cubic, and quartic specification of teachers’ Classroom Organization scores. In both sets of analyses, we found no evidence for a non-linear relationship. Given our small sample size and limited statistical power, though, we suggest that this may be a focus of future research.

13 In similar analyses in a subset of the NCTE data, Blazar (2015) did find a statistically significant relationship between Ambitious Mathematics Instruction and the low-stakes math test of 0.11 sd. The 95% confidence interval around that point estimate overlaps with the 95% confidence interval relating Ambitious Mathematics Instruction to the low-stakes math test in this analysis. Estimates of the relationship between the other three domains of teaching practice and low-stakes math test scores were of smaller magnitude and not statistically significant. Differences between the two studies likely emerge from the fact that we drew on a larger sample with an additional district and year of data, as well as slight modifications to our identification strategy.

14 When we adjusted p -values for estimates presented in Table 5 to account for multiple hypothesis testing using both the Šidák and Bonferroni algorithms ( Dunn, 1961 ; Šidák, 1967 ), relationships between Emotional Support and both Self-Efficacy in Math and Happiness in Class , as well as between Mathematical Errors and Self-Efficacy in Math remained statistically significant.

Contributor Information

David Blazar, Harvard Graduate School of Education.

Matthew A. Kraft, Brown University.

• Achenbach TM, McConaughy SH, Howell CT. Child/adolescent behavioral and emotional problems: implications of cross-informant correlations for situational specificity. Psychological Bulletin. 1987; 101 (2):213. [ PubMed ] [ Google Scholar ]
• Backes B, Hansen M. Working Paper 146. Washington, D C: National Center for Analysis of Longitudinal in Education Research; 2015. Teach for America impact estimates on nontested student outcomes. Retrieved from http://www.caldercenter.org/sites/default/files/WP&%20146.pdf . [ Google Scholar ]
• Bandura A, Barbaranelli C, Caprara GV, Pastorelli C. Multifaceted impact of self-efficacy beliefs on academic functioning. Child Development. 1996:1206–1222. [ PubMed ] [ Google Scholar ]
• Baron J. Personality and intelligence. In: Sternberg RJ, editor. Handbook of human intelligence. New York: Cambridge University Press; 1982. pp. 308–351. [ Google Scholar ]
• Blazar D. Effective teaching in elementary mathematics: Identifying classroom practices that support student achievement. Economics of Education Review. 2015; 48 :16–29. [ Google Scholar ]
• Blazar D, Braslow D, Charalambous CY, Hill HC. Working Paper. Cambridge, MA: National Center for Teacher Effectiveness; 2015. Attending to general and content-specific dimensions of teaching: Exploring factors across two observation instruments. Retrieved from http://scholar.harvard.edu/files/david_blazar/files/blazar_et_al_attending_to_general_and_content_specific_dimensions_of_teaching.pdf . [ Google Scholar ]
• Borghans L, Duckworth AL, Heckman JJ, Ter Weel B. The economics and psychology of personality traits. Journal of Human Resources. 2008; 43 (4):972–1059. [ Google Scholar ]
• Burchinal M, Howes C, Pianta R, Bryant D, Early D, Clifford R, Barbarin O. Predicting child outcomes at the end of kindergarten from the quality of pre-kindergarten teacher-child interactions and instruction. Applied Developmental Science. 2008; 12 (3):140–153. [ Google Scholar ]
• Center on Great Teachers and Leaders. Databases on state teacher and principal policies. 2013 Retrieved from: http://resource.tqsource.org/stateevaldb .
• Chan TC, Jarman D. Departmentalize elementary schools. Principal. 2004; 84 (1):70–72. [ Google Scholar ]
• Chetty R, Friedman JN, Hilger N, Saez E, Schanzenbach D, Yagan D. How does your kindergarten classroom affect your earnings? Evidence from Project STAR. Quarterly Journal of Economics. 2011; 126 (4):1593–1660. [ PubMed ] [ Google Scholar ]
• Chetty R, Friedman JN, Rockoff JE. Measuring the impacts of teachers I: Evaluating Bias in Teacher Value-Added Estimates. American Economic Review. 2014; 104 (9):2593–2632. [ Google Scholar ]
• Chin M, Goldhaber D. Working Paper. Cambridge, MA: National Center for Teacher Effectiveness; 2015. Exploring explanations for the “weak” relationship between value added and observation-based measures of teacher performance. Retrieved from: http://cepr.harvard.edu/files/cepr/files/sree2015_simulation_working_paper.pdf?m=1436541369 . [ Google Scholar ]
• Cohen DK. Teaching and its predicaments. Cambridge, MA: Harvard University Press; 2011. [ Google Scholar ]
• Corcoran SP, Jennings JL, Beveridge AA. Teacher effectiveness on high- and low-stakes tests. 2012 Unpublished manuscript. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.269.5537&rep=rep1&type=pdf .
• Council of the Great City Schools. Beating the odds: Analysis of student performance on state assessments results from the 2012–2013 school year. Washington, DC: Author; 2013. [ Google Scholar ]
• Darling-Hammond L. Getting teacher evaluation right: What really matters for effectiveness and improvement. New York: Teachers College Press; 2013. [ Google Scholar ]
• Diener E. Subjective well-being: The science of happiness and a proposal for a national index. American Psychologist. 2000; 55 (1):34–43. [ PubMed ] [ Google Scholar ]
• Downer JT, Rimm-Kaufman S, Pianta RC. How do classroom conditions and children's risk for school problems contribute to children's behavioral engagement in learning? School Psychology Review. 2007; 36 (3):413–432. [ Google Scholar ]
• Duckworth A. Don’t grade schools on grit. The New York Times. 2016 Mar 26; Retrieved from http://www.nytimes.com/2016/03/27/opinion/sunday/dont-grade-schools-on-grit.html .
• Duckworth AL, Peterson C, Matthews MD, Kelly DR. Grit: Perseverance and passion for long-term goals. Journal of Personality and Social Psychology. 2007; 92 (6):1087–1101. [ PubMed ] [ Google Scholar ]
• Duckworth AL, Quinn PD, Tsukayama E. What No Child Left Behind leaves behind: The roles of IQ and self-control in predicting standardized achievement test scores and report card grades. Journal of Educational Psychology. 2012; 104 (2):439–451. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Duckworth AL, Yeager DS. Measurement matters: Assessing personal qualities other than cognitive ability for educational purposes. Educational Researcher. 2015; 44 (4):237–251. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Dunn OJ. Multiple comparisons among means. Journal of the American Statistical Association. 1961; 56 (293):52–64. [ Google Scholar ]
• Epstein D, Miller RT. Slow off the mark: Elementary school teachers and the crisis in science, technology, engineering, and math education. Washington, DC: Center for American Progress; 2011. [ Google Scholar ]
• The Every Student Succeeds Act. Public Law 114-95, 114th Cong., 1st sess. 2015 Dec 10; available at https://www.congress.gov/bill/114th-congress/senate-bill/1177/text .
• Farrington CA, Roderick M, Allensworth E, Nagaoka J, Keyes TS, Johnson DW, Beechum NO. Teaching adolescents to become learners: The role of non-cognitive factors in shaping school performance, a critical literature review. Chicago: University of Chicago Consortium on Chicago School Reform; 2012. [ Google Scholar ]
• Field A. Discovering statistics using IBM SPSS statistics. 4. London: SAGE publications; 2013. [ Google Scholar ]
• Gershenson S. Linking teacher quality, student attendance, and student achievement. Education Finance and Policy. 2016; 11 (2):125–149. [ Google Scholar ]
• Goodman R. Psychometric properties of the strengths and difficulties questionnaire. Journal of the American Academy of Child & Adolescent Psychiatry. 2001; 40 (11):1337–1345. [ PubMed ] [ Google Scholar ]
• Grossman P, McDonald M. Back to the future: Directions for research in teaching and teacher education. American Educational Research Journal. 2008; 45 :184–205. [ Google Scholar ]
• Guarino CM, Maxfield M, Reckase MD, Thompson PN, Wooldridge JM. An evaluation of Empirical Bayes’ estimation of value-added teacher performance measures. Journal of Educational and Behavioral Statistics. 2015; 40 (2):190–222. [ Google Scholar ]
• Hafen CA, Hamre BK, Allen JP, Bell CA, Gitomer DH, Pianta RC. Teaching through interactions in secondary school classrooms: Revisiting the factor structure and practical application of the classroom assessment scoring system–secondary. The Journal of Early Adolescence. 2015; 35 (5–6):651–680. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Hamre B, Hatfield B, Pianta R, Jamil F. Evidence for general and domain-specific elements of teacher–child interactions: Associations with preschool children's development. Child Development. 2014; 85 (3):1257–1274. [ PubMed ] [ Google Scholar ]
• Hamre BK, Pianta RC. Early teacher–child relationships and the trajectory of children's school outcomes through eighth grade. Child Development. 2001; 72 (2):625–638. [ PubMed ] [ Google Scholar ]
• Hamre BK, Pianta RC, Downer JT, DeCoster J, Mashburn AJ, Jones SM, Brackett MA. Teaching through interactions: Testing a developmental framework of teacher effectiveness in over 4,000 classrooms. The Elementary School Journal. 2013; 113 (4):461–487. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Hanushek EA, Rivkin SG. Generalizations about using value-added measures of teacher quality. American Economic Review. 2010; 100 (2):267–271. [ Google Scholar ]
• Hickman JJ, Fu J, Hill HC. Technical report: Creation and dissemination of upper-elementary mathematics assessment modules. Princeton, NJ: Educational Testing Service; 2012. [ Google Scholar ]
• Hill HC, Blazar D, Lynch K. Resources for teaching: Examining personal and institutional predictors of high-quality instruction. AERA Open. 2015; 1 (4):1–23. [ Google Scholar ]
• Hill HC, Blunk ML, Charalambous CY, Lewis JM, Phelps GC, Sleep L, Ball DL. Mathematical knowledge for teaching and the mathematical quality of instruction: An exploratory study. Cognition and Instruction. 2008; 26 (4):430–511. [ Google Scholar ]
• Hill HC, Charalambous CY, Kraft MA. When rater reliability is not enough teacher observation systems and a case for the generalizability study. Educational Researcher. 2012; 41 (2):56–64. [ Google Scholar ]
• Hill HC, Grossman P. Learning from teacher observations: Challenges and opportunities posed by new teacher evaluation systems. Harvard Educational Review. 2013; 83 (2):371–384. [ Google Scholar ]
• Hill HC, Schilling SG, Ball DL. Developing measures of teachers’ mathematics knowledge for teaching. Elementary School Journal. 2004; 105 :11–30. [ Google Scholar ]
• Hitt C, Trivitt J, Cheng A. When you say nothing at all: The predictive power of student effort on surveys. Economics of Education Review. 2016; 52 :105–119. [ Google Scholar ]
• Ho AD, Kane TJ. The reliability of classroom observations by school personnel. Seattle, WA: Measures of Effective Teaching Project, Bill and Melinda Gates Foundation; 2013. [ Google Scholar ]
• Jackson CK. NBER Working Paper No. 18624. Cambridge, MA: National Bureau for Economic Research; 2012. Non-cognitive ability, test scores, and teacher quality: Evidence from ninth grade teachers in North Carolina. [ Google Scholar ]
• Jacob BA, Lefgren L. Can principals identify effective teachers? Evidence on subjective performance evaluation in education. Journal of Labor Economics. 2008; 20 (1):101–136. [ Google Scholar ]
• Jennings JL, DiPrete TA. Teacher effects on social and behavioral skills in early elementary school. Sociology of Education. 2010; 83 (2):135–159. [ Google Scholar ]
• John OP, Srivastava S. The Big Five trait taxonomy: History, measurement, and theoretical perspectives. Handbook of personality: Theory and research. 1999; 2 (1999):102–138. [ Google Scholar ]
• Kane TJ, McCaffrey DF, Miller T, Staiger DO. Have we identified effective teachers? Validating measures of effective teaching using random assignment. Seattle, WA: Measures of Effective Teaching Project, Bill and Melinda Gates Foundation; 2013. [ Google Scholar ]
• Kane TJ, Staiger DO. Gathering feedback for teaching. Seattle, WA: Measures of Effective Teaching Project, Bill and Melinda Gates Foundation; 2012. [ Google Scholar ]
• King RB, McInerney DM, Ganotice FA, Villarosa JB. Positive affect catalyzes academic engagement: Cross-sectional, longitudinal, and experimental evidence. Learning and Individual Differences. 2015; 39 :64–72. [ Google Scholar ]
• Kline P. An easy guide to factor analysis. London: Routledge; 1994. [ Google Scholar ]
• Kraft MA, Grace S. Working Paper. Providence, RI: Brown University; 2016. Teaching for tomorrow’s economy? Teacher effects on complex cognitive skills and social-emotional competencies. Retrieved from http://scholar.harvard.edu/files/mkraft/files/teaching_for_tomorrows_economy_-_final_public.pdf . [ Google Scholar ]
• Koedel C. Teacher quality and dropout outcomes in a large, urban school district. Journal of Urban Economics. 2008; 64 (3):560–572. [ Google Scholar ]
• Ladd HF, Sorensen LC. Working Paper No. 112. Washington, D C: National Center for Analysis of Longitudinal in Education Research; 2015. Returns to teacher experience: Student achievement and motivation in middle school. Retrieved from http://www.caldercenter.org/sites/default/files/WP%20112%20Update_0.pdf . [ Google Scholar ]
• Lampert M. Teaching problems and the problems of teaching. Yale University Press; 2001. [ Google Scholar ]
• Lockwood JR, McCaffrey DF, Hamilton LS, Stecher B, Le V, Martinez JF. The sensitivity of value-added teacher effect estimates to different mathematics achievement measures. Journal of Educational Measurement. 2007; 44 (1):47–67. [ Google Scholar ]
• Luckner AE, Pianta RC. Teacher-student interactions in fifth grade classrooms: Relations with children's peer behavior. Journal of Applied Developmental Psychology. 2011; 32 (5):257–266. [ Google Scholar ]
• Lynch K, Chin M, Blazar D. Working Paper. Cambridge, MA: National Center for Teacher Effectiveness; 2015. Relationship between observations of elementary teacher mathematics instruction and student achievement: Exploring variability across districts. [ Google Scholar ]
• Lyubomirsky S, King L, Diener E. The benefits of frequent positive affect: Does happiness lead to success? Psychological Bulletin. 2005; 131 (6):803–855. [ PubMed ] [ Google Scholar ]
• Mashburn AJ, Pianta RC, Hamre BK, Downer JT, Barbarin OA, Bryant D, Howes C. Measures of classroom quality in prekindergarten and children's development of academic, language, and social skills. Child Development. 2008; 79 (3):732–749. [ PubMed ] [ Google Scholar ]
• Mihaly K, McCaffrey DF, Staiger DO, Lockwood JR. A composite estimator of effective teaching. Seattle, WA: Measures of Effective Teaching Project, Bill and Melinda Gates Foundation; 2013. [ Google Scholar ]
• Miles SB, Stipek D. Contemporaneous and longitudinal associations between social behavior and literacy achievement in a sample of low-income elementary school children. Child Development. 2006; 77 (1):103–117. [ PubMed ] [ Google Scholar ]
• Miller CC. Why what you learned in preschool is crucial at work. The New York Times. 2015 Oct 16; Retrieved from http://www.nytimes.com/2015/10/18/upshot/how-the-modern-workplace-has-become-more-like-preschool.html?_r=0 .
• Moffitt TE, Arseneault L, Belsky D, Dickson N, Hancox RJ, Harrington H, Houts R, Poulton R, Roberts BW, Ross S. A gradient of childhood self-control predicts health, wealth, and public safety. Proceedings of the National Academy of Sciences. 2011; 108 (7):2693–2698. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• National Council of Teachers of Mathematics. Curriculum and evaluation standards for school mathematics. Reston, VA: Author; 1989. [ Google Scholar ]
• National Council of Teachers of Mathematics. Principles to actions: Ensuring mathematical success for all. Reston, VA: Author; 2014. [ Google Scholar ]
• National Governors Association Center for Best Practices. Common core state standards for mathematics. Washington, DC: Author; 2010. [ Google Scholar ]
• Papay JP. Different tests, different answers: The stability of teacher value-added estimates across outcome measures. American Educational Research Journal. 2011; 48 (1):163–193. [ Google Scholar ]
• Papay JP. Refocusing the debate: Assessing the purposes and tools of teacher evaluation. Harvard Educational Review. 2012; 82 (1):123–141. [ Google Scholar ]
• Pianta RC, Hamre BK. Conceptualization, measurement, and improvement of classroom processes: Standardized observation can leverage capacity. Educational Researcher. 2009; 38 (2):109–119. [ Google Scholar ]
• Pianta R, La Paro K, Payne C, Cox M, Bradley R. The relation of kindergarten classroom environment to teacher, family, and school characteristics and child outcomes. Elementary School Journal. 2002; 102 :225–38. [ Google Scholar ]
• Raudenbush SW, Bryk AS. Hierarchical linear models: Applications and data analysis methods. Second. Thousand Oaks, CA: Sage Publications; 2002. [ Google Scholar ]
• Rockoff JE, Speroni C. Subjective and objective evaluations of teacher effectiveness. American Economic Review. 2010:261–266. [ Google Scholar ]
• Rockoff JE, Staiger DO, Kane TJ, Taylor ES. Information and employee evaluation: evidence from a randomized intervention in public schools. American Economic Review. 2012; 102 (7):3184–3213. [ Google Scholar ]
• Ruzek EA, Domina T, Conley AM, Duncan GJ, Karabenick SA. Using value-added models to measure teacher effects on students’ motivation and achievement. The Journal of Early Adolescence. 2015; 35 (5–6):852–882. [ Google Scholar ]
• Segal C. Misbehavior, education, and labor market outcomes. Journal of the European Economic Association. 2013; 11 (4):743–779. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Šidák Z. Rectangular confidence regions for the means of multivariate normal distributions. Journal of the American Statistical Association. 1967; 62 (318):626–633. [ Google Scholar ]
• Spearman C. “General Intelligence,” objectively determined and measured. The American Journal of Psychology. 1904; 15 (2):201–292. [ Google Scholar ]
• Steinberg MP, Garrett R. Classroom composition and measured teacher performance: What do teacher observation scores really measure? Educational Evaluation and Policy Analysis. 2016; 38 (2):293–317. [ Google Scholar ]
• Tabachnick BG, Fidell LS. Using multivariate statistics. 4. New York: Harper Collins; 2001. [ Google Scholar ]
• Todd PE, Wolpin KI. On the specification and estimation of the production function for cognitive achievement. The Economic Journal. 2003; 113 (485):F3–F33. [ Google Scholar ]
• Tremblay RE, Masse B, Perron D, LeBlanc M, Schwartzman AE, Ledingham JE. Early disruptive behavior, poor school achievement, delinquent behavior, and delinquent personality: Longitudinal analyses. Journal of Consulting and Clinical Psychology. 1992; 60 (1):64. [ PubMed ] [ Google Scholar ]
• Tsukayama E, Duckworth AL, Kim B. Domain-specific impulsivity in school-age children. Developmental Science. 2013; 16 (6):879–893. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• U.S. Department of Education. A blueprint for reform: Reauthorization of the elementary and secondary education act. Washington, DC: U.S. Department of Education, Office of Planning, Evaluation and Policy Development; 2010. [ Google Scholar ]
• Usher EL, Pajares F. Sources of self-efficacy in school: Critical review of the literature and future directions. Review of Educational Research. 2008; 78 (4):751–796. [ Google Scholar ]
• West MR, Kraft MA, Finn AS, Martin RE, Duckworth AL, Gabrieli CF, Gabrieli JD. Promise and paradox: Measuring students’ non-cognitive skills and the impact of schooling. Educational Evaluation and Policy Analysis. 2016; 38 (1):148–170. [ Google Scholar ]
• Whitehurst GJ. Hard thinking on soft skills. Brookings Institute; Washington, DC: 2016. Retrieved from http://www.brookings.edu/research/reports/2016/03/24-hard-thinking-soft-skills-whitehurst . [ Google Scholar ]
• Whitehurst GJ, Chingos MM, Lindquist KM. Evaluating teachers with classroom observations: Lessons learned in four districts. Brown Center on Education Policy at the Brookings Institute; Washington, DC: 2014. Retrieved from http://www.brookings.edu/~/media/research/files/reports/2014/05/13-teacher-evaluation/evaluating-teachers-with-classroom-observations.pdf . [ Google Scholar ]
• Wigfield A, Meece JL. Math anxiety in elementary and secondary school students. Journal of Educational Psychology. 1988; 80 (2):210. [ Google Scholar ]
• Zernike K. Testing for joy and grit? Schools nationwide push to measure students’ emotional skills. The New York Times. 2016 Feb 29; Retrieved from http://www.nytimes.com/2016/03/01/us/testing-for-joy-and-grit-schools-nationwide-push-to-measure-students-emotional-skills.html?_r=0 .

REVIEW article

The effect of teacher caring behavior and teacher praise on students’ engagement in efl classrooms.

• School of Foreign Languages, Zhongnan University of Economics and Law, Wuhan, China

The emergent respect for the prominence of engagement in the present education has made it one of the most widespread inquiry issues that it has been regarded as the ultimate target of learning. In the language teaching field, the idea of student activities for learning is intensely rooted in the prevailing standards of effective language learning, which considers language communication and interaction as analytical for language improvement. Moreover, teachers as center of learning process is the most prominent research attention, and teachers play a key role in regulating the education process as well as students’ learning achievement. However, there is an absence of research which have considered teachers’ care and praise among all positive interpersonal behavior and its significant effect on students’ engagement. So, the present review attempts to focus on teacher care and praise, and their effects on student engagement in EFL classrooms. Subsequently, some implications are presented to clarify the practice of teachers, students, teacher educators, and materials developers.

Introduction

In language learning, some students are not motivated enough, so they lose their primary attentiveness that ultimately results in dropping out and quitting without graduation ( Finn and Zimmer, 2012 ), and lack of their engagement has a remarkable role in this way ( Fredricks et al., 2004 ; Ladd and Dinella, 2009 ). That is to say, students give up studying English because they become less engaged; hence, they might lose their initial interest gradually, which can result in dropping out.

Student engagement, as a strategic factor of learner achievement in higher education, has been at the center of the attention of directors, experts, and scholars in the previous decade ( Kahu and Nelson, 2018 ). In language learning, some researchers have paid attention to engagement in the classroom and have been of service to this domain to date ( Philp and Duchesne, 2016 ; Oga-Baldwin, 2019 ). Second language acquisition (SLA) has undertaken a shift toward Positive Psychology (PP; MacIntyre et al., 2019 ), which has fortified studies on engagement, focusing on some vital PP aspects embedded in the heart of positive language learning ( Mercer and Dörnyei, 2020 ; Wang et al., 2021 ).

Engagement is two sides of the coin; one side is disengagement that is what learners do to elude attending to learning tasks, while the other side is the way a student is involved in these tasks ( Lei et al., 2018 ). Engagement arises moderately out of “bright side” precursors, such as teacher care which derives from self-determination theory (SDT; Ryan and Deci, 2017 ). In line with SDT, all learners have a series of three fundamental widespread spiritual needs that is those for autonomy (need to encounter preference and self-authorization in individual’s performance), competence (need to sustain progress and a nous of reflectance in one’s communications with the situation), and relatedness (need to go through deep, approachable, and mutual care within individual’s interactions; Mercer, 2019 ; Reeve et al., 2019 ). The fulfillment of these needs throughout language learning regulates the degree to which learners flourish and show adaptive functioning, namely, inherent motivation and engagement ( Reeve et al., 2018 ). The relationships between teacher and student, which can be associated with learners’ basic emotional needs, are among the levels of encouragement on learner improvement ( Froiland et al., 2019 ; Xie and Derakhshan, 2021 ) and are the outcomes of a continuing interaction between the educator and the learner’s features ( Sabol and Pianta, 2012 ). Relatedness can envisage learner behavioral, emotional, and agentic engagement since good teacher-student relations can boost learners’ participation (behavioral engagement), nurture students’ optimistic outlooks toward the course and its tasks (emotional engagement), provide learners the self-confidence to work on difficult actions (cognitive engagement), and boost learners to speak out concerning their education requirements (agentic engagement; Ruzek et al., 2016 ; Vollet et al., 2017 ).

Student engagement is noteworthy since it can envisage learners’ success or academic advancement ( Ladd and Dinella, 2009 ). Also, student engagement is by some issues, such as teacher support or social experiences that provide teachers with instant feedback and praise on their efforts to inspire learners during the teaching process for assessment determinations ( Reeve, 2012 ). It is maintained that engagement would be the best educational indicator of students’ motivation and its dynamic and flexible features ( Appleton et al., 2006 ) entail that it can be reformed as a result of various intrapersonal and interpersonal ecological elements ( Fredricks et al., 2004 ). Teachers’ interpersonal relationship is the main element in the academic setting that exerts a central effect on students’ engagement ( Jiang and Zhang, 2021 ). Likewise, student engagement is inclined by relative variants, such as learning situations or approaches and techniques utilized by teachers ( Fredricks et al., 2019 ). Some longitudinal research ( Jang et al., 2016 ; Reeve et al., 2018 ) within the SDT framework indicated that modifications in student engagement are affected by their learning milieu and such relation is mutual; when situating in classroom circumstances, this ecological element is hypothesized as their teachers’ diverse appealing practice. In previous theories, student engagement has been proposed to be mutually a procedure and a consequence ( Reschly and Christenson, 2012 ). It might be perceived as an interpersonal development triggered by reciprocal interpersonal interactions ( Pianta et al., 2012 ), while as a consequence, student engagement refers to what learners do in the process of intervention. Furthermore, it is adjudged as a moderator between learners’ academic settings and student consequences ( Appleton et al., 2006 ).

Moreover, the success of language learning in the classroom depends on the teacher, and it is stated that students’ achievement or failure in learning can rely on the efficacy of the teachers ( Luz, 2015 ). Sarter (2012) declared that human emotions have been brought to light recently. Although among the emotions that have been tackled so far, anxiety, depression, and stress have been the most prominent, during two previous decades, positive emotions, like love, pride, hope, and enjoyment, have been brought into view ( MacIntyre and Mercer, 2014 ), as generated by the advent of PP into second language learning ( MacIntyre and Mercer, 2014 ; MacIntyre et al., 2019 ; Wang et al., 2021 ). Correspondingly, there has been growing consideration to the role of emotions in teachers’ lives, and emotion is a crucial element of teaching ( Samier and Schmidt, 2009 ). It has been revealed that most teachers all around the world feel negative in language learning classrooms, so it can be proposed that teachers’ emotions should go beyond emotional issues and should turn into social aspects. Thus, sociology can be considered as an agenda to be aware of the social foundations of teachers’ feelings ( Tsang, 2015 ). Lacking constructive emotions, teachers may not be interested or motivated to develop students’ academic, social, and emotional progress ( Day and Qing, 2009 ). The significant role of positive emotions is assured as it helps to foster students’ emotional powers and wellbeing, and encourages social manners and it organizes the social properties for the students’ achievement in language learning ( Zhang et al., 2019 ). Prosocial behavior is a premeditated action to assist others when it is done intentionally instead of reacting to another’s command or by the expectancy of a reward or reprimand ( Grusec et al., 2011 ). Prosocial manners happen as peers support, care, collaborate, and demonstrate respect for each other, and variations in learners’ prosocial behavior are more receptive to sympathetic interactions and involving students in a caring situation ( Cheon et al., 2018 ).

Furthermore, the relations between teachers and learners and teacher manners can meaningfully influence student engagement ( Groves et al., 2015 ). Through interactions with teachers, the students encounter emotional and attitudinal stability and obtain satisfactory emotional support from their teachers which results in effective learning ( Pekrun and Schutz, 2007 ). As stated by Malaimakuni (2016) , effective teachers must have adequate knowledge of the subject matter and in giving their knowledge to students, they routinely should have noble relational communication. Among numerous issues, which provide emotional support for language learners, the relationship between teacher and learner is prominent which is actualized as the most authoritative tool that teachers have, when trying to cultivate a satisfactory learning setting ( Strachan, 2020 ; Li and Yang, 2021 ; Xie and Derakhshan, 2021 ). Because the teacher-learner relationship is dominant to the satisfaction of learners’ emotional needs, scholars have emphasized its quality and nature ( Pishghadam and Khajavy, 2014 ). This relationship in the classroom is essential for not only teachers’ progress but also students’ progress ( Delos Reyes and Torio, 2020 ). Therefore, they must cooperate together to build worthwhile learning circumstances in which the teacher motivates the formation of such situations by taking on relational performances that are related to students’ positive involvements ( Bolkan et al., 2015 ).

A positive relationship between the teacher and learners may be thoroughly associated with the passions, particularly the positive ones emphasized in PP, that students may face within the route of language learning ( Dewaele et al., 2019 ; McIntyre et al., 2019 ). A positive relationship between teacher and learner is acknowledged by empathy, caring, participation, hope, and esteem, and all examples of teacher positive behaviors investigated to date are teacher care, stroke, immediacy, credibility, simplicity, approval, and praise ( Frisby, 2019 ). It is hypothesized that for increasing student engagement, teachers should be friendly, sympathetic, sociable to students’ distinctiveness, support learners’ independence, and be eager about their careers ( Frisby, 2019 ). To this end, teachers can take on varied roles, such as taking care of their conversation, being cautious about feedback to learners, listening to them, providing inquiries to involve learners, and reconsidering classroom management to control relations ( Mercer and Dörnyei, 2020 ). In academic state, the construct of “care” has been broadly investigated and is evolving as an essential element of successful education ( Velasquez et al., 2013 ; Pishghadam et al., 2019 ). In this situation, caring encompasses presenting emotional provision and venture in the rapport with learners, and it is similar to what individuals do and say in their performances and communications ( Davis et al., 2012 ).

Furthermore, caring has been clarified as those feelings, activities, and thoughts that emanate from an educator’s aspiration to stimulate, help, engage, or motivate their learners ( O’Connor, 2008 ). Concentrating on the mutual nature of this construct, it is claimed that “caring education is the performance that arises from a reciprocal caring relationship between learner and teacher, where learning takes place through modeling, discourse, and approval at the social levels” ( Velasquez et al., 2013 ). Teacher care inspires learner-related capabilities, such as engagement, self-confidence, wellbeing, feeling appreciated, and achievement ( Derakhshan et al., 2019 ; Havik and Westergård, 2020 ).

In addition, praise has been reflected as providing encouragement, self-confidence, and good teacher-learner relationships and it is believed that in educational psychology, teacher praise is an essential basis of support for effective student presentation and an indispensable and influential part of teaching and it is a noteworthy strategy in engaging student in the route of learning and praising students in the class fosters language students’ learning motivation and behaviors ( Guilloteaux and Dörnyei, 2008 ). Praising is a technique to reward students who involve in echoing good behaviors or accomplishing better presentations to take advantage of praise ( Brophy, 2004 ).

Undoubtedly, the reward of the teacher is a type of gratefulness of the work of learners which can be done through phrasing praise proclamations as a statement of educational response and feedback instead of appraisal and assessment ( Brophy, 2004 ). This is congruent with Deci et al. (2001) who pinpointed that verbal rewards should be explanatory more willingly than regulatory since the regulatory types are inclined to challenging motivation. Verbal praise should embrace gratefulness of the students’ presentation because the teacher is acting two things equivalently; he is gratifying learners for their performance while teaching them how to allocate their determinations to their inherent enthusiasm rather than to extrinsic motivations provided by the teacher ( Brophy, 2004 ), and it is evinced that the use of praise brings about inspiring learners of having a feeling of superiority and self-assurance in their abilities and accomplishments. As Firdaus (2015) stated, the use of praise will be influential if the teachers discern about it well and how to employ it. Moreover, Hodgman (2015) claimed that praise can be positive support toward students’ manners and confronts the students in a challenging setting to be involved in the educational inquiries and decrease the learners’ problems. Teacher praise is frequently acclaimed as behavior management preparation, which is maintained by some studies ( Conroy et al., 2008 ; Epstein et al., 2008 ).

Taken together the significance of teacher caring behavior and praise as types of positive interpersonal interactions in language education, on the one hand, and learner engagement, on the other hand, it seems required that investigating the rapport between these two constructs has superiority. Furthermore, the rapport between student engagement and teacher caring behavior and teacher praise has not been much investigated in the language education field thus far. Accordingly, the aim of the present study was to bridge this lacuna by investigating the connection between student engagement and teacher praise and caring behavior in the EFL context.

Student Engagement: Definition and Dimensions

As stated by Dörnyei (2018) , student engagement as a whole relates to involvement in educational tasks and activities. More accurately, engagement can be illuminated as the level of a student’s enthusiastic participation in instructional activities ( Reeve, 2012 ), or a person’s extreme participation in an action ( Reeve et al., 2004 ). Concerning the dimensions of learner engagement, Appleton et al. (2006) utilized the cognitive and emotional modules to measure student engagement. Hart et al. (2011) focused on the three sub-constituents to measure student engagement, namely, emotional, cognitive , and behavioral , and another component which is agentic was added by Reeve (2013) .

The behavioral engagement is elucidated as the noticeable educational presentation and sharing activities and tasks which is evaluated through visible educational act containing: student’s positive behavior; participation; attempt to focus on activities; involvement in class negotiations; contribution in educational and co-curricular tasks; persistence; and resiliency, when confronted with challenging actions ( Khademi Ashkzari et al., 2018 ).

The affective or emotional aspect of engagement relates to the cumulative and permanent degrees of emotions encountered by learners and gains the level of desire learners perceive toward the tertiary knowledge ( Bowden, 2013 ), and this type of engagement evinced through intensified levels of positive emotions during activities, which may be presented through pleasure, superiority, enjoyment, eagerness, and interest ( Klem and Connell, 2004 ). Students who are passionately involved in academic activities are capable of detecting the objective of the tasks and social communications ( Schaufeli et al., 2002 ).

Social engagement examines the links of belongingness shaped between students and their classmates, educational staff, and other pertinent facts in their tertiary practice ( Pekrun and Linnenbrink-Garcia, 2012 ). It engenders feelings of determination, socialization, and association to the tertiary source ( Eldegwy et al., 2018 ) that are noticeable in language learning contexts through collaboration with speakers ( Mercer, 2019 ). Social engagement in the classroom is operationally defined as directions of the learning setting, such as assistance, listening to others, taking part in a class on time, and preserving a sensible teacher-learner power construction ( Pekrun and Linnenbrink-Garcia, 2012 ), while out of the class, it is presented through students’ involvement in groups, where ties are molded with others founded on shared principles, wellbeing, or perseverance ( Wentzel, 2012 ). Students without social engagement are ready to undergo isolation and loneliness bringing about condensed wellbeing ( MacIntyre et al., 2018 ).

Cognitive engagement talks about active mental states and goal-oriented learning strategies that students employ in educational activities during learning developments ( Lei et al., 2018 ). Learners who are cognitively involved reveal a better understanding of educational work through their opinions, theories, and approaches implemented during educational activities ( Khademi Ashkzari et al., 2018 ).

Agentic engagement refers to the learners’ participation in the current teaching that is thoughtful and originated by the student ( Reeve, 2013 ) and this dimension of engagement is close to the other three, as it is also a practical student-originated route to educational development.

Teachers’ Positive Behaviors

Teacher caring behavior.

Caring is a passion, a connection, and a behavioral sign that can be theorized as an emotion, an inspiration, and/or behavior, displaying an apprehension about other individual’s emotional states and desires ( Mayseless, 2015 ). Teacher care refers to teachers’ performances to fulfill students’ spiritual and passionate desires through running a positive, caring, and nurturing setting ( Laletas and Reupert, 2016 ). In the educational setting, teacher care represents a noteworthy facet of teacher-student interpersonal relationships ( Gasser et al., 2018 ) and teacher care affects teachers’ establishment of support to students, demonstrating awareness in students’ learning ( Gabryś-Barker, 2016 ). Caring was hypothesized to be an essential component for generating and preserving influential teacher-student interactions ( Noddings, 2006 ), permitting teachers to concede and react to their students’ desires and provide them with safety and care ( Mayseless, 2015 ). It has been proposed that caring is advantageous for both the care receiver and the care provider, as it stimulates the care provider’s joy, pleasure, self-assessment, social relations, and ties between them ( Lavy and Bocker, 2018 ). In fact, teachers can stimulate the positive emotions of learners by involving them in meaningful tasks, providing a milieu that boosts their contribution in classroom negotiations, and presenting empathy ( Gedzune, 2015 ). Some issues related to students, such as engagement, self-confidence, wellbeing, and achievement, are encouraged by teacher care ( Derakhshan et al., 2019 ; Lavy and Naama-Ghanayim, 2020 ).

Teacher Praise

Baumeister et al. (1990) as cited in Abbasi et al. (2015) declared that praise is encouraging interpersonal feedback . Positive feedback is categorized as a dynamic element in nurturing learners’ educational success and strengthening the preferred classroom behavior. Nicols (1995) as cited in Abbasi et al. (2015) pinpointed that positive feedback is perceived as an attractive corresponding that is in line with the learner’s self-image. Praise is generally regarded as positive feedback since it has the same meaning as it makes students feeling reinforced and meaningful and praise can be universal or specific ( Moffat, 2011 ). The former refers to as behavior-specific praise ( Hawkins and Heflin, 2011 ), while the latter type of praise is a well-organized and constructive educational tactic that can surge an extensive range of proper behaviors ( Jenkins et al., 2015 ). Teacher praise is a manifestation of support or appreciation that goes further than feedback for an accurate reaction ( Reinke et al., 2007 ). Teacher praise is regarded as a classroom strategy as dependent or a result of suitable student behaviors. In academic settings, praise should be associated with the performances or skills that the teacher desires to develop ( Partin et al., 2009 ). Praise makes the students feel respectable, and it increases student-teacher relations through constructing a positive learning setting, diminishes troubles in the classroom, and makes learning promising ( Rathel et al., 2014 ). To develop student engagement and success, teachers use praise regularly to reassure suitable behavior, while it reduces problematic behaviors in the classroom ( Reinke et al., 2007 ).

Empirical Studies

The teacher-student interactions, which occur through supportive and approachable relationships in addition to positive and promising behaviors of teachers toward students, affect foreign language satisfaction ( Pishghadam et al., 2021 ). As stated by Mercer and Dörnyei (2020) , and Li et al. (2018) , teachers and some of their features, such as care, respect, helpfulness, and positive attitude, seem to be among the factors that play a prominent role in foreign language interest. When the positive teacher-student interactions are shaped, learners’ motivation, learning achievement, and engagement are developed ( Henry and Thorsen, 2018 ). The results of the study by Royer et al. (2019) about the role of teacher praise in educational situations proved the declines of unsuitable behaviors. Teacher praise is spontaneously associated with the eminence of the student-teacher relations as Cook et al. (2018) indicated that providing praise to students can support the improvement of positive relations with learners. In the same vein, Epstein et al. (2008) acknowledged teacher praise as one of the operational approaches that support student performance and involvement and consequently undergo social and behavioral accomplishment. Rahimi and Karkami (2015) stated that teachers commonly use reward strategies in general and praise, in particular, to elude reprimand and violence strategies since these types of strategies have a destructive impact on their motivation and commitment. The study conducted by Awang et al. (2013) indicated that teachers praise is a common management strategy that is used in the classroom to manage behavior and upsurge student learning engagement in the classroom.

While there are quite a few empirical researches on Positive Psychology worldwide, there is a relatively small number of researches on Positive Psychology in China. Li (2020) has hosted a column in Journal of the Foreign Language World , one of the top linguistic journals in China, featuring the study of emotions in SLA. In this column, Dewaele and Li (2020) contributed a critical review on the previous theories and practices in emotion studies in SLA, proposing that the future of emotion studies can be combined with the control-value theory from the perspective of educational Positive Psychology. The next three empirical studies in the column echo with this proposal. Han and Xu (2020) investigated cases of EFL college students’ academic emotions after receiving written corrective feedback in learning second language writing and their emotion-oriented‚appraisal-oriented‚and situation-oriented self-regulation strategies. The study has generated implications for using Positive Psychology to facilitate students’ wellbeing. Another empirical study conducted by Jiang (2020) used focused essay technique to examine teacher-related factors in affecting EFL classroom enjoyment. Jiang’s research has implications for promoting Positive Psychology in China’s EFL classrooms. The last empirical research article by Li (2020) is also conducted in the realm of Positive Psychology. The method of questionnaire and self-rating test is used to investigate students’ emotional intelligence, emotions, and their relationship with English achievement. Emotions, such as enjoyment, anxiety, and burnout, exert influence on students’ emotional intelligence in general. Emotions and EI have correlations with English achievement. Li’s (2020) research offers a unique perspective of understanding emotion intervention in L2 pedagogy. This column has demonstrated a variety of research methodologies and perspectives, covering a wide range of emotions in EFL learning, such as enjoyment and emotional intelligence, and has implications for using Positive Psychology in EFL setting.

Li’s research interest remains in Positive Psychology of SLA. Li (2021) critically reviewed the researches in PP from the past to the present, advocating that the conception of positive language education will promote language learning emotions as well as the wellbeing of the students. Positive Psychology in SLA has attracted research interest not only in China, but also in worldwide. Empirical studies are still in urgent need to investigate the role of PP in language teaching and learning.

Implications and Future Directions

The current review may have some implications for researchers, teachers, and teacher educators in the EFL context. From the operational viewpoint, developing the interrelations of teacher and student features in the EFL milieu can be significant in developing learner engagement. Likewise, this study can be of help to the language teacher in search of ways to improve student engagement.

This review can help teachers to be acquainted with the status of some individual aspects like teacher caring behavior and praise in inspiring positive results concerning student engagement. Thus, teachers and teacher trainers keen on increasing the positive upshots of EFL classes can meditate on the findings of this study and make enhancements in their works. Based on the low degrees of learner engagement, it is necessary for teachers to scrutinize methods to enthusiastically involve learners in the classroom ( Nguyen et al., 2018 ). Teachers evinced that distractions, rebellion, and disengagement are among the most reliably demanding and unsatisfying manners with which they face in their life ( Alter et al., 2013 ). Learner engagement is promoted and nurtured with the mastery of the use of motivating teaching behaviors ( Nicholson and Putwain, 2018 ). More precisely, the teaching behaviors should embrace implementing great levels of relatedness care from the outset and teachers need to engross learners in the syllabus with learning tasks, while witnessing the learners with endurance and providing regulation with positive feedback, namely, praise and support during interventions. Based on the literature review, the authors concluded that teachers’ classroom management and learner engagement, and the relations between learner and teacher are significantly integrated.

Teacher praise is a widespread classroom-managing approach that successfully impacts student learning ( Floress et al., 2017 ). Praise is an active and concrete policy that is employed to surge learners’ prosocial behaviors ( Dufrene et al., 2014 ). Teacher praise and overt inspiration can also be salient for constructing students’ self-confidence ( Dweck, 2007 ). Assisting teachers to utilize praise in the classrooms is prominent as it can prevent student problems. However, the fact that several teachers do not logically arranged for more positive than negative in their classrooms ( Reinke et al., 2013 ; Derakhshan et al., 2021 ) specifies that it is required to conduct further study to investigate what teaching approaches and types of praise will result in successful teacher praise. Undoubtedly, having a more detailed perception of how praise functions in EFL classrooms will assist all learners to be efficacious in the EFL classroom. Although the significant effect of teacher praise is certified in language learning, studying the kinds of praise can be most efficient will be worthwhile in evolving proper proficient progress for teachers in further studies.

Teachers can encourage positive relations through activities that convey hope, compassion, and care and in which they identify the independence and individuality of students ( Gkonou and Mercer, 2018 ). All learners have strong points, and it can be essential for them to be able to ascertain these and use them ( Mercer, 2019 ). Teacher care speaks of teacher-originated actions that cultivate positive social ties with learners which demands sustaining a classroom setting in which the learners feel appreciated and are simultaneously respectful of the teacher as the power character ( Ware, 2006 ). The caring relation constructed between teacher and student through interactions appeared to manage their conception and creations of themselves. When learners feel that the teacher is caring for them, they become more self-confident and regard themselves as superior learners. Sequentially, for the teachers, students’ mutuality permitted them to perceive the positive effect of their caring for most learners leading to their engagement in the process of learning. Teacher caring behavior has been related to a widespread series of positive results comprising higher presence, enhanced academic success, and decreased drop-out proportion ( Foster, 2008 ).

Additionally, material developers can take advantage of this route of study by considering them when adjusting teacher and learner books. In the same vein, syllabus designers are supposed to reflect effective teacher-student relations as a basis of learning to design tasks and activities in a way to uphold teacher-student negotiations and interactions to undertake tasks and engage them. However, there is an absence of inquiries on how teacher’s positive behaviors, such as teacher praise and caring behavior, can be enhanced in the training courses to be efficient in engaging learners and further consideration should be given to different dimensions of engagement.

Author Contributions

The author confirms being the sole contributor of this work and has approved it for publication.

This study is sponsored by the China Postdoctoral Science Foundation (Project No. 2018M642877) and MOE (Ministry of Education in China) Project of Humanities and Social Sciences (Project No. 18YJC740088).

Conflict of Interest

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Abbasi, A., Ghanbari, B., and Zare, M. H. (2015). The effect of teachers’ individual verbal feedback and praise on EFL learners’ motivation and attitude. Int. J. Recent Adv. Multidiscip. Res. 2, 822–831. Available at: http://ijramr.com/sites/default/files/issues-pdf/395.pdf

Google Scholar

Alter, P., Walker, J. N., and Landers, E. (2013). Teachers’ perceptions of students’ challenging behavior and the impact of teacher demographics. Educ. Treat. Child. 36, 51–69. doi: 10.1353/etc.2013.0040

CrossRef Full Text | Google Scholar

Appleton, J. J., Christenson, S. L., Kim, D., and Reschly, A. L. (2006). Measuring cognitive and psychological engagement: Validation of the student engagement instrument. J. Sch. Psychol. 44, 427–445. doi: 10.1016/j.jsp.2006.04.002

Awang, M. M., Ahmad, A. R., Wahab, J. L. A., and Mamat, N. (2013). Effective teaching strategies to encourage learning behaviour. IOSR J. Humanit. Soc. Sci. 8, 35–40. doi: 10.9790/0837-0823540

Baumeister, R. F., Hutton, D. G., and Cairns, K. J. (1990). Negative effects of praise on skilled performance. Basic and Applied Social Psychology. 11, 131–148. doi: 10.1207/s15324834basp1102_2

Bolkan, S., Goodboy, A. K., and Kelsey, D. M. (2015). Instructor clarity and student motivation: Academic performance as a product of students’ ability and motivation to process instructional material. Commun. Educ. 65, 129–148. doi: 10.1080/03634523.2015.1079329

Bowden, J. L. H. (2013). What’s in a relationship? Asia Pac. J. Mark. Logist. 25, 428–451. doi: 10.1108/APJML-07-2012-0067

Brophy, J. (2004). Motivating Students to Learn. 2nd Edn . Mahwah, NJ: Lawrence Erlbaum.

Cheon, S. H., Reeve, J., and Ntoumanis, N. (2018). A needs-supportive intervention to help PE teachers enhance students’ prosocial behavior and diminish antisocial behavior. Psychol. Sport Exerc. 35, 74–88. doi: 10.1016/j.psychsport.2017.11.010

Conroy, M. A., Sutherland, K. S., Snyder, A. L., and Marsh, S. (2008). Class wide interventions: effective instruction makes a difference. Teach. Except. Child. 40, 24–30. doi: 10.1177/004005990804000603

Cook, C. R., Coco, S., Zhang, Y., Fiat, A. E., Duong, M. T., Renshaw, T. L., et al. (2018). Cultivating positive teacher–student relationships: Preliminary evaluation of the establish–maintain–restore (EMR) method. Sch. Psychol. Rev. 47, 226–243. doi: 10.17105/SPR-2017-0025.V47-3

Day, C., and Qing, G. (2009). “Teacher emotions: Well being and effectiveness,” in Advances in Teacher Emotion Research. eds. P. Schutz and M. Zembylas (Boston, MA: Springer), 15–31.

Davis, H. A., Summers, J. J., and Miller, L. M. (2012). What does it mean for students to be engaged? An interpersonal approach to classroom management: Strategies for improving student engagement (Thousand Oaks, CA: Corwin Press), 21–34. doi: 10.4135/9781483387383.n2

Deci, L., Koester, R., and Ryan, R. M. (2001). Extrinsic rewards and intrinsic motivation in education: reconsidered once again. Rev. Educ. Res. 71, 1–27. doi: 10.3102/00346543071001001

Delos Reyes, R. D. G., and Torio, V. A. G. (2020). The relationship of expert teacher–learner rapport and learner autonomy in the CVIF-dynamic learning program. Asia Pac. Educ. Res. 2, 1–11. doi: 10.1007/s40299-020-00532

Derakhshan, A., Kruk, M., Mehdizadeh, M., and Pawlak, M. (2021). Boredom in online classes in the Iranian EFL context: Sources and solutions. System 101:102556. doi: 10.1016/j.2021.102556

Derakhshan, A., Saeidi, M., and Beheshti, F. (2019). The interplay between Iranian EFL teachers’ conceptions of intelligence, care, feedback, and students’ stroke. IUP J. Eng. Stud. 14, 81–98.doi: 10.22054/ilt.2020.52263.496

Dewaele, J. M., Chen, X., Padilla, A. M., and Lake, J. (2019). The flowering of positive psychology in foreign language teaching and acquisition research. Front. Psychol. 10:2128. doi: 10.3389/fpsyg.2019.02128

PubMed Abstract | CrossRef Full Text | Google Scholar

Dewaele, J. M., and Li, C. (2020). Emotions in second language acquisition: A critical review and research agenda. J. Foreign Lang. World 196, 34–49.

Dörnyei, Z. (2018). Motivating students and teachers. In J. I. Liontas (ed.), TESOL Encycl. Eng. Lang. Teach. , (Hoboken, NJ: Wiley-Blackwell) 4293–4299. doi: 10.1002/9781118784235.eelt0128

Dufrene, B. A., Lestremau, L., and Zoder-Martell, K. (2014). Direct behavioral consultation: Effects on teachers’ praise and student disruptive behavior. Psychol. Sch. 51, 567–580. doi: 10.1002/pits.21768

Dweck, C. S. (2007). The perils and promises of praise. Educ. Leadersh. 65, 34–39.

Eldegwy, A., Elsharnouby, T. H., and Kortam, W. (2018). How sociable is your university brand? An empirical investigation of university social augmenters’ brand equity. Int. J. Educ. Manag. 32, 912–930. doi: 10.1108/IJEM-12-2017-0346

Epstein, M., Atkins, M., Cullinan, D., Kutash, K., and Weaver, K. (2008). Reducing behavior problems in the elementary school classroom. IES Pract. Guide (NCEE 2008-2012). U.S. Department of Education, National Center for Education Statistics. Washington, DC: U.S. Government Printing Office. 20, 12–22.

Finn, J. D., and Zimmer, K. (2012). “Student engagement: What is it? Why does it matter?” in Handbook of Research on Student Engagement. eds. S. L. Christenson, A. L. Reschly, and C. Wylie (New York, NY: Springer), 97–132.

Firdaus, F. H. (2015). Teacher praise and students’engagement in EFL classroom (A case study of seventh grade students at one of junior high school in Bandung). J. Eng. Educ. 3, 28–40.

Floress, M. T., Beschta, S. L., Meyer, K. L., and Reinke, W. M. (2017). Praise research trends and future directions: characteristics and teacher training. Behav. Disord. 43, 227–243. doi: 10.1177/0198742917704648

Foster, K. C. (2008). The transformative potential of teacher care as described by students in a higher education access initiative. Educ. Urban Soc. 41, 104–126. doi: 10.1177/0013124508321591

Fredricks, J. A., Blumenfeld, P. C., and Paris, A. H. (2004). School engagement: potential of the concept, state of the evidence. Rev. Educ. Res. 74, 59–109. doi: 10.3102/00346543074001059

Fredricks, J. A., Parr, A. K., Amemiya, J. L., Wang, M. T., and Brauer, S. (2019). What matters for urban adolescents’ engagement and disengagement in school: a mixed-methods study. J. Adolesc. Res. 34, 491–527. doi: 10.1177/0743558419830638

Frisby, B. N. (2019). The influence of emotional contagion on student perceptions of instructor rapport, emotional support, emotion work, valence, and cognitive learning. Commun. Stud. 70, 492–506. doi: 10.1080/10510974.2019.1622584

Froiland, J. M., Worrell, F. C., and Oh, H. (2019). Teacher–student relationships, psychological need satisfaction, and happiness among diverse students. Psychol. Sch. 56, 856–870. doi: 10.1002/pits.22245

Gabryś-Barker, D. (2016). “Caring and sharing in the foreign language class: on a positive classroom climate,” in Positive Psychology Perspectives on Foreign Language Learning and Teaching. eds. D. Gabryś-Barker and D. Gałajda (New York, NY: Springer), 155–174.

Gasser, L., Grütter, J., Buholzer, A., and Wettstein, A. (2018). Emotionally supportive classroom interactions and students perceptions of their teachers as caring and just. Learn. Instruct. 54, 82–92. doi: 10.1016/j.learninstruc.2017.08.003

Gedzune, G. (2015). Awakening pre-service teachers to children’s social exclusion in the classroom. Discourse Commun. Sustain. Educ. 6, 95–109. doi: 10.1515/dcse-2015-0007

Gkonou, C., and Mercer, S. (2018). “The relational beliefs and practices of highly socio-emotionally competent language teachers,” in Teacher Psychology in SLA. eds. S. Mercer and A. Kostoulas (Bristol: Multilingual Matters), 158–177.

Groves, M., Sellars, C., Smith, J., and Barber, A. (2015). Factors affecting student engagement: a case study examining two cohorts of students attending a post −1992 university in the United Kingdom. Int. J. High. Educ. 4, 27–37. doi: 10.5430/ijhe.v4np27

Grusec, J. E., Hastings, P. D., and Almas, A. (2011). “Helping and prosocial behavior” in Handbook of Child Social Development. eds. C. Hart and P. Smith (Malden, MA: Wiley-Blackwell), 549–566.

Guilloteaux, M. J., and Dörnyei, Z. (2008). Motivating language learners: a classroom-oriented investigation of on student the elects of motivational strategies motivation. TESOL Q. 42, 55–77. doi: 10.1002/j.1545-7249.2008.tb00207.x

Han, Y., and Xu, Y. (2020). Emotional experiences and emotion regulation strategies in second language writing classrooms from the perspective of positive psychology: what can we learn from written corrective feedback situations? J. Foreign Lang. World 1, 50–59.

Hart, S. R., Stewart, K., and Jimerson, S. R. (2011). The student engagement in schools questionnaire and the teacher engagement report form-new: Examining the preliminary evidence. Contemporary school psychology: Formerly. California Sch. Psychol. 15, 67–79. doi: 10.21832/9781783099467-014

Havik, T., and Westergård, E. (2020). Do teachers matter? Students’ perceptions of classroom interactions and student engagement. Scand. J. Educ. Res. 64, 1–20. doi: 10.1080/00313831.2019.1577754

Hawkins, S. M., and Heflin, L. J. (2011). Increasing secondary teachers’ behavior-specific praise using a video self-modeling and visual performance feedback intervention. J. Posit. Behav. Interv. 13, 97–108. doi: 10.1177/1098300709358110

Henry, A., and Thorsen, C. (2018). Teacher-student relationships and L2 motivation. Mod. Lang. J. 102, 218–241. doi: 10.1111/modl.12446

Hodgman, M. R. (2015). Student praise in the modern classroom: the use of praise notes as a productive motivational tool. J. Educ. Train. 2, 41–47. doi: 10.5296/jet.v2i1.6142

Jang, H., Kim, E., and Reeve, J. (2016). Why students become more engaged or more disengaged during the semester: a self-determination theory dual-process model. Learn. Instr. 43, 27–38. doi: 10.1016/j.learninstruc.2016.01.002

Jenkins, L. N., Floress, M. T., and Reinke, W. (2015). Rates and types of teacher praise: a review and future directions. Psychol. Sch. 52, 463–476. doi: 10.1002/pits.21835

Jiang, Y. (2020). An investigation of the effect of teacher on Chinese university students'foreign language enjoyment. J. Foreign Lang. World 196, 60–68.

Jiang, A. L., and Zhang, L. J. (2021). University teachers’ teaching style and their students' argentic engagement in EFL learning in China: a self-determination theory and achievement goal theory integrated perspective. Front. Psychol. 12:704269. doi: 10.3389/fpsyg.2021.704269

Kahu, E. R., and Nelson, K. (2018). Student engagement in the educational interface: understanding the mechanisms of student success. High. Educ. Res. Dev. 37, 58–71. doi: 10.1080/07294360.2017.1344197

Khademi Ashkzari, M., Piryaei, S., and Kamelifar, L. (2018). Designing a causal model for fostering academic engagement and verification of its elect on educational performance. Int. J. Psychol. 12, 136–161. doi: 10.24200/ijpb.2018.58146

Klem, A. M., and Connell, J. P. (2004). Relationships matter: linking teacher support to student engagement and achievement. J. Sch. Health 74, 262–273. doi: 10.1111/j.1746-1561.2004.tb08283.x

Ladd, G. W., and Dinella, L. M. (2009). Continuity and change in early school engagement: predictive of children’s achievement trajectories from first to eighth grade? J. Educ. Psychol. 101, 190–206. doi: 10.1037/a0013153

Laletas, S., and Reupert, A. (2016). Exploring pre-service secondary teachers’ understanding of care. Teachers Teach. 22, 485–503. doi: 10.1080/13540602.2015.1082730

Lavy, S., and Bocker, S. (2018). A path to happiness? A sense of meaning affects relationships, which affect job satisfaction: evidence from two studies of teachers. J. Happiness Stud. 19, 1439–1463. doi: 10.1007/s10902-017-9883-9

Lavy, S., and Naama-Ghanayim, E. (2020). Why care about caring? Linking teachers’ caring and sense of meaning at work with students’ self-esteem, well-being, and school engagement. Teach. Teacher Educ. 91, 1–12. doi: 10.1016/j.tate.2020.103046

Lei, H., Cui, Y., and Zhou, W. (2018). Relationships between student engagement and academic achievement: a meta-analysis. Soc. Behav. Pers. 46, 517–528. doi: 10.2224/sbp.7054

Li, C. (2020). Emotional intelligence and English achievement: The mediating effects of enjoyment‚anxiety and burnout. J. Foreign Lang. World 1, 69–78.

Li, C. (2021). Looking back and looking forward: SLA research from a positive psychology perspective over the past decade (2012-2021). Foreign Lang. Educ. 42, 57–63.

Li, C., Jiang, G., and Dewaele, J.-M. (2018). Understanding Chinese high school students’ foreign language enjoyment: validation of the Chinese version of the foreign language enjoyment scale. System 76, 183–196. doi: 10.1016/j.system.2018.06.004

Li, L., and Yang, S. (2021). Exploring the influence of teacher-student interaction on university students’ self-Efficacy in the flipped classroom. J. Educ. Learn. 10, 84–90. doi: 10.5539/jel.v10n2p84

Luz, F. S. D. R. D. (2015). The Relationship between and Students in the Classroom: Communicative Language Teaching Approach and Cooperative Learning Strategy to Improve Learning. (Master’s thesis) Massachusetts: Bridgewater.

MacIntyre, J. C., Worsley, J., Corcoran, R., Harrison Woods, P., and Bentall, R. P. (2018). Academic and non-academic predictors of student psychological distress: the role of social identity and loneliness. J. Ment. Health 27, 230–239. doi: 10.1080/09638237.2018.1437608

Macintyre, P. D., and Mercer, S. (2014). Introducing positive psychology to SLA. Stud. Second Lang. Learn. Teach. 4, 153–172. doi: 10.14746/ssllt.2014.4.2.2

MacIntyre, P. D., Gregersen, T., and Mercer, S. (2019). Setting an agenda for positive psychology in SLA: theory, practice, and research. Mod. Lang. J. 103, 262–274. doi: 10.1111/modl.12544

Malaimakuni, M. N. (2016). Students’ perception towards English teacher’s interpersonal communication skill at SMP Negeri 3 Kupang. J. Educ. Learn. 10, 382–389. doi: 10.11591/edulearn.v10i4.4168

Mayseless, O. (2015). The Caring Motivation: An Integrated Theory. Oxford, England: Oxford University Press.

Mercer, S. (2019). “Language learner engagement: Setting the scene,” in Second Handbook of English Language Teaching. ed. X. Gao (Basel, Switzerland: Springer), 1–19.

Mercer, S., and Dörnyei, Z. (2020). Engaging Language Learners in Contemporary Classrooms. Cambridge: Cambridge University Press.

Moffat, T. K. (2011). Increasing the teacher rate of behaviour specific praise and its effect on a child with aggressive behaviour problems. Kairaranga 12, 51–58.

Nguyen, T., Cannata, M., and Miller, J. (2018). Understanding student behavioral engagement: importance of student interaction with peers and teachers. J. Educ. Res. 111, 163–174. doi: 10.1080/00220671.2016.1220359

Nicholson, L. J., and Putwain, D. W. (2018). The importance of psychological need satisfaction in educational re-engagement. Res. Pap. Educ. 33, 169–186. doi: 10.1080/02671522.2016.1271004

Nicols, F. W. (1995). Feedback about feedback. Human Resource Development Quarterly, 6, 289–296. Available at: http://home.att.net/~OPSINC/feedback.pdf

Noddings, N. (2006). Principles, feelings and reality. Sch. Field 4, 9–21. doi: 10.1177/1477878506060680

O’Connor, K. E. (2008). You choose to care: teachers, emotions and professional identity. Teach. Teach. Educ. 24, 117–126. doi: 10.1016/j.tate.2006.11.008

Oga-Baldwin, W. Q. (2019). Acting, thinking, feeling, making, collaborating: the engagement process in foreign language learning. System 86, 102–128. doi: 10.1016/j.system.2019.102128

Partin, T. C. M., Robertson, R. E., Maggin, D. M., Oliver, R. M., and Wehby, J. H. (2009). Using teacher praise and opportunities to respond to promote appropriate student behavior. Preven. Sch. Fail. Alter. Educ. Child. Youth 54, 172–178. doi: 10.1080/10459880903493179

Pekrun, R., and Linnenbrink-Garcia, L. (2012). “Academic emotions and student engagement,” in Handbook of Research on Student Engagement. eds. S. L. Christenson, A. L. Reschly, and C. Wylie (New York, NY: Springer), 259–282.

Pekrun, R., and Schutz, P. A. (2007). “Where Do We Go From Here? Implications and Future Directions for Inquiry on Emotions in Education,” in Emotions in Education. eds. P. A. Schutz and R. Pekrun (San Diego: Academic), 313–331.

Philp, J., and Duchesne, S. (2016). Exploring engagement in tasks in the language classroom. Annu. Rev. Appl. Linguist. 36, 50–72. doi: 10.1017/S0267190515000094

Pianta, R. C., Hamre, Β. K., and Allen, J. P. (2012). “Teacher-student relationships and engagement: conceptualizing, measuring, and improving the capacity of classroom interactions,” in Handbook of Research on Student Engagement. eds. S. L. Christenson, A. L. Reschly, and C. Wylie (Boston, MA: Springer), 365–386.

Pishghadam, R., Derakhshan, A., and Zhaleh, K. (2019). The interplay of teacher success, credibility, and stroke with respect to EFL students’ willingness to attend classes. Polish Psychol. Bull. 50, 284–292. doi: 10.24425/ppb.2019.131001

Pishghadam, R., Derakhshan, A., Zhaleh, K., and Al-Obaydi, L. H. (2021). Students’ willingness to attend EFL classes with respect to teachers’ credibility, stroke, and success: a cross-cultural study of Iranian and Iraqi students’ perceptions. Curr. Psychol. , 40, 1–15. doi: 10.1007/s12144-021-01738-z

Pishghadam, R., and Khajavy, G. H. (2014). Development and validation of the student stroke scale and examining its relation with academic motivation. Stud. Educ. Eval. 43, 109–114. doi: 10.1016/j.stueduc.2014.03.004

Rahimi, M., and Karkami, F. H. (2015). The role of teachers' classroom discipline in their teaching effectiveness and students' language learning motivation and achievement: a Path method. Iranian J. Lang. Teach. Res. 3, 57–82.

Rathel, J. M., Drasgow, E., Brown, W. H., and Marshall, K. J. (2014). Increasing induction-level teachers’ positive-tonegative communication ratio and use of behavior-specific praise through e-mailed performance feedback and its effect on students’ task engagement. J. Posit. Behav. Interv. 16, 219–233. doi: 10.1177/1098300713492856

Reeve, J. (2012). “A self-determination theory perspective on student engagement,” in Handbook of Research on Student Engagement. eds. S. L. Christenson, A. L. Reschly, and C. Wylie (New York: Springer), 149–172.

Reeve, J. (2013). How students create motivationally supportive learning environments for themselves: the concept of agentic engagement. J. Educ. Psychol. 105, 579–595. doi: 10.1037/a0032690

Reeve, J., Cheon, S. H., and Jang, H. R. (2019). “A teacher-focused intervention to enhance students’ classroom engagement,” In Fredricks J., A. Reschly, and S. Christenson (eds.), in Handbook of Student Engagement Interventions (London: Academic Press), 87–102.

Reeve, J., Jang, H., Carrell, D., Jeon, S., and Barch, J. (2004). Enhancing students’ engagement by increasing teachers’ autonomy support. Motiv. Emot. 28, 147–169. doi: 10.1023/B:MOEM.0000032312.95499.6f

Reeve, J., Ryan, R. M., and Deci, E. L. (2018). Sociocultural influences on student motivation as viewed through the lens of self-determination theory. Big theories revisited 2, 15–40.

Reinke, W. M., Herman, K. C., and Stormont, M. (2013). Classroom-level positive behavior supports in schools implementing SW-PBIS: identifying areas for enhancement. J. Posit. Behav. Interv. 15, 39–50. doi: 10.1177/1098300712459079

Reinke, W. M., Lewis-Palmer, T., and Martin, E. (2007). The effect of visual performance feedback on teacher use of behavior-specific praise. Behav. Modif. 31, 247–263. doi: 10.1177/0145445506288967

Reschly, A. L., and Christenson, S. L. (2012). “Jingle, jangle, and conceptual haziness: Evolution and future directions of the engagement construct,” in Handbook of Research on Student Engagement. eds. S. L. Christenson, A. L. Reschly, and C. Wylie (New York, NY: Springer), 3–20.

Royer, D. J., Lane, K. L., Dunlap, K. D., and Ennis, R. P. (2019). A systematic review of teacher-delivered behavior-specific praise on K–12 student performance. Remedial Spec. Educ. 40, 112–128. doi: 10.1177/0741932517751054

Ruzek, E. A., Hafen, C. A., Allen, J. P., Gregory, A., Mikami, A. Y., and Pianta, R. C. (2016). How teacher emotional support motivates students: The mediating roles of perceived peer relatedness, autonomy support, and competence. Learn. Instr. 42, 95–103. doi: 10.1016/j.learninstruc.2016.01.004

Ryan, R. M., and Deci, E. L. (2017). Self-Determination Theory: Basic Psychological Needs in Motivation, Development, and Wellness. New York: Guilford.

Sabol, T. J., and Pianta, R. C. (2012). Recent trends in research on teacher–child relationships. Attach Hum. Dev. 14, 213–231. doi: 10.1080/14616734.2012.672262

Samier, E., and Schmidt, M. (2009). Emotional Dimensions of Educational Administration and Leadership. New York, NY: Routledge.

Sarter, H. (2012). “Languages and emotions,” in Applied Psycholinguistics: Positive Effects and Ethical Perspectives. eds. G. Mininni and A. Manuti (Milan, IT: Angeli), 61–73.

Schaufeli, W. B., Salanova, M., González-Romá, V., and Bakker, A. B. (2002). The measurement of engagement and burnout: a two sample confirmatory factor analytic approach. J. Happiness Stud. 3, 71–92. doi: 10.1023/A:1015630930326

Sinatra, G. M., Heddy, B. C., and Lombardi, D. (2014). The challenge of defining and measuring student engagement in science. Educ. Psychol. 50, 1–13. doi: 10.1080/00461520.2014.1002924

Strachan, S. L. (2020). The case for the caring instructor. Coll. Teach. 68, 53–56. doi: 10.1080/87567555.2019.1711011

Tsang, K. K. (2015). Sociological research on teachers’ emotions: four approaches and the shared themes. Sociol. Res. 6, 150–168. doi: 10.5296/jsr.v6i2.8749

Velasquez, A., West, R., Graham, C., and Osguthorpe, R. (2013). Developing caring relationships in schools: a review of the research on caring and nurturing pedagogies. Rev. Educ. 1, 162–190. doi: 10.1002/rev3.3014

Vollet, J. W., Kindermann, T. A., and Skinner, E. A. (2017). In peer matters, teachers matter: peer group influences on students’ engagement depend on teacher involvement. J. Educ. Psychol. 109, 635–652. doi: 10.1037/edu0000172

Ware, F. (2006). Warm demander pedagogy: culturally responsive teaching that supports a culture of achievement for African American students. Urban Educ. 41, 427–456. doi: 10.1177/0042085906289710

Wang, Y., Derakhshan, A., and Zhang, L. J. (2021). Positive psychology in second/foreign language learning and teaching research and practice: past, current and future directions. Front. Psychol. 12, 3512. doi: 10.3389/fpsyg.2021.665175

Wentzel, K. (2012). “Commentary: Sociocultural contexts, social competence, and engagement at school,” in Handbook of Research on Student Engagement. eds. S. L. Christenson, A. L. Reschly, and Y. C. Wylie (New York: Springer), 479–488.

Xie, F., and Derakhshan, A. (2021). A conceptual review of positive teacher interpersonal communication behaviors in the instructional context. Front. Psychol. 12:708490. doi: 10.3389/fpsyg.2021.708490

Zhang, L. J., Thomas, N., and Qin, T. L. (2019). Learning strategy research in system: looking back and looking forward. System 84, 87–93. doi: 10.1016/j.system.2019.06.002

Keywords: teacher caring behavior, teacher praise, students’ engagement, EFL classroom, teacher’s effect on language teaching

Citation: Sun Y (2021) The Effect of Teacher Caring Behavior and Teacher Praise on Students’ Engagement in EFL Classrooms. Front. Psychol . 12:746871. doi: 10.3389/fpsyg.2021.746871

Received: 25 July 2021; Accepted: 11 August 2021; Published: 14 September 2021.

Reviewed by:

Copyright © 2021 Sun. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Yadi Sun, [email protected]

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Lawsuit: Former HCS teacher used dangerous interventions against students before arrest

HORRY COUNTY, SC (WMBF) - The parent of the Horry County student allegedly dragged across the floor by his special education teacher has filed a lawsuit.

The suit against former St. James Intermediate special education teacher Gabriel Hernandez and Horry County Schools was filed on Aug. 14.

Horry County police charged Hernandez with cruelty to children in April 2023 for allegedly dragging the plaintiff’s son, a nonverbal student at St. James Intermediate identified in the lawsuit as John Doe.

PREVIOUS COVERAGE: Warrant: St. James Intermediate special education teacher dragged student across floor

But the parent alleges that wasn’t the first time Hernandez inappropriately touched his son or other students.

STORY CONTINUES BELOW VIDEO

In January 2020, Hernandez started working in the district as a special education teacher at Waccamaw Elementary School.

About a year and a half later, a student at the school claimed Hernandez grabbed and squeezed his neck, making the student place his head down on his desk, according to the lawsuit.

Hernandez then made his first of several transfers to different schools in September 2021 before finally ending up at St. James Intermediate in August 2022, taking over John Doe’s classroom.

During his first month at the school, a paraprofessional working with Hernandez reported to school leaders that Hernandez possibly left a mark on a student’s leg, the lawsuit states.

That same paraprofessional reported Hernandez again in October 2022, when Hernandez allegedly held a student down by their shoulders in the cafeteria with the help of another adult holding the student by the waist.

Hernandez reportedly later told law enforcement this behavior was “not in keeping with CPI training he had received.”

The day after the cafeteria incident, Hernandez stepped on John Doe’s hand, making him wiggle his hand free to escape, according to the lawsuit.

Shortly after, the district placed Hernandez on administrative leave with full pay and benefits.

Around the same time, Hernandez‘s paraprofessional turned in his resignation because of “Hernandez’s persistent inappropriate physical contact with students,” the lawsuit states.

Horry County police began investigating the incident with John Doe but ultimately differed to HCS’ internal investigation.

Besides the paid administrative leave, the district did not discipline Hernandez for the incident with John Doe or any incident prior, the lawsuit claims.

Hernandez was back in the classroom a little over two weeks after being placed on leave and became “more aggressive when dealing with the undesirable behavior of students,” the suit states.

In March 2023, Hernandez allegedly let John Doe bang his head on the table at lunch, something the boy did when he was frustrated.

It wasn’t until another paraprofessional intervened that John Doe stopped banging his head.

The next day, March 16, John Doe wasn’t cooperating with being brought into the classroom, a common behavior for special needs students.

John Doe’s behavior caused Hernandez “to become very agitated,” the suit states.

“According to a paraprofessional who worked with Defendant Hernandez, Defendant Hernandez’s responses to such behavior often escalated the behavior and caused the students to become afraid,” the lawsuit reads.

John Doe began banging his head on a bookshelf, and that’s when Hernandez allegedly dragged the student by the wrists across the room.

Hernandez also is accused of pinning John Doe’s knees against his chest to where the student could not move.

The district placed Hernandez on paid leave again, but after police charged him in April, Hernandez resigned for “personal reasons,” according to the lawsuit.

John Doe’s parent is accusing Hernandez of causing physical and emotional harm to his son.

The parent is also accusing HCS of failing to properly discipline Hernandez.

WMBF News asked for comment on the lawsuit from HCS, and the district said it does not comment on pending litigation.

The parent is asking for actual, consequential and punitive damages in amounts to be determined by a jury.

A jury trial for Hernandez‘s cruelty to children charged is scheduled for Sept. 27, public records show.

Copyright 2024 WMBF. All rights reserved.

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SCHP: Driver killed after car overturns in Marlboro County crash

Man accused of trying to steal fridge from unfinished Horry County home

Missing woman’s remains found near Myrtle Beach home; arrest made

Deputies: Wanted suspect robbed Dollar General at gunpoint in Florence County

NASCAR announces dates for 2025 races at Darlington Raceway, will return to Rockingham