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Engaging students in higher education with educational technology

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• Published: 06 August 2024

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• Mikkel Godsk   ORCID: orcid.org/0000-0002-8332-2712 1 &
• Karen Louise Møller   ORCID: orcid.org/0000-0002-0539-1763 1  

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There is a widespread agenda of improving teaching and learning in higher education by engaging students with educational technology. Based on a large-scale literature review, the article presents 61 specific, research-based recommendations for realising the engagement potential of eight types of educational technologies in higher education. These recommendations can be used, for example, by educators to incorporate specific, available educational technologies into their teaching or as an educational development method to enhance particular forms of student engagement. Based on the evidence, the article points out that some educational technologies have a more documented and sometimes also broader potential to engage the students behaviourally, affectively, and/or cognitively than others and that this likely is related to the extent the technology supports structure, active learning, communication, interaction, and activities on the higher levels on the learning taxonomies.

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1 Introduction

The use of digital educational technology is not a new phenomenon in higher education and gained traction in the early ‘70s in the form of telecourses and the ‘80s in the form of computer-assisted learning and online learning (Garrison, 1985 ). In recent years, technology has received significant attention as a means to support distance education during the COVID-19 pandemic (Abu Talib et al., 2021 ) and as a disruptor of traditional teaching, learning, and assessment forms with the advent of generative artificial intelligence (GenAI) tools such as ChatGPT, Google Gemini, and Dall-E (Farrelly & Baker, 2023 ; Godsk & Elving, 2024 ). Studies show that educational technology has the potential for improving learning outcomes, motivation, engagement, and pass rates (Garrison & Kanuka, 2004 ; Price & Kirkwood, 2011 ; Schindler et al., 2017 ), as well as the business potential for reducing costs, increasing intakes, and increasing student retention (Daniel et al., 2009 ). In higher education in Europe and English-speaking countries, student engagement is often linked to the students’ experience, satisfaction, and learning outcomes, which is why there is a widespread desire to benefit from the technology’s potential to engage students (Payne, 2019 ; Schindler et al., 2017 ). Despite the evidence and interest, universities are struggling to make effective and systematic use of technology to support student engagement (Henrie et al., 2015b ). This may be due to limited systematic evidence on how to engage students with specific educational technologies in terms of practical, concrete recommendations or guidelines, which can be directly applied by educators in their lesson planning or connection with Learning Design processes (Henrie et al., 2015b ; Schindler et al., 2017 ).

1.1 The concept of student engagement and educational technology

The concept of “student engagement” has significantly evolved and expanded within educational research and higher education. Unlike traditional views that mainly focus on observable behaviours and indicators of involvement in educational activities, such as attendance and participation, recent studies adopt broader conceptualisations, analysing how students behave, feel, and think in the context of teaching and learning (Bond et al., 2020 ; Fredricks et al., 2004 ; Henrie et al., 2015a ). This includes aspects like the general student experience and the resultant institutional reputation (Trowler, 2010 ; Wimpenny & Savin-Baden, 2013 ), viewing student engagement as an interconnected and psychosocial process influenced by personal and contextual factors (Kahu, 2013 ), “force-fields” (i.e., driving/resisting forces) for and against intrinsic and extrinsic motivation (Payne, 2019 ), or as described through three dimensions of engagement: behavioural, affective/emotional, and cognitive (Fredricks et al., 2004 ; Newmann et al., 1992 ). These dimensions are sometimes supplemented by additional dimensions such as “the will to succeed” (Kahu, 2013 ), social-behavioural engagement in the context of group work (Linnenbrink-Garcia et al., 2011 ), and student agency (Reeve & Tseng, 2011 ), which other researchers consider unnecessary, as they believe the three existing dimensions already adequately capture these aspects of student engagement (Kahu, 2013 ). These varied conceptualisations also reflect a broader debate between narrow, “mainstream”, and broad, holistic views of student engagement. The narrow view often restricts engagement to specific, measurable behaviours within classroom settings related to an effective learning process (Henrie et al., 2015b ; Zepke, 2015 ), whereas the more broad and holistic view considers engagement as encompassing a wide range of student activities, interactions, and emotions both within and beyond academic environments that contribute to a richer learning experience (Bond et al., 2020 ; Fredricks et al., 2004 ; Henrie et al., 2015b ; Zepke, 2015 ).

In addition, educational technology can involve students in teaching activities that were previously inconceivable (e.g., in virtual reality, simulations, online self-test quizzes, and GenAI-based formative feedback) (Kirkwood & Price, 2014 ; Puentedura, 2010 ; Godsk & Elving, 2024 ) and engagement can be expressed in ways and with indicators that could not previously be observed without technology (Bond & Bedenlier, 2019 ; Fredricks et al., 2004 ). This underscores the importance of not limiting focus to readily observable indicators of student engagement or confining the understanding to just one indicator, as both approaches risk overly simplifying the potential for student engagement. Such narrow focus may also overlook other forms of engagement that are indirectly related or cannot be observed without technology.

In other words, both the general desire to improve students’ learning experiences by engaging them with educational technology and the potential of the technology to engage in numerous ways that are not necessarily observable but interconnected (Payne, 2019 ) advocate for a need to adopt a broad conceptualisation of student engagement. One of the broad and widely used conceptualisations is based on Fredricks et al. ( 2004 ) and Newmann et al.’s ( 1992 ) three perspectives on student engagement and defined by Bond et al. ( 2020 ) in the context of higher education as: “The energy and effort that students employ within their learning community, observable via any number of behavioural, cognitive or affective indicators across a continuum.” (Bond et al., 2020 , p. 2). This conceptualisation extends the narrow behavioural perspective by adding affective and cognitive dimensions, including how students feel and think about their learning experiences, which may significantly affect their engagement (Fredricks et al., 2004 ). “Behavioural engagement” is typically indicated by participation, interaction, involvement, achievement, confidence, and study habits; “affective engagement” or “emotional engagement” is often indicated by positive interaction, enjoyment, attitude, motivation, and enthusiasm; and “cognitive engagement” is typically indicated by peer learning, deep learning, self-regulated learning, positive self-perception, and critical thinking (Bond et al., 2020 ; Fredricks et al., 2004 ). This breadth of Fredricks et al. ( 2004 )’s conceptualisation of student engagement, along with Bond et al. ( 2020 )’s extensive and thorough list of indicators based on a large-scale review related to the three dimensions of engagement, therefore provides a coherent and practical framework for mapping studies of educational technologies and their use to actual engagement types, including the broader, holistic views of student engagement. Although no direct relationship between introducing specific educational technologies and student engagement in higher education has been established (Schindler et al., 2017 ; see also Pickering & Swinnerton, 2019 ), studies show that technology in education does influence student engagement and that more research is needed to understand the potential of specific educational technologies and how to benefit from them (Bond & Bedenlier, 2019 ; Clark, 1994 ; Lillejord et al., 2018 ) and thus ultimately meet the widespread desire to promote student engagement with educational technology. This leads to the following research question:

How to engage students with educational technology in higher education?

A systematic literature review guided by the PRISMA process and utilising the inclusion and exclusion criteria in Table  1 was conducted to answer this question. The PRISMA process involved four steps: (1) searching for, screening and identifying relevant studies based on abstracts; (2) screening of and excluding studies that were not relevant based on full-text; (3) assessment of eligibility based on full-text; and (4) selection (‘inclusion’), coding, and analysis of the relevant studies in the final synthesis (see 6. for details). The analysis was based on a deductive and inductive coding of the studies according to educational technology, subject area, educational level, modality, type of student engagement, research method, and aim (Khan et al., 2003 ; Littell et al., 2008 ; Moher et al., 2009 ); and supplemented with follow-up searches (“Round 2”) on the identified types of educational technologies in step 4 (see details in 6. and Godsk et al, 2021 ). Fredricks et al.’s ( 2004 ) conceptualisation of student engagement as comprising three perspectives — behavioural, affective (emotional), and cognitive engagement — as well as Bond et al. ( 2020 )’s identification of 55 specific indicators related to these dimensions, served as the basis for the coding of the engagement type (see Bond et al., 2020 , Additional file 2). In Round 1, the searches were limited to empirical studies from OECD countries from 2013 onwards for maximum comparability of the educational contexts regarding teaching tradition, educational regulations, including GDPR, and the available technologies. In Round 2, there were no exclusion criteria related to country or resource type as long as the resource was scientifically robust and directly or indirectly based on empirical data. However, only resources that included firsthand empirical data were included as the basis of the synthesis and recommendations, while, for example, systematic reviews and reports were used for perspective and discussion.

In the first round, 2,154 articles were screened, and 112 empirical studies were included in the synthesis. The 112 studies document a positive or negative engagement potential of educational technology related to eight major clusters of educational technologies, hereafter referred to as “types”: (1) learning management systems, (2) discussion forums and weblogs, (3) audience response systems and tablets, (4) online quizzes, (5) social media, (6) video and audio, (7) games and gamification, and (8) virtual reality and simulation. In addition, only eight eligible studies addressed diverse technologies that did not fall within these eight types of technologies (i.e., digital curation tools, e-portfolios, peer feedback tools, haptic devices (except virtual and augmented reality), digital magazines, open badges, word clouds, and diverse or non-specified mobile technologies), thereby constituting an insufficient basis to conclude on their engagement potential and thus excluded from the article. In the second round, the eight identified types of technology were used to search more specifically for the engagement potential of each respective technology. This resulted in screening 618 new articles, of which 60 ended up being added, bringing the total number of studies and other publications included in the article to 196 (see Table  2 and Appendix  for details). The second round of searches validated and expanded the already identified recommendations, but only eight new recommendations were identified, suggesting that the list was already saturated.

The coding revealed that a wide range of subject areas were represented, including the social sciences, comprising psychology and business; natural and technical sciences; humanities; and health sciences, as well as a representation of first-year, other undergraduate, and postgraduate teaching. The coding also revealed that most included studies were based on qualitative case studies or quantitative quasi-experimental research methods involving pre- and post-studies or a control group receiving conventional teaching, analysing differences in students’ test results, activity level, perceived engagement, or attitude. However, despite the wide representation of subject areas and levels and the thorough research, it is difficult to generalise findings from these kinds of studies from various contexts. Thus, the findings and recommendations in this article build on the heterogeneity principle (Patton, 2015 ) that any common finding that emerges from a great variation suggests a potentially more general pattern and forms the basis for the recommendations for each technology collected in Table  2 .

The included studies show that educational technology can engage students in higher education behaviourally, affectively, and cognitively. However, the studies also show that this potential depends on the context, how the technology is pedagogically and didactically integrated into teaching practice, and that the potential type of engagement varies between the specific educational technologies (Vercellotti, 2018 ). The findings for actualising the engagement potential of the eight types of educational technologies are further unfolded in the following sections and Table  2 .

3.1 Learning Management Systems

Learning Management Systems (LMS) is a collective term for web-based learning platforms for developing, distributing, delivering, and administrating educational materials and activities via the Internet (Weller, 2007 ). 99% of higher education institutions have at least one platform available, of which Canvas, Blackboard, Brightspace, and Moodle are currently the most widespread (Dahlstrom & Bichsel, 2014 ). Clark et al. ( 2016 ) demonstrate that an LMS can lead to increased engagement, better student-educator interaction, and improved learning when used to structure flipped classrooms with online video lessons supplemented by face-to-face activities. Zanjani et al. ( 2017 ) also note that engagement is generally strengthened by simple structure and navigation and a manageable number of links and tools that students can customise according to their needs and preferences. Furthermore, Karaksha et al. ( 2013 ) highlight that it is relevant to remind students of the available digital tools to increase their use and engagement potential. Vercellotti ( 2018 ) compares students’ learning outcomes in online and face-to-face teaching and finds that how the technology is utilised to support an active learning pedagogy plays a crucial role, while Osman ( 2022 ) finds that combining synchronous and asynchronous activities in the LMS enhances students’ interaction and engagement and ultimately their satisfaction. Orcutt and Dringus ( 2017 ) highlight how educators’ online presence and passion for teaching influence the students’ intellectual curiosity. Wdowik ( 2014 ) highlights the opportunities to support more interaction and collaboration between educator and students, as well as among students, using the video conferencing tool in the LMS.

Another potential of LMSs is linked to their tools for tracking students’ activities, progress, and submissions (Veluvali & Surisetti, 2022 ). Lawrence et al. ( 2019 ) point out how learning analytics can promote desired study behaviour and increase behavioural engagement by identifying and assisting students at a low academic level or close to dropping out through reminders, links to resources, or other support for task completion. The study also emphasises the need to explicitly communicate expectations for online students and prepare them for online activities (Pepple, 2022 ). The tools to monitor students’ progression also influence their retention through continuous summative assessment and peer feedback, and students can monitor their learning. This can be done, for example, through the educator’s feedback on activities and tasks submitted on the e-learning platform (Holmes, 2018 ) or via peer assessment activities, where students anonymously assess each other’s activities and assignments (Mirmotahari et al., 2019 ; Sullivan & Watson, 2015 ).

3.2 Discussion forums and weblogs

Discussion forums and weblogs are typically used for asynchronous activities in which students and the educator discuss and develop ideas related to the course content and form using threaded discussions, text, and possibly multimedia independently of time and place. Most LMSs have a built-in discussion forum that the educator typically manages, whereas weblogs are often managed by the students individually. Research on this technology, in general, focuses primarily on how the technology can be used to train writing, critical thinking, reflection, and argumentation, social constructivist online teaching and peer learning, “scaffolding” (Arend, 2009 ; Dalsgaard & Paulsen, 2009 ; MacKnight, 2000 ; Salmon, 2000 ; Szabo & Schwartz, 2011 ), and how students can be activated in their learning processes (Balaji & Chakrabarti, 2010 ; Dennen, 2005 ). The included studies show that it is essential that the educator outlines the code of conduct as well as provides short, precise instructions. Additionally, open questions at an appropriate academic level that can encourage all students to participate and discussions where students can apply existing experiences or relate them to their lives can be stimulating. Likewise, the peer aspect of online discussions can contribute to developing students’ professional identity and sense of belonging, thereby increasing their participation (Willis et al, 2013 ). In addition, audiovisual media can make discussions more authentic for the students (Douglas et al., 2020 ; Harvey et al., 2018 ; Kebble, 2017 ; Page et al., 2020 ). Stimulating questions can, for example, be formulated based on Bloom’s taxonomy (Badenhorst & Mather, 2014 ; Shaw & Irwin, 2017 ), and students’ participation can be strengthened by providing exemplars of “quality discussions” (Kebble, 2017 ). It is also effective to let the discussion be based on questions and topics that are engaging for students, such as relevant cases and real situations, and that invite students to share different opinions and develop personal perspectives through reflection questions (Buelow et al., 2018 ; Fukuzawa & Boyd, 2016 ). Another important factor is the educator’s visible and active participation in the discussion forum, which can consist of relevant contributions related to the issues the students are discussing (Collins et al., 2019 ; Mokoena, 2013 ; Mooney et al., 2014 ) or guide and point out relevant teaching materials that students can work with (Fukuzawa & Boyd, 2016 ). It also has a positive effect on engagement if students are assigned roles that frame their active participation in the discussion (Mooney et al., 2014 ; Truhlar et al., 2018 ), there is a requirement to use a specific argumentation model (Oh & Kim, 2016 ), or the students’ participation is assessed according to well-defined criteria (Kebble, 2017 ; Wyatt, 2021 ). Truhlar et al. ( 2018 ) highlight that activities in which students summarise discussions stimulate higher-order thinking. Discussions with many participants and repetitive and extensive posts are experienced as frustrating, so large groups should consider this (Fukuzawa & Boyd, 2016 ; Kebble, 2017 ). Concerning weblogs in formal settings, Sharma and Tietjen ( 2016 ) demonstrate a similar effect on education, indicating that the technology is viable for supporting both students’ collaboration and meaning-making.

3.3 Audience response systems

Audience response systems and devices (ARS) are a collective term for a range of software and hardware-based technologies that allow students to participate in activities such as polls or ask questions and provide answers interactively during lectures using their computer, tablet, mobile phone, or a so-called clicker. The majority of studies find that activities involving audience response systems enhance student engagement (Çakir, 2020 ; Fischer et al., 2015 ; Funnell, 2017 ; Habel & Stubbs, 2014 ; Han & Finkelstein, 2013 ; Jozwiak, 2015 ; Kay & LeSage, 2009 ; Remón et al., 2017 ; Sawang et al., 2017 ; Shaw et al., 2015 ; Sun et al., 2014 ), and a comprehensive literature review from 2009 highlights the technology’s potential to particularly increase behavioural and cognitive engagement (Kay & LeSage, 2009 ). Shaw et al. ( 2015 ) and Lim’s ( 2017 ) studies demonstrate that digital polls with questions and answers foster a sense of cohesion between the educator and students, which is not typically experienced in large classes. The technology also provides educators with insights into students’ learning outcomes for continuous feedback and addressing their questions (McKenzie & Ziemann, 2020 ; Remón et al., 2017 ; Robson & Basse, 2018 ; Yilmaz, 2017 ) and allows students to pause the classroom if they needed more time (Dong et al., 2017 ). Polls should ideally be academically challenging (Sawang et al., 2017 ), preferably combined with group activities (Jozwiak, 2015 ) or plenary discussions in the class (Robson & Basse, 2018 ; Sawang et al., 2017 ), and ideally allow students to respond anonymously (Heaslip et al., 2014 : Remón et al., 2017 ). Notably, the opportunity to discuss the reasoning behind poll responses is crucial (Habel & Stubbs, 2014 ; Steadman, 2015 ; see also “Peer Instruction,” Crouch & Mazur, 2001 , and Thomas et al., 2017 ). It can also enhance engagement if students formulate questions themselves (Song et al., 2017 ) or if the question is open-ended, controversial, or requires ethical consideration or higher-order thinking (Campbell & Monk, 2015 ; Steadman, 2015 ; Wood & Shirazi, 2020 ). Finally, the technology can support students’ mutual dialogue through a “backchannel,” where students can discuss ongoing teaching, leading to higher student satisfaction, higher grades, and more frequent use of class content (Neustifter et al., 2016 ).

3.4 Online quizzes

In online quizzes, students can answer questions related to the subject matter. Online quizzes differ from audience response stems by being fully online and, typically, asynchronous so that they can be used and reused regardless of time and place. The activities contribute to students’ understanding and deep learning and consolidate what has been learned (Argyriou et al., 2022 ; Browne, 2019 ; Russell et al., 2016 ). Students appreciate the flexible access, the options to revisit the quizzes, and the ability to do the quizzes at their own pace (Browne, 2019 ). When quizzes are used regularly for providing feedback, it promotes students’ engagement (Browne, 2019 ; Holmes, 2015 ; Lee & Harris, 2018 ; McKenzie et al., 2013 ) and is an effective mechanism for incentivising student completion of preparatory work (Cann, 2016 ; Cook & Babon, 2017 ; Cossu et al., 2022 ). It is important to use various quiz question types (Browne, 2019 ) and provide the students with specific feedback so that they can monitor and self-regulate their studying and progression (Evans et al., 2021 ; Thomas et al., 2017 ). Combining quizzes with group activities promotes students’ engagement and learning outcomes (Balta & Awedh, 2017 ) and supports collaborative learning.

3.5 Social media

Social media is a collective term for web-based social networks where users can socialise, communicate, and share files and other information. Social media is typically not an institutionalised learning technology but often plays a role in students’ social interaction and their informal digital learning environment (frequently referred to as “personal learning environment,” PLE, see also Caviglia et al., 2018 ) or as part of the curriculum (see Delello et al., 2015 ; Megele, 2015 ). Overall, studies indicate that increased interaction and collaboration opportunities offered by the social media in terms of their flexibility and the ability to incorporate external resources contribute to enhanced motivation and interest in teaching (Camus et al., 2016 ; Cooper & Naatus, 2014 ; Chugh & Ruhi, 2018 ; Delello et al., 2015 ; Evans, 2014 ; Glowatz & Bofin, 2014 ; Graham, 2014 ; Gregory et al., 2016 ; Kent, 2013 ; Northey et al., 2015 ; Scott & Stanway, 2015 ; Sharma & Tietjen, 2016 ). Students prefer Facebook and Twitter (now “X”) over discussion forums in LMSs, as they are perceived as more accessible than the LMSs’ discussion forums (Kent, 2013 ) and are more familiar (Clements, 2015 ). However, other studies suggest that familiarity with Facebook does not guarantee its use for study purposes (Dyson et al., 2015 ; Gregory et al., 2016 ). Similarly, Cooke ( 2017 ) points out a risk that students may lose interest in the specific social media and, as a result, its value as a supplementary tool for supporting discussions if the platform is their primary learning platform and its use is mandatory (Cooke, 2017 ). Both Camus et al. ( 2016 ) and Kent ( 2013 ) note that the use of Facebook resulted in more dialogue compared to the institutionalised LMS, and Evans ( 2014 ), Tiernan ( 2014 ), and Pallas et al. ( 2019 ) find that social media can also contribute to increasing student collaboration, creating an inclusive atmosphere that increases the participation of “quiet” students and supporting deep learning (Megele, 2015 ). However, if assessment is involved, it is important to be explicit about expectations and criteria (O’Brien & Freund, 2018 ). Similarly, Barber et al. ( 2015 ) show that a “Digital Moments” course helped create meaningful online learning communities among the students. Kent ( 2013 ) also points to a different perception and use of social media and LMS. LMS is associated with formal learning, while social media is more often used for practical questions and informal collaboration. Several studies describe different ways Twitter has been used: as a channel for questions to the instructor during class (Kunka, 2020 ; Tiernan, 2014 ; Prestridge, 2014 ), as a discussion forum between students and possibly external participants (Bender, 2021 ; Dragseth, 2020 ; Megele, 2015 ), and as a channel for students to share academic examples (Prestridge, 2014 ). Diug et al. ( 2016 ) demonstrate that Twitter gave students a sense of increased access to their educators while supporting their collaboration.

3.6 Video, audio, and multimedia

Video, audio, and multimedia are used here as a broad term for synchronous and asynchronous, audiovisual and digital multimedia, such as video presentations of course content and feedback on assignments, video recordings from field trips, and video assignments, produced by both the educator, students, or external providers. Video can be used, for example, to “flip” the teaching, allowing students to watch video lectures at home, creating more time for in-class dialogue (Noetel et al., 2021 ; Willis et al., 2018 ), appealing to multiple sensory channels simultaneously (Mayer, 2008 ), and supporting more authentic communication compared to written communication (Henderson & Phillips, 2015 ; McCarthy, 2015 ; Noetel et al., 2021 ; Oh & Kim, 2016 ). Activities where students produce audio can enhance their engagement, provided they have the equipment and skills to create them (Bolliger & Armier, 2013 ). In addition, student-produced audio materials can have a socialising effect on teaching due to their authenticity and personal touch, offering variation compared to traditional written assignments (Barber et al., 2015 ; Bolliger & Armier, 2013 ). Similarly, audio and video feedback from the educator is perceived as more personal and information-rich than written feedback (Cavaleri et al., 2019 ; Pearson, 2018 ; Rasi & Vuojärvi, 2018 ; Seery, 2015 ; Zhan, 2023 ) as well as video conferences can make the educator more visible and “accessible” than in face-to-face teaching (Gleason & Greenhow, 2017 ; Ng, 2018 ; Wdowik, 2014 ), thus creating a closer connection and being perceived as more personal (Steele et al., 2018 ). Educator feedback on video is often revisited and used in later assignments (Speicher & Stollhans, 2015 ). Several studies document a generally positive attitude towards video lectures and instructions among students, providing greater flexibility and allowing more independence in the learning process compared to face-to-face teaching (O’Callaghan et al., 2017 ; Gnaur & Hüttel, 2014 ; Lin et al., 2017 ; Lupinski & Kaufman, 2023 ; Scagnoli et al., 2019 ; Seery, 2015 ; Speicher & Stollhans, 2015 ). Scagnoli et al. ( 2019 ) conclude that the more video lectures students watch, the more positively they perceive the medium. However, they also emphasise the importance of familiarity with and experience using video for learning purposes, students’ academic level (postgraduate students are more positive than undergraduates), and how well the video lectures are integrated into the course. In addition, Brame ( 2016 ) stresses the importance of minimising students’ cognitive load when watching the videos — a parallel theme to research on “attention span,” which ambiguously indicates various durations students can maintain concentration depending on the context, teaching format, subject matter, and the students’ characteristics (Bradbury, 2016 ; Hartley & Davies, 1978 ). However, there are also studies highlighting the risk of a more superficial learning approach (Francescucci & Rohani, 2019 ; Trenholm et al., 2019 ), lower learning outcomes (Roberts, 2015 ), lower attendance in class (O’Callaghan et al., 2017 ), and lower engagement with video lectures where in particular the low-performing students are at risk (Murphy & Stewart, 2015 ). Lin et al. ( 2017 ) point out that students found concrete, instructional videos for laboratory work more useful and essential for their learning than video lectures of a generally more conceptual nature. However, the longer the videos are, the fewer students will watch them to the end (Lin et al., 2017 ). Video combined with other activities such as quizzes, small assignments, group work, or individual feedback positively impacts student engagement (Brame, 2016 ; Gnaur & Hüttel, 2014 ; Jozwiak, 2015 ; Paiva et al., 2017 ). In addition, student-produced video and audio for learning and assessment purposes may also positively impact students’ learning experience and contribute to the development of their communication, knowledge construction, and teamwork skills (Arsenis et al., 2022 ; Mathany & Dodd, 2018 ; Morena et al., 2019 ), for example, in the form of digital storytelling, which can also contribute to developing social and cultural competencies (Grant & Bolin, 2016 ; Ribiero, 2016 ; Yousuf & Conlan, 2018 ).

3.7 Games and gamification

Games and gamification as educational technology involve activities with various forms of game elements such as leaderboards, points, badges, or other forms of rewards or competition. The technology distinguishes itself from online quizzes by extensively using entertainment and possible competitive elements to motivate students’ participation and learning (Educause Learning Initiative, 2011 ). Subhash and Cudney ( 2018 ) find in their review that the elements mentioned above increase, in particular, the students’ attitude, level of participation, motivation, and performance. However, several studies also highlight the importance of authenticity and its relation to reality. Edmonds and Smith ( 2017 ) find that mobile learning games can engage students if they involve interactive investigations of phenomena with fellow students and involve them as designers of similar games. Similarly, Buckley and Doyle ( 2016 ) find that involving games with real-world dilemmas and decisions increases student engagement. However, it is important to note that students who are already gamers are more positive towards games in education than other students (Davis et al., 2018 ). Bawa ( 2019 ), Plump and LaRosa ( 2017 ), and Holbrey ( 2020 ) find that the game-inspired polling tool Kahoot can increase student engagement and participation in education if used for students to play together in groups against other groups, collaboratively create quizzes for other groups based on the curriculum, and this subsequently forms the basis for discussion among the students. Viswanathan and Radhakrishnan ( 2018 ) document in this context that students find it engaging to be co-developers of a game and that it supports their critical thinking. The combination of games and collaboration is also highlighted by Christopoulos et al. ( 2018 ), who, in their study, emphasise the importance of both the interaction among students and the function of the game. For example, individual games that test students’ knowledge will only be engaging for a few students (Christopoulos et al., 2018 ).

3.8 Virtual reality and simulation

Virtual reality (VR) and simulation are computer-generated simulations of an environment where educators and students can interact via a computer or, for example, through a dedicated headset (Makransky & Petersen, 2019 ). Studies indicate a general increase in engagement, especially due to the sense of presence (Cavanaugh et al., 2023 ; Chulkov & Wang, 2020 ; Papanastasiou et al., 2019 ; Rafiq et al., 2022 ), the simulated first-hand experiences that would have been impossible in the real world (Di Natale et al., 2020 ) for instance, interacting with three-dimensional virtual molecular phenomena (Elford et al., 2021 ), doing virtual field trips in Google Earth (McDaniel, 2022 ), use virtual microscopes for manipulation of online images (Herodotou et al., 2020 ) and provide variation for the students in the learning process (Hayes et al., 2021 ). However, opinions on the technology may be divided, and reservations among students often stem from a lack of experience and comfort in participating and interacting in VR (Francescucci & Foster, 2013 ). Francescucci and Foster ( 2013 ) and Makransky and Lilleholt ( 2018 ) find it essential to ensure that students have a high level of autonomy through a sense of control and active learning when using the technology, while others find it important that educators have the qualifications to use VR for learning purposes, give time for students to get familiar with the technology and have access to support in initial phases (Nesenbergs et al., 2020 ; Pellas et al., 2021 ). Luo et al. ( 2021 ) find that activities in VR can benefit from being combined with non-VR activities, including group or educator debriefings related to the VR activities. Pellas and Kazanidis ( 2015 ) found significantly positive learning outcomes and engagement results for teaching conducted solely in Second Life, compared to combined Second Life and face-to-face teaching. Matthew & Butler’s ( 2017 ) study showed that video from Second Life was suitable for simulating authentic problems, positively influencing students’ engagement and learning outcomes. Similarly, Sobocan and Klemenc-Ketis ( 2017 ) document that virtual patients in teaching for diagnosis and medical practice are perceived as beneficial due to the increased opportunities for skill training. Likewise, a positive effect on student engagement is demonstrated in simulations. Pallas et al. ( 2019 ) identify how simulations can increase students’ online interaction and reflection, including involving otherwise quiet students. Irby et al. ( 2018 ) and Marques et al. ( 2014 ) point out that virtual laboratories can be just as engaging as working in a physical laboratory and, in some situations, primarily introductory modules, completely replace face-to-face laboratory work.

4 Discussion

Overall, the included studies document the potential of educational technology to engage students in higher education behaviourally, affectively, and cognitively, which is dependent on the context, integration, and the specific educational technology as well as the specific technology’s support for structure, active learning, communication, and interaction between students and/or educators (Fig.  1 , further developed from Schindler et al., 2017 ). Furthermore, the synthesis indicates that each of the eight technologies has the potential to support all three forms of engagement, of which some are more well-documented than others and that they are interconnected.

Overview of the potential of educational technology for student engagement

Across 64 studies, the impact on students’ behavioural engagement is documented, particularly in the context of LMSs, discussion forums, audience response systems, online quizzes, social media, video and audio, and virtual reality and simulations. The studies document that technologies suitable for conveying curriculum content, creating structure, providing assessment tasks, and facilitating interaction and active learning effectively support students’ behavioural engagement. The interaction between students and content, educators, and peers is crucial for behavioural engagement (McCallum et al., 2015 ) as well as a course organisation with clear learning goals, logical course structures, recurring activities, and regular interactions with peers and educators contribute to behavioural engagement, satisfaction, and learning (Gray & DiLoreto, 2016 ; Gross et al., 2015 ; Porcaro et al., 2016 ; Ravenscroft & Luhanga, 2018 ; Ravishankar et al., 2018 ). Thus, this also shows how structure influences students’ affective engagement. Muir et al. ( 2019 ) highlight the importance of assessment tasks, workload, work-life balance, assignment quality, and educator presence. While online activities can enhance retention and engagement (Callahan, 2016 ), Dumford & Miller, ( 2018 ) note a link between students’ preferences and experience with online learning. Studies emphasise the flexibility of access to online teaching materials, with video lectures freeing up time for more engaging in-class activities (Steen-Utheim & Foldnes, 2018 ).

The impact of technology on students’ affective engagement is highly linked to how it influences the communication and interaction between students and educators, as documented in 59 studies. Communication tools within the LMS, discussion forums for peer learning, social media, competitive game elements, VR and simulations, and other audiovisual media can play a key role in this context. In general, technologies facilitating multi-faceted communication and interaction and educator involvement are often effective for affective engagement (Vayre & Vonthron, 2017 ). Educator presence, social support, figurative language, and effective facilitation are pivotal factors in online settings (Dixson et al., 2017 ; O’Shea et al., 2015 ; Orcutt & Dringus, 2017 ; Yates et al., 2014 ). Nevertheless, students’ low technological skills can negatively impact their affective engagement (Butz et al., 2016 ; Vayre & Vonthron, 2017 ), and some students may prefer using technologies they are already familiar with (del Barrio-Garcia et al., 2015 ). While students generally have experience with and a positive attitude towards technology in education, they may lack the skills to use technology in their academic work (Kim et al., 2019 ). Technology and online teaching can also hinder students’ involvement in the informal, implicit aspects of academic work (Selwyn, 2016 ).

The cognitive engagement is documented in 46 studies and notably supported by technologies such as audio and video, virtual reality and simulations, and audience response systems used to facilitate active and flexible student involvement in high taxonomic learning activities, such as collaboration, problem-solving, reflection, authentic exploration, and hypothesis testing. Flexible technology access supports self-directed learning, motivating students to engage actively (Mello, 2016 ; Mihret et al., 2017 ). McGuinness and Fulton ( 2019 ) illustrate the value of online tutorials as a flexible supplement to in-class teaching, aiding students in self-paced learning. Mihret et al.’s ( 2017 ) case-based teaching, combined with online discussions and ongoing e-portfolio assessment, enhances self-directed learning compared to face-to-face participation. However, high flexibility may negatively impact affective engagement due to the self-discipline required (McCallum et al., 2015 ). The technology may also support adaptive learning involving diagnostic quizzes, individual materials, formative tests, lectures, and summative tests that enhance satisfaction, performance, and cognitive engagement, as McKenzie et al. ( 2013 ) and Pourdana ( 2022 ) demonstrated. Technology supporting pedagogical strategies, like Baum’s ( 2013 ) guided inquiry, blends short video lectures and self-organised problem-solving, proving less confusing than traditional teaching. Gibbings et al. ( 2015 ) highlight the role of technology in providing authentic online activities and fostering communication, collaboration, and personal development despite geographical distances. Activities that challenge students’ understanding of societal issues, entertaining elements, and connections to past experiences also enhance cognitive and affective engagement (Buelow et al., 2018 ; O’Shea et al., 2015 ).

4.1 Breadth and Interconnectedness

When looking across the three types of engagement, there is no clear pattern in which technologies that engage students in more than one way. However, as also stressed by Payne ( 2019 ) and Fredricks et al. ( 2004 ), engagement is often interconnected, and indicators can be ambiguous. This interconnectedness is notably evident from the 25 included studies on specific technologies and background studies that document the technology’s potential to engage students in multiple ways simultaneously as well as from the studies that investigate the impact of technology-enhanced learning designs in education (e.g., Gray & DiLoreto, 2016 ; Gross et al., 2015 ; Porcaro et al., 2016 ; Ravenscroft & Luhanga, 2018 ; Ravishankar et al., 2018 ). Audience response systems and video, audio, and multimedia appeared most frequently in the studies of specific technologies, with seven and five studies, respectively, and three studies demonstrated a potential to support all three types of engagement simultaneously (Chulkov & Wang, 2020 , on VR, and Christopoulos et al., 2018 , on games and gamification; and Neustifter et al., 2016 , on audience response systems). The varying documented breadth may be due to a narrow focus of the individual studies, but it may also suggest a diverse potential to support student engagement more broadly. Furthermore, it may indicate that it often does not make sense to talk about a specific type of engagement potential as they are often interconnected and/or prerequisites for each other, just as important indicators can be overlooked. For example, Bond et al. ( 2020 ) categorise “confidence” as a (direct) indicator of affective engagement as well as an (indirect) indicator of behavioural engagement. The rationale is that the students’ confidence with the technology is manifested in their constructive behaviour. Likewise, cognitive engagement can manifest as self-regulated behaviour or simple memorisation (Fredricks et al., 2004 ).

Overall, the conceptual framework of student engagement by Fredricks et al. ( 2004 ) and the indicators provided by Bond et al. ( 2020 ) are useful for capturing a broad spectrum of the concept. This includes both observable behaviours, traditionally associated with narrow understandings of student engagement and the broader understandings, where student engagement is linked to experience, satisfaction, learning outcomes, and various affective and cognitive factors. This broader conceptualisation also addresses the additional dimensions proposed by Kahu ( 2013 ), Linnenbrink-Garcia et al. ( 2011 ), and Reeve and Tseng ( 2011 ). Furthermore, these frameworks accommodate indicators that may be overlooked without technology. For example, the use of technology allows for the observation of student engagement in online peer feedback activities (Mirmotahari et al., 2019 ) and supports self-regulated behaviours through online quizzes that enable students to monitor their progress and receive automated feedback (Evans et al., 2021 ; McKenzie et al., 2013 ; Thomas et al., 2017 ). However, the results suggest that one should place little importance on the actual classification but rather consider whether a given indicator may point to multiple types of engagement and be connected to other indicators.

4.2 How to Engage Students with Educational Technology in Higher Education?

The answer to the research question depends on the type of engagement one wishes to support, available technologies, and the specific context and educator competencies. For instance, to increase students’ behavioural engagement, educators may utilise technologies that provide structure and support active content delivery, such as LMSs, ARSs, and online quizzes, and follow the provided recommendations (Table  2 ). Those aiming to increase students’ affective engagement can benefit from technologies supporting student interaction, like discussion forums, social media, and games. Educators wanting to support students’ cognitive engagement can use simulations to aid students in authentic exploration of a given topic, have the students produce their own video, or facilitate structured online discussions. If there is a need to engage students behaviourally, affectively, and/or cognitively at the same time, it is relevant to consider technologies with a documented, broad engagement potential. However, if the educational technology is already provided, the recommendations provided (Table  2 ) can increase the chances of engaging students with the respective technology.

4.3 Limitations

The study in this article has revealed limitations related to the concept of student engagement and an inherent limitation associated with the research methods of the available studies.

The term “engagement” is ambiguous in English and may refer to attending something in a broad sense (Payne, 2019 ) or, in a narrow sense, referring to student behaviour in class (Zepke, 2015 ). Conversely, studies may deal with student engagement without necessarily using the term. A similar limitation is seen in the naming of educational technologies, which are often referred to by the name of the software or hardware and not necessarily by the type of technology, which is why it is easy to overlook relevant studies with a traditional protocol-driven search strategy based on keywords.

In addition, the study confirmed that engagement can be interconnected and indicators can be ambiguous. This is not a problem per se in realising the technology’s engagement potential but rather a problem in analysing studies that investigate and document a narrow engagement potential. Thus, further validation and mapping of the interconnectedness of Bond et al. ( 2020 )'s indicators would be useful.

Finally, there is a limitation that relates to the nature of the available studies, which are often characterised by qualitative case and quasi-experimental studies and other research methodologies in which it is difficult to distinguish the cause of the effect from other factors such as the novelty effect (McKechnie, 2008 ), the redesign of teaching that the introduction of technology entails (Kirkwood & Price, 2014 ), and the context (Schindler et al., 2017 ) and thus also to generalise findings. This calls for more research on the significance of the teaching context, including course design, course delivery, and other contextual factors.

5 Conclusion and implications

The article has identified the potential of educational technology to support students’ behavioural, affective, and cognitive engagement, along with a series of specific recommendations on how to realise this potential. These recommendations can be used, for example, by educators to incorporate specific, available educational technologies into their teaching or as an educational development method to enhance particular forms of student engagement. Educators and educational developers can use these recommendations to qualify the use of educational technology for student engagement in higher education. While the studies highlight various engagement potentials of educational technology, the synthesis also revealed that whether this potential is realised is dependent on the context, integration, the specific technology, and the educator’s competencies in teaching with technology (see also Orcutt & Dringus, 2017 , and Schindler et al., 2017 ). Furthermore, the synthesis also shows that all included technologies can support all three kinds of engagement, that engagement is often interconnected, and that technologies may vary in how broad their engagement potential is. Therefore, the recommendations should be viewed for what they are — practical guidelines derived from what was effective in another context — and should always be adjusted based on what is possible and relevant in the given situation. One cannot expect a specific effect on learning outcomes or student engagement simply by introducing a specific educational technology, and only few studies investigate aspects such as the importance of context, the role of the educator, how students interact, and what happens in the actual learning process (e.g., Bertheussen & Myrland, 2016 ; Butz et al., 2016 ; Evans, 2014 ; Steen-Utheim & Foldnes, 2018 ; Vercellotti, 2018 ). This calls for more research on the influence of course context and delivery on student engagement.

The synthesis also revealed that many aspects that determine whether the potential is realised are recognisable from traditional face-to-face teaching. For example, the educator’s active role as a facilitator of learning, active involvement of students, and consideration for students and their needs are crucial, as well as the technical support, feedback, authenticity, and learning environment. This is not surprising but important to remember when designing and delivering technology-enhanced, blended, and online learning. Careful considerations should be made for both the design and delivery of teaching: What is the purpose of educational technology, what potential does this technology hold for student engagement, and what determines whether this potential is realised? Thus, if all forms of engagement are to be supported by technology, the educator must have competencies in structuring, developing, and delivering technology-enhanced teaching, as well as taking the possibilities, engagement broadness, and limitations of the technology into account. Furthermore, the educator must be able to communicate and involve students in an activating way in high-taxonomic learning activities, as well as support students’ communication and interaction through suitable technology.

Data availability

The review is based on published research and other publicly available resources. A search protocol can be obtained from the authors upon reasonable request.

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Acknowledgements

The authors would like to thank Bente Kristiansen for her contribution to screening articles in the early version of the literature review as well as Jens Laurs Kærsgaard and Birthe Aagesen for feedback on earlier versions of this article.

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The results of the initial study from 2021 and its preliminary findings have been published in a Danish e-book (Godsk et al., 2021 ). Since this publication was based on narrow searches, only included results from before COVID-19), and did not include a specific research question or similar focus, everything has been completely revised, extended, and updated. Consequently, only very few elements from this e-book can be found in this article. Therefore, we consider the submitted article to be original and not published. Engaging students in higher education with educational technology.

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Appendix: Literature search

The literature review was guided by a PRISMA process (Khan et al., 2003 ; Littell et al., 2008 ; Moher et al., 2009 ; Appendix Fig.  2 ) and follow-up hand searches. The review identified eight clusters (henceforth referred to as “types”) of educational technologies, leading to focused follow-up hand searches on each technology type. This minimised the risk of overlooking key publications due to a single protocol-driven search strategy (Greenhalgh & Peacock, 2005 ). Figure  2 provides an overview of the process.

The PRISMA flow diagram

1.1 Search procedure and identification

The search in the first PRISMA process was carried out in January 2019 in four international databases: ERIC, Education Database, Australian Education Index, and British Education Index; eight Scandinavian databases: Bibliotek.dk, Forskningsdatabasen, Libris, Swepub, DIVA Portal, Oria, Christin, and Norart; and 12 Scandinavian knowledge-producing institutions’ databases and publications (see Godsk et al., 2021 ). The search combined three concepts and their synonyms: (1) educational technology or technology-enhanced learning (the means), (2) student engagement (the effect), and (3) university or higher education (the context) (see protocol for synonyms).

The second round of searches was conducted in 2022–2023 in Google Scholar and ERIC, combining each of the identified clusters of educational technologies, the student engagement concept, and higher education. The reason for using ERIC in the second round was that it, besides being one of the most comprehensive educational databases, also indexes other kinds of publication types such as theses, books, and reports. The reason for using Google Scholar was to compensate for the low effectiveness associated with protocol-driven searches on standard electronic databases (Greenhalgh & Peacock, 2005 ).

1.2 Screening and selection

The identified articles in the first round were imported into EPPI reviewer and screened. Studies of the wrong document type, year, country, educational level, language, or focus were excluded (see Fig.  2 ; Table  1 ). During the screening of articles, however, it became clear that most publications before 2013 were dated and thus not applicable for students today due to contextual factors such as the technologies’ stage of development, ethical and legal perspectives such as GDPR and privacy, and students’ technological skills and competencies. The first round identified 135 relevant articles, of which 112 were included in the review.

The second round was less exclusive in terms of publication type. It included any kind of publication, including theses, books, and reports, as long as it was relevant to the research question, scientifically robust, and directly or indirectly based on empirical data. This round involved the screening of 618 publications and resulted in the inclusion of 60 additional articles and other publications.

1.3 Data coding and analysis

The articles included in the first round were coded and negotiated by three researchers according to subject area, educational level, modality, educational technology, conceptualisation of student engagement, and research question/aim. The first round revealed eight clusters of educational technologies: learning management systems, discussion forums and weblogs, audience response systems, online quizzes, social media, video, audio and multimedia, games and gamification, and virtual reality and simulation. The round also revealed that student engagement was often not explicitly defined, often used as a synonym for students’ participation in the teaching (i.e., a form of behavioural engagement), and often measured on a single indicator and that the three-perspective conceptualisation by Fredricks et al. ( 2004 ) and the related indicators identified by Bond, Bedenlier and others (Bond & Bedenlier, 2019 ; Bond et al., 2020 ) were utilised for analysing the data and classifying the engagement potential.

The included studies were subsequently revisited, discussed, and organised according to the engagement potential of the specific educational technology together with the findings phrased as recommendations in Table  2 . Studies that did not analyse a specific educational technology are only included in the discussion, and technologies addressed only by individual studies are excluded from the article due to the limited extent of evidence.

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Impacts of digital technologies on education and factors influencing schools' digital capacity and transformation: A literature review

Stella timotheou.

1 CYENS Center of Excellence & Cyprus University of Technology (Cyprus Interaction Lab), Cyprus, CYENS Center of Excellence & Cyprus University of Technology, Nicosia-Limassol, Cyprus

Ourania Miliou

Yiannis dimitriadis.

2 Universidad de Valladolid (UVA), Spain, Valladolid, Spain

Sara Villagrá Sobrino

Nikoleta giannoutsou, romina cachia.

3 JRC - Joint Research Centre of the European Commission, Seville, Spain

Alejandra Martínez Monés

Andri ioannou, associated data.

Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

Digital technologies have brought changes to the nature and scope of education and led education systems worldwide to adopt strategies and policies for ICT integration. The latter brought about issues regarding the quality of teaching and learning with ICTs, especially concerning the understanding, adaptation, and design of the education systems in accordance with current technological trends. These issues were emphasized during the recent COVID-19 pandemic that accelerated the use of digital technologies in education, generating questions regarding digitalization in schools. Specifically, many schools demonstrated a lack of experience and low digital capacity, which resulted in widening gaps, inequalities, and learning losses. Such results have engendered the need for schools to learn and build upon the experience to enhance their digital capacity and preparedness, increase their digitalization levels, and achieve a successful digital transformation. Given that the integration of digital technologies is a complex and continuous process that impacts different actors within the school ecosystem, there is a need to show how these impacts are interconnected and identify the factors that can encourage an effective and efficient change in the school environments. For this purpose, we conducted a non-systematic literature review. The results of the literature review were organized thematically based on the evidence presented about the impact of digital technology on education and the factors that affect the schools’ digital capacity and digital transformation. The findings suggest that ICT integration in schools impacts more than just students’ performance; it affects several other school-related aspects and stakeholders, too. Furthermore, various factors affect the impact of digital technologies on education. These factors are interconnected and play a vital role in the digital transformation process. The study results shed light on how ICTs can positively contribute to the digital transformation of schools and which factors should be considered for schools to achieve effective and efficient change.

Introduction

Digital technologies have brought changes to the nature and scope of education. Versatile and disruptive technological innovations, such as smart devices, the Internet of Things (IoT), artificial intelligence (AI), augmented reality (AR) and virtual reality (VR), blockchain, and software applications have opened up new opportunities for advancing teaching and learning (Gaol & Prasolova-Førland, 2021 ; OECD, 2021 ). Hence, in recent years, education systems worldwide have increased their investment in the integration of information and communication technology (ICT) (Fernández-Gutiérrez et al., 2020 ; Lawrence & Tar, 2018 ) and prioritized their educational agendas to adapt strategies or policies around ICT integration (European Commission, 2019 ). The latter brought about issues regarding the quality of teaching and learning with ICTs (Bates, 2015 ), especially concerning the understanding, adaptation, and design of education systems in accordance with current technological trends (Balyer & Öz, 2018 ). Studies have shown that despite the investment made in the integration of technology in schools, the results have not been promising, and the intended outcomes have not yet been achieved (Delgado et al., 2015 ; Lawrence & Tar, 2018 ). These issues were exacerbated during the COVID-19 pandemic, which forced teaching across education levels to move online (Daniel, 2020 ). Online teaching accelerated the use of digital technologies generating questions regarding the process, the nature, the extent, and the effectiveness of digitalization in schools (Cachia et al., 2021 ; König et al., 2020 ). Specifically, many schools demonstrated a lack of experience and low digital capacity, which resulted in widening gaps, inequalities, and learning losses (Blaskó et al., 2021 ; Di Pietro et al, 2020 ). Such results have engendered the need for schools to learn and build upon the experience in order to enhance their digital capacity (European Commission, 2020 ) and increase their digitalization levels (Costa et al., 2021 ). Digitalization offers possibilities for fundamental improvement in schools (OECD, 2021 ; Rott & Marouane, 2018 ) and touches many aspects of a school’s development (Delcker & Ifenthaler, 2021 ) . However, it is a complex process that requires large-scale transformative changes beyond the technical aspects of technology and infrastructure (Pettersson, 2021 ). Namely, digitalization refers to “ a series of deep and coordinated culture, workforce, and technology shifts and operating models ” (Brooks & McCormack, 2020 , p. 3) that brings cultural, organizational, and operational change through the integration of digital technologies (JISC, 2020 ). A successful digital transformation requires that schools increase their digital capacity levels, establishing the necessary “ culture, policies, infrastructure as well as digital competence of students and staff to support the effective integration of technology in teaching and learning practices ” (Costa et al, 2021 , p.163).

Given that the integration of digital technologies is a complex and continuous process that impacts different actors within the school ecosystem (Eng, 2005 ), there is a need to show how the different elements of the impact are interconnected and to identify the factors that can encourage an effective and efficient change in the school environment. To address the issues outlined above, we formulated the following research questions:

a) What is the impact of digital technologies on education?

b) Which factors might affect a school’s digital capacity and transformation?

In the present investigation, we conducted a non-systematic literature review of publications pertaining to the impact of digital technologies on education and the factors that affect a school’s digital capacity and transformation. The results of the literature review were organized thematically based on the evidence presented about the impact of digital technology on education and the factors which affect the schools’ digital capacity and digital transformation.

Methodology

The non-systematic literature review presented herein covers the main theories and research published over the past 17 years on the topic. It is based on meta-analyses and review papers found in scholarly, peer-reviewed content databases and other key studies and reports related to the concepts studied (e.g., digitalization, digital capacity) from professional and international bodies (e.g., the OECD). We searched the Scopus database, which indexes various online journals in the education sector with an international scope, to collect peer-reviewed academic papers. Furthermore, we used an all-inclusive Google Scholar search to include relevant key terms or to include studies found in the reference list of the peer-reviewed papers, and other key studies and reports related to the concepts studied by professional and international bodies. Lastly, we gathered sources from the Publications Office of the European Union ( https://op.europa.eu/en/home ); namely, documents that refer to policies related to digital transformation in education.

Regarding search terms, we first searched resources on the impact of digital technologies on education by performing the following search queries: “impact” OR “effects” AND “digital technologies” AND “education”, “impact” OR “effects” AND “ICT” AND “education”. We further refined our results by adding the terms “meta-analysis” and “review” or by adjusting the search options based on the features of each database to avoid collecting individual studies that would provide limited contributions to a particular domain. We relied on meta-analyses and review studies as these consider the findings of multiple studies to offer a more comprehensive view of the research in a given area (Schuele & Justice, 2006 ). Specifically, meta-analysis studies provided quantitative evidence based on statistically verifiable results regarding the impact of educational interventions that integrate digital technologies in school classrooms (Higgins et al., 2012 ; Tolani-Brown et al., 2011 ).

However, quantitative data does not offer explanations for the challenges or difficulties experienced during ICT integration in learning and teaching (Tolani-Brown et al., 2011 ). To fill this gap, we analyzed literature reviews and gathered in-depth qualitative evidence of the benefits and implications of technology integration in schools. In the analysis presented herein, we also included policy documents and reports from professional and international bodies and governmental reports, which offered useful explanations of the key concepts of this study and provided recent evidence on digital capacity and transformation in education along with policy recommendations. The inclusion and exclusion criteria that were considered in this study are presented in Table ​ Table1 1 .

Inclusion and exclusion criteria for the selection of resources on the impact of digital technologies on education

To ensure a reliable extraction of information from each study and assist the research synthesis we selected the study characteristics of interest (impact) and constructed coding forms. First, an overview of the synthesis was provided by the principal investigator who described the processes of coding, data entry, and data management. The coders followed the same set of instructions but worked independently. To ensure a common understanding of the process between coders, a sample of ten studies was tested. The results were compared, and the discrepancies were identified and resolved. Additionally, to ensure an efficient coding process, all coders participated in group meetings to discuss additions, deletions, and modifications (Stock, 1994 ). Due to the methodological diversity of the studied documents we began to synthesize the literature review findings based on similar study designs. Specifically, most of the meta-analysis studies were grouped in one category due to the quantitative nature of the measured impact. These studies tended to refer to student achievement (Hattie et al., 2014 ). Then, we organized the themes of the qualitative studies in several impact categories. Lastly, we synthesized both review and meta-analysis data across the categories. In order to establish a collective understanding of the concept of impact, we referred to a previous impact study by Balanskat ( 2009 ) which investigated the impact of technology in primary schools. In this context, the impact had a more specific ICT-related meaning and was described as “ a significant influence or effect of ICT on the measured or perceived quality of (parts of) education ” (Balanskat, 2009 , p. 9). In the study presented herein, the main impacts are in relation to learning and learners, teaching, and teachers, as well as other key stakeholders who are directly or indirectly connected to the school unit.

The study’s results identified multiple dimensions of the impact of digital technologies on students’ knowledge, skills, and attitudes; on equality, inclusion, and social integration; on teachers’ professional and teaching practices; and on other school-related aspects and stakeholders. The data analysis indicated various factors that might affect the schools’ digital capacity and transformation, such as digital competencies, the teachers’ personal characteristics and professional development, as well as the school’s leadership and management, administration, infrastructure, etc. The impacts and factors found in the literature review are presented below.

Impacts of digital technologies on students’ knowledge, skills, attitudes, and emotions

The impact of ICT use on students’ knowledge, skills, and attitudes has been investigated early in the literature. Eng ( 2005 ) found a small positive effect between ICT use and students' learning. Specifically, the author reported that access to computer-assisted instruction (CAI) programs in simulation or tutorial modes—used to supplement rather than substitute instruction – could enhance student learning. The author reported studies showing that teachers acknowledged the benefits of ICT on pupils with special educational needs; however, the impact of ICT on students' attainment was unclear. Balanskat et al. ( 2006 ) found a statistically significant positive association between ICT use and higher student achievement in primary and secondary education. The authors also reported improvements in the performance of low-achieving pupils. The use of ICT resulted in further positive gains for students, namely increased attention, engagement, motivation, communication and process skills, teamwork, and gains related to their behaviour towards learning. Evidence from qualitative studies showed that teachers, students, and parents recognized the positive impact of ICT on students' learning regardless of their competence level (strong/weak students). Punie et al. ( 2006 ) documented studies that showed positive results of ICT-based learning for supporting low-achieving pupils and young people with complex lives outside the education system. Liao et al. ( 2007 ) reported moderate positive effects of computer application instruction (CAI, computer simulations, and web-based learning) over traditional instruction on primary school student's achievement. Similarly, Tamim et al. ( 2011 ) reported small to moderate positive effects between the use of computer technology (CAI, ICT, simulations, computer-based instruction, digital and hypermedia) and student achievement in formal face-to-face classrooms compared to classrooms that did not use technology. Jewitt et al., ( 2011 ) found that the use of learning platforms (LPs) (virtual learning environments, management information systems, communication technologies, and information- and resource-sharing technologies) in schools allowed primary and secondary students to access a wider variety of quality learning resources, engage in independent and personalized learning, and conduct self- and peer-review; LPs also provide opportunities for teacher assessment and feedback. Similar findings were reported by Fu ( 2013 ), who documented a list of benefits and opportunities of ICT use. According to the author, the use of ICTs helps students access digital information and course content effectively and efficiently, supports student-centered and self-directed learning, as well as the development of a creative learning environment where more opportunities for critical thinking skills are offered, and promotes collaborative learning in a distance-learning environment. Higgins et al. ( 2012 ) found consistent but small positive associations between the use of technology and learning outcomes of school-age learners (5–18-year-olds) in studies linking the provision and use of technology with attainment. Additionally, Chauhan ( 2017 ) reported a medium positive effect of technology on the learning effectiveness of primary school students compared to students who followed traditional learning instruction.

The rise of mobile technologies and hardware devices instigated investigations into their impact on teaching and learning. Sung et al. ( 2016 ) reported a moderate effect on students' performance from the use of mobile devices in the classroom compared to the use of desktop computers or the non-use of mobile devices. Schmid et al. ( 2014 ) reported medium–low to low positive effects of technology integration (e.g., CAI, ICTs) in the classroom on students' achievement and attitude compared to not using technology or using technology to varying degrees. Tamim et al. ( 2015 ) found a low statistically significant effect of the use of tablets and other smart devices in educational contexts on students' achievement outcomes. The authors suggested that tablets offered additional advantages to students; namely, they reported improvements in students’ notetaking, organizational and communication skills, and creativity. Zheng et al. ( 2016 ) reported a small positive effect of one-to-one laptop programs on students’ academic achievement across subject areas. Additional reported benefits included student-centered, individualized, and project-based learning enhanced learner engagement and enthusiasm. Additionally, the authors found that students using one-to-one laptop programs tended to use technology more frequently than in non-laptop classrooms, and as a result, they developed a range of skills (e.g., information skills, media skills, technology skills, organizational skills). Haßler et al. ( 2016 ) found that most interventions that included the use of tablets across the curriculum reported positive learning outcomes. However, from 23 studies, five reported no differences, and two reported a negative effect on students' learning outcomes. Similar results were indicated by Kalati and Kim ( 2022 ) who investigated the effect of touchscreen technologies on young students’ learning. Specifically, from 53 studies, 34 advocated positive effects of touchscreen devices on children’s learning, 17 obtained mixed findings and two studies reported negative effects.

More recently, approaches that refer to the impact of gamification with the use of digital technologies on teaching and learning were also explored. A review by Pan et al. ( 2022 ) that examined the role of learning games in fostering mathematics education in K-12 settings, reported that gameplay improved students’ performance. Integration of digital games in teaching was also found as a promising pedagogical practice in STEM education that could lead to increased learning gains (Martinez et al., 2022 ; Wang et al., 2022 ). However, although Talan et al. ( 2020 ) reported a medium effect of the use of educational games (both digital and non-digital) on academic achievement, the effect of non-digital games was higher.

Over the last two years, the effects of more advanced technologies on teaching and learning were also investigated. Garzón and Acevedo ( 2019 ) found that AR applications had a medium effect on students' learning outcomes compared to traditional lectures. Similarly, Garzón et al. ( 2020 ) showed that AR had a medium impact on students' learning gains. VR applications integrated into various subjects were also found to have a moderate effect on students’ learning compared to control conditions (traditional classes, e.g., lectures, textbooks, and multimedia use, e.g., images, videos, animation, CAI) (Chen et al., 2022b ). Villena-Taranilla et al. ( 2022 ) noted the moderate effect of VR technologies on students’ learning when these were applied in STEM disciplines. In the same meta-analysis, Villena-Taranilla et al. ( 2022 ) highlighted the role of immersive VR, since its effect on students’ learning was greater (at a high level) across educational levels (K-6) compared to semi-immersive and non-immersive integrations. In another meta-analysis study, the effect size of the immersive VR was small and significantly differentiated across educational levels (Coban et al., 2022 ). The impact of AI on education was investigated by Su and Yang ( 2022 ) and Su et al. ( 2022 ), who showed that this technology significantly improved students’ understanding of AI computer science and machine learning concepts.

It is worth noting that the vast majority of studies referred to learning gains in specific subjects. Specifically, several studies examined the impact of digital technologies on students’ literacy skills and reported positive effects on language learning (Balanskat et al., 2006 ; Grgurović et al., 2013 ; Friedel et al., 2013 ; Zheng et al., 2016 ; Chen et al., 2022b ; Savva et al., 2022 ). Also, several studies documented positive effects on specific language learning areas, namely foreign language learning (Kao, 2014 ), writing (Higgins et al., 2012 ; Wen & Walters, 2022 ; Zheng et al., 2016 ), as well as reading and comprehension (Cheung & Slavin, 2011 ; Liao et al., 2007 ; Schwabe et al., 2022 ). ICTs were also found to have a positive impact on students' performance in STEM (science, technology, engineering, and mathematics) disciplines (Arztmann et al., 2022 ; Bado, 2022 ; Villena-Taranilla et al., 2022 ; Wang et al., 2022 ). Specifically, a number of studies reported positive impacts on students’ achievement in mathematics (Balanskat et al., 2006 ; Hillmayr et al., 2020 ; Li & Ma, 2010 ; Pan et al., 2022 ; Ran et al., 2022 ; Verschaffel et al., 2019 ; Zheng et al., 2016 ). Furthermore, studies documented positive effects of ICTs on science learning (Balanskat et al., 2006 ; Liao et al., 2007 ; Zheng et al., 2016 ; Hillmayr et al., 2020 ; Kalemkuş & Kalemkuş, 2022 ; Lei et al., 2022a ). Çelik ( 2022 ) also noted that computer simulations can help students understand learning concepts related to science. Furthermore, some studies documented that the use of ICTs had a positive impact on students’ achievement in other subjects, such as geography, history, music, and arts (Chauhan, 2017 ; Condie & Munro, 2007 ), and design and technology (Balanskat et al., 2006 ).

More specific positive learning gains were reported in a number of skills, e.g., problem-solving skills and pattern exploration skills (Higgins et al., 2012 ), metacognitive learning outcomes (Verschaffel et al., 2019 ), literacy skills, computational thinking skills, emotion control skills, and collaborative inquiry skills (Lu et al., 2022 ; Su & Yang, 2022 ; Su et al., 2022 ). Additionally, several investigations have reported benefits from the use of ICT on students’ creativity (Fielding & Murcia, 2022 ; Liu et al., 2022 ; Quah & Ng, 2022 ). Lastly, digital technologies were also found to be beneficial for enhancing students’ lifelong learning skills (Haleem et al., 2022 ).

Apart from gaining knowledge and skills, studies also reported improvement in motivation and interest in mathematics (Higgins et. al., 2019 ; Fadda et al., 2022 ) and increased positive achievement emotions towards several subjects during interventions using educational games (Lei et al., 2022a ). Chen et al. ( 2022a ) also reported a small but positive effect of digital health approaches in bullying and cyberbullying interventions with K-12 students, demonstrating that technology-based approaches can help reduce bullying and related consequences by providing emotional support, empowerment, and change of attitude. In their meta-review study, Su et al. ( 2022 ) also documented that AI technologies effectively strengthened students’ attitudes towards learning. In another meta-analysis, Arztmann et al. ( 2022 ) reported positive effects of digital games on motivation and behaviour towards STEM subjects.

Impacts of digital technologies on equality, inclusion and social integration

Although most of the reviewed studies focused on the impact of ICTs on students’ knowledge, skills, and attitudes, reports were also made on other aspects in the school context, such as equality, inclusion, and social integration. Condie and Munro ( 2007 ) documented research interventions investigating how ICT can support pupils with additional or special educational needs. While those interventions were relatively small scale and mostly based on qualitative data, their findings indicated that the use of ICTs enabled the development of communication, participation, and self-esteem. A recent meta-analysis (Baragash et al., 2022 ) with 119 participants with different disabilities, reported a significant overall effect size of AR on their functional skills acquisition. Koh’s meta-analysis ( 2022 ) also revealed that students with intellectual and developmental disabilities improved their competence and performance when they used digital games in the lessons.

Istenic Starcic and Bagon ( 2014 ) found that the role of ICT in inclusion and the design of pedagogical and technological interventions was not sufficiently explored in educational interventions with people with special needs; however, some benefits of ICT use were found in students’ social integration. The issue of gender and technology use was mentioned in a small number of studies. Zheng et al. ( 2016 ) reported a statistically significant positive interaction between one-to-one laptop programs and gender. Specifically, the results showed that girls and boys alike benefitted from the laptop program, but the effect on girls’ achievement was smaller than that on boys’. Along the same lines, Arztmann et al. ( 2022 ) reported no difference in the impact of game-based learning between boys and girls, arguing that boys and girls equally benefited from game-based interventions in STEM domains. However, results from a systematic review by Cussó-Calabuig et al. ( 2018 ) found limited and low-quality evidence on the effects of intensive use of computers on gender differences in computer anxiety, self-efficacy, and self-confidence. Based on their view, intensive use of computers can reduce gender differences in some areas and not in others, depending on contextual and implementation factors.

Impacts of digital technologies on teachers’ professional and teaching practices

Various research studies have explored the impact of ICT on teachers’ instructional practices and student assessment. Friedel et al. ( 2013 ) found that the use of mobile devices by students enabled teachers to successfully deliver content (e.g., mobile serious games), provide scaffolding, and facilitate synchronous collaborative learning. The integration of digital games in teaching and learning activities also gave teachers the opportunity to study and apply various pedagogical practices (Bado, 2022 ). Specifically, Bado ( 2022 ) found that teachers who implemented instructional activities in three stages (pre-game, game, and post-game) maximized students’ learning outcomes and engagement. For instance, during the pre-game stage, teachers focused on lectures and gameplay training, at the game stage teachers provided scaffolding on content, addressed technical issues, and managed the classroom activities. During the post-game stage, teachers organized activities for debriefing to ensure that the gameplay had indeed enhanced students’ learning outcomes.

Furthermore, ICT can increase efficiency in lesson planning and preparation by offering possibilities for a more collaborative approach among teachers. The sharing of curriculum plans and the analysis of students’ data led to clearer target settings and improvements in reporting to parents (Balanskat et al., 2006 ).

Additionally, the use and application of digital technologies in teaching and learning were found to enhance teachers’ digital competence. Balanskat et al. ( 2006 ) documented studies that revealed that the use of digital technologies in education had a positive effect on teachers’ basic ICT skills. The greatest impact was found on teachers with enough experience in integrating ICTs in their teaching and/or who had recently participated in development courses for the pedagogical use of technologies in teaching. Punie et al. ( 2006 ) reported that the provision of fully equipped multimedia portable computers and the development of online teacher communities had positive impacts on teachers’ confidence and competence in the use of ICTs.

Moreover, online assessment via ICTs benefits instruction. In particular, online assessments support the digitalization of students’ work and related logistics, allow teachers to gather immediate feedback and readjust to new objectives, and support the improvement of the technical quality of tests by providing more accurate results. Additionally, the capabilities of ICTs (e.g., interactive media, simulations) create new potential methods of testing specific skills, such as problem-solving and problem-processing skills, meta-cognitive skills, creativity and communication skills, and the ability to work productively in groups (Punie et al., 2006 ).

Impacts of digital technologies on other school-related aspects and stakeholders

There is evidence that the effective use of ICTs and the data transmission offered by broadband connections help improve administration (Balanskat et al., 2006 ). Specifically, ICTs have been found to provide better management systems to schools that have data gathering procedures in place. Condie and Munro ( 2007 ) reported impacts from the use of ICTs in schools in the following areas: attendance monitoring, assessment records, reporting to parents, financial management, creation of repositories for learning resources, and sharing of information amongst staff. Such data can be used strategically for self-evaluation and monitoring purposes which in turn can result in school improvements. Additionally, they reported that online access to other people with similar roles helped to reduce headteachers’ isolation by offering them opportunities to share insights into the use of ICT in learning and teaching and how it could be used to support school improvement. Furthermore, ICTs provided more efficient and successful examination management procedures, namely less time-consuming reporting processes compared to paper-based examinations and smooth communications between schools and examination authorities through electronic data exchange (Punie et al., 2006 ).

Zheng et al. ( 2016 ) reported that the use of ICTs improved home-school relationships. Additionally, Escueta et al. ( 2017 ) reported several ICT programs that had improved the flow of information from the school to parents. Particularly, they documented that the use of ICTs (learning management systems, emails, dedicated websites, mobile phones) allowed for personalized and customized information exchange between schools and parents, such as attendance records, upcoming class assignments, school events, and students’ grades, which generated positive results on students’ learning outcomes and attainment. Such information exchange between schools and families prompted parents to encourage their children to put more effort into their schoolwork.

The above findings suggest that the impact of ICT integration in schools goes beyond students’ performance in school subjects. Specifically, it affects a number of school-related aspects, such as equality and social integration, professional and teaching practices, and diverse stakeholders. In Table ​ Table2, 2 , we summarize the different impacts of digital technologies on school stakeholders based on the literature review, while in Table ​ Table3 3 we organized the tools/platforms and practices/policies addressed in the meta-analyses, literature reviews, EU reports, and international bodies included in the manuscript.

The impact of digital technologies on schools’ stakeholders based on the literature review

Tools/platforms and practices/policies addressed in the meta-analyses, literature reviews, EU reports, and international bodies included in the manuscript

Additionally, based on the results of the literature review, there are many types of digital technologies with different affordances (see, for example, studies on VR vs Immersive VR), which evolve over time (e.g. starting from CAIs in 2005 to Augmented and Virtual reality 2020). Furthermore, these technologies are linked to different pedagogies and policy initiatives, which are critical factors in the study of impact. Table ​ Table3 3 summarizes the different tools and practices that have been used to examine the impact of digital technologies on education since 2005 based on the review results.

Factors that affect the integration of digital technologies

Although the analysis of the literature review demonstrated different impacts of the use of digital technology on education, several authors highlighted the importance of various factors, besides the technology itself, that affect this impact. For example, Liao et al. ( 2007 ) suggested that future studies should carefully investigate which factors contribute to positive outcomes by clarifying the exact relationship between computer applications and learning. Additionally, Haßler et al., ( 2016 ) suggested that the neutral findings regarding the impact of tablets on students learning outcomes in some of the studies included in their review should encourage educators, school leaders, and school officials to further investigate the potential of such devices in teaching and learning. Several other researchers suggested that a number of variables play a significant role in the impact of ICTs on students’ learning that could be attributed to the school context, teaching practices and professional development, the curriculum, and learners’ characteristics (Underwood, 2009 ; Tamim et al., 2011 ; Higgins et al., 2012 ; Archer et al., 2014 ; Sung et al., 2016 ; Haßler et al., 2016 ; Chauhan, 2017 ; Lee et al., 2020 ; Tang et al., 2022 ).

Digital competencies

One of the most common challenges reported in studies that utilized digital tools in the classroom was the lack of students’ skills on how to use them. Fu ( 2013 ) found that students’ lack of technical skills is a barrier to the effective use of ICT in the classroom. Tamim et al. ( 2015 ) reported that students faced challenges when using tablets and smart mobile devices, associated with the technical issues or expertise needed for their use and the distracting nature of the devices and highlighted the need for teachers’ professional development. Higgins et al. ( 2012 ) reported that skills training about the use of digital technologies is essential for learners to fully exploit the benefits of instruction.

Delgado et al. ( 2015 ), meanwhile, reported studies that showed a strong positive association between teachers’ computer skills and students’ use of computers. Teachers’ lack of ICT skills and familiarization with technologies can become a constraint to the effective use of technology in the classroom (Balanskat et al., 2006 ; Delgado et al., 2015 ).

It is worth noting that the way teachers are introduced to ICTs affects the impact of digital technologies on education. Previous studies have shown that teachers may avoid using digital technologies due to limited digital skills (Balanskat, 2006 ), or they prefer applying “safe” technologies, namely technologies that their own teachers used and with which they are familiar (Condie & Munro, 2007 ). In this regard, the provision of digital skills training and exposure to new digital tools might encourage teachers to apply various technologies in their lessons (Condie & Munro, 2007 ). Apart from digital competence, technical support in the school setting has also been shown to affect teachers’ use of technology in their classrooms (Delgado et al., 2015 ). Ferrari et al. ( 2011 ) found that while teachers’ use of ICT is high, 75% stated that they needed more institutional support and a shift in the mindset of educational actors to achieve more innovative teaching practices. The provision of support can reduce time and effort as well as cognitive constraints, which could cause limited ICT integration in the school lessons by teachers (Escueta et al., 2017 ).

Teachers’ personal characteristics, training approaches, and professional development

Teachers’ personal characteristics and professional development affect the impact of digital technologies on education. Specifically, Cheok and Wong ( 2015 ) found that teachers’ personal characteristics (e.g., anxiety, self-efficacy) are associated with their satisfaction and engagement with technology. Bingimlas ( 2009 ) reported that lack of confidence, resistance to change, and negative attitudes in using new technologies in teaching are significant determinants of teachers’ levels of engagement in ICT. The same author reported that the provision of technical support, motivation support (e.g., awards, sufficient time for planning), and training on how technologies can benefit teaching and learning can eliminate the above barriers to ICT integration. Archer et al. ( 2014 ) found that comfort levels in using technology are an important predictor of technology integration and argued that it is essential to provide teachers with appropriate training and ongoing support until they are comfortable with using ICTs in the classroom. Hillmayr et al. ( 2020 ) documented that training teachers on ICT had an important effecton students’ learning.

According to Balanskat et al. ( 2006 ), the impact of ICTs on students’ learning is highly dependent on the teachers’ capacity to efficiently exploit their application for pedagogical purposes. Results obtained from the Teaching and Learning International Survey (TALIS) (OECD, 2021 ) revealed that although schools are open to innovative practices and have the capacity to adopt them, only 39% of teachers in the European Union reported that they are well or very well prepared to use digital technologies for teaching. Li and Ma ( 2010 ) and Hardman ( 2019 ) showed that the positive effect of technology on students’ achievement depends on the pedagogical practices used by teachers. Schmid et al. ( 2014 ) reported that learning was best supported when students were engaged in active, meaningful activities with the use of technological tools that provided cognitive support. Tamim et al. ( 2015 ) compared two different pedagogical uses of tablets and found a significant moderate effect when the devices were used in a student-centered context and approach rather than within teacher-led environments. Similarly, Garzón and Acevedo ( 2019 ) and Garzón et al. ( 2020 ) reported that the positive results from the integration of AR applications could be attributed to the existence of different variables which could influence AR interventions (e.g., pedagogical approach, learning environment, and duration of the intervention). Additionally, Garzón et al. ( 2020 ) suggested that the pedagogical resources that teachers used to complement their lectures and the pedagogical approaches they applied were crucial to the effective integration of AR on students’ learning gains. Garzón and Acevedo ( 2019 ) also emphasized that the success of a technology-enhanced intervention is based on both the technology per se and its characteristics and on the pedagogical strategies teachers choose to implement. For instance, their results indicated that the collaborative learning approach had the highest impact on students’ learning gains among other approaches (e.g., inquiry-based learning, situated learning, or project-based learning). Ran et al. ( 2022 ) also found that the use of technology to design collaborative and communicative environments showed the largest moderator effects among the other approaches.

Hattie ( 2008 ) reported that the effective use of computers is associated with training teachers in using computers as a teaching and learning tool. Zheng et al. ( 2016 ) noted that in addition to the strategies teachers adopt in teaching, ongoing professional development is also vital in ensuring the success of technology implementation programs. Sung et al. ( 2016 ) found that research on the use of mobile devices to support learning tends to report that the insufficient preparation of teachers is a major obstacle in implementing effective mobile learning programs in schools. Friedel et al. ( 2013 ) found that providing training and support to teachers increased the positive impact of the interventions on students’ learning gains. Trucano ( 2005 ) argued that positive impacts occur when digital technologies are used to enhance teachers’ existing pedagogical philosophies. Higgins et al. ( 2012 ) found that the types of technologies used and how they are used could also affect students’ learning. The authors suggested that training and professional development of teachers that focuses on the effective pedagogical use of technology to support teaching and learning is an important component of successful instructional approaches (Higgins et al., 2012 ). Archer et al. ( 2014 ) found that studies that reported ICT interventions during which teachers received training and support had moderate positive effects on students’ learning outcomes, which were significantly higher than studies where little or no detail about training and support was mentioned. Fu ( 2013 ) reported that the lack of teachers’ knowledge and skills on the technical and instructional aspects of ICT use in the classroom, in-service training, pedagogy support, technical and financial support, as well as the lack of teachers’ motivation and encouragement to integrate ICT on their teaching were significant barriers to the integration of ICT in education.

School leadership and management

Management and leadership are important cornerstones in the digital transformation process (Pihir et al., 2018 ). Zheng et al. ( 2016 ) documented leadership among the factors positively affecting the successful implementation of technology integration in schools. Strong leadership, strategic planning, and systematic integration of digital technologies are prerequisites for the digital transformation of education systems (Ređep, 2021 ). Management and leadership play a significant role in formulating policies that are translated into practice and ensure that developments in ICT become embedded into the life of the school and in the experiences of staff and pupils (Condie & Munro, 2007 ). Policy support and leadership must include the provision of an overall vision for the use of digital technologies in education, guidance for students and parents, logistical support, as well as teacher training (Conrads et al., 2017 ). Unless there is a commitment throughout the school, with accountability for progress at key points, it is unlikely for ICT integration to be sustained or become part of the culture (Condie & Munro, 2007 ). To achieve this, principals need to adopt and promote a whole-institution strategy and build a strong mutual support system that enables the school’s technological maturity (European Commission, 2019 ). In this context, school culture plays an essential role in shaping the mindsets and beliefs of school actors towards successful technology integration. Condie and Munro ( 2007 ) emphasized the importance of the principal’s enthusiasm and work as a source of inspiration for the school staff and the students to cultivate a culture of innovation and establish sustainable digital change. Specifically, school leaders need to create conditions in which the school staff is empowered to experiment and take risks with technology (Elkordy & Lovinelli, 2020 ).

In order for leaders to achieve the above, it is important to develop capacities for learning and leading, advocating professional learning, and creating support systems and structures (European Commission, 2019 ). Digital technology integration in education systems can be challenging and leadership needs guidance to achieve it. Such guidance can be introduced through the adoption of new methods and techniques in strategic planning for the integration of digital technologies (Ređep, 2021 ). Even though the role of leaders is vital, the relevant training offered to them has so far been inadequate. Specifically, only a third of the education systems in Europe have put in place national strategies that explicitly refer to the training of school principals (European Commission, 2019 , p. 16).

Connectivity, infrastructure, and government and other support

The effective integration of digital technologies across levels of education presupposes the development of infrastructure, the provision of digital content, and the selection of proper resources (Voogt et al., 2013 ). Particularly, a high-quality broadband connection in the school increases the quality and quantity of educational activities. There is evidence that ICT increases and formalizes cooperative planning between teachers and cooperation with managers, which in turn has a positive impact on teaching practices (Balanskat et al., 2006 ). Additionally, ICT resources, including software and hardware, increase the likelihood of teachers integrating technology into the curriculum to enhance their teaching practices (Delgado et al., 2015 ). For example, Zheng et al. ( 2016 ) found that the use of one-on-one laptop programs resulted in positive changes in teaching and learning, which would not have been accomplished without the infrastructure and technical support provided to teachers. Delgado et al. ( 2015 ) reported that limited access to technology (insufficient computers, peripherals, and software) and lack of technical support are important barriers to ICT integration. Access to infrastructure refers not only to the availability of technology in a school but also to the provision of a proper amount and the right types of technology in locations where teachers and students can use them. Effective technical support is a central element of the whole-school strategy for ICT (Underwood, 2009 ). Bingimlas ( 2009 ) reported that lack of technical support in the classroom and whole-school resources (e.g., failing to connect to the Internet, printers not printing, malfunctioning computers, and working on old computers) are significant barriers that discourage the use of ICT by teachers. Moreover, poor quality and inadequate hardware maintenance, and unsuitable educational software may discourage teachers from using ICTs (Balanskat et al., 2006 ; Bingimlas, 2009 ).

Government support can also impact the integration of ICTs in teaching. Specifically, Balanskat et al. ( 2006 ) reported that government interventions and training programs increased teachers’ enthusiasm and positive attitudes towards ICT and led to the routine use of embedded ICT.

Lastly, another important factor affecting digital transformation is the development and quality assurance of digital learning resources. Such resources can be support textbooks and related materials or resources that focus on specific subjects or parts of the curriculum. Policies on the provision of digital learning resources are essential for schools and can be achieved through various actions. For example, some countries are financing web portals that become repositories, enabling teachers to share resources or create their own. Additionally, they may offer e-learning opportunities or other services linked to digital education. In other cases, specific agencies of projects have also been set up to develop digital resources (Eurydice, 2019 ).

Administration and digital data management

The digital transformation of schools involves organizational improvements at the level of internal workflows, communication between the different stakeholders, and potential for collaboration. Vuorikari et al. ( 2020 ) presented evidence that digital technologies supported the automation of administrative practices in schools and reduced the administration’s workload. There is evidence that digital data affects the production of knowledge about schools and has the power to transform how schooling takes place. Specifically, Sellar ( 2015 ) reported that data infrastructure in education is developing due to the demand for “ information about student outcomes, teacher quality, school performance, and adult skills, associated with policy efforts to increase human capital and productivity practices ” (p. 771). In this regard, practices, such as datafication which refers to the “ translation of information about all kinds of things and processes into quantified formats” have become essential for decision-making based on accountability reports about the school’s quality. The data could be turned into deep insights about education or training incorporating ICTs. For example, measuring students’ online engagement with the learning material and drawing meaningful conclusions can allow teachers to improve their educational interventions (Vuorikari et al., 2020 ).

Students’ socioeconomic background and family support

Research show that the active engagement of parents in the school and their support for the school’s work can make a difference to their children’s attitudes towards learning and, as a result, their achievement (Hattie, 2008 ). In recent years, digital technologies have been used for more effective communication between school and family (Escueta et al., 2017 ). The European Commission ( 2020 ) presented data from a Eurostat survey regarding the use of computers by students during the pandemic. The data showed that younger pupils needed additional support and guidance from parents and the challenges were greater for families in which parents had lower levels of education and little to no digital skills.

In this regard, the socio-economic background of the learners and their socio-cultural environment also affect educational achievements (Punie et al., 2006 ). Trucano documented that the use of computers at home positively influenced students’ confidence and resulted in more frequent use at school, compared to students who had no home access (Trucano, 2005 ). In this sense, the socio-economic background affects the access to computers at home (OECD, 2015 ) which in turn influences the experience of ICT, an important factor for school achievement (Punie et al., 2006 ; Underwood, 2009 ). Furthermore, parents from different socio-economic backgrounds may have different abilities and availability to support their children in their learning process (Di Pietro et al., 2020 ).

Schools’ socioeconomic context and emergency situations

The socio-economic context of the school is closely related to a school’s digital transformation. For example, schools in disadvantaged, rural, or deprived areas are likely to lack the digital capacity and infrastructure required to adapt to the use of digital technologies during emergency periods, such as the COVID-19 pandemic (Di Pietro et al., 2020 ). Data collected from school principals confirmed that in several countries, there is a rural/urban divide in connectivity (OECD, 2015 ).

Emergency periods also affect the digitalization of schools. The COVID-19 pandemic led to the closure of schools and forced them to seek appropriate and connective ways to keep working on the curriculum (Di Pietro et al., 2020 ). The sudden large-scale shift to distance and online teaching and learning also presented challenges around quality and equity in education, such as the risk of increased inequalities in learning, digital, and social, as well as teachers facing difficulties coping with this demanding situation (European Commission, 2020 ).

Looking at the findings of the above studies, we can conclude that the impact of digital technologies on education is influenced by various actors and touches many aspects of the school ecosystem. Figure  1 summarizes the factors affecting the digital technologies’ impact on school stakeholders based on the findings from the literature review.

Factors that affect the impact of ICTs on education

The findings revealed that the use of digital technologies in education affects a variety of actors within a school’s ecosystem. First, we observed that as technologies evolve, so does the interest of the research community to apply them to school settings. Figure  2 summarizes the trends identified in current research around the impact of digital technologies on schools’ digital capacity and transformation as found in the present study. Starting as early as 2005, when computers, simulations, and interactive boards were the most commonly applied tools in school interventions (e.g., Eng, 2005 ; Liao et al., 2007 ; Moran et al., 2008 ; Tamim et al., 2011 ), moving towards the use of learning platforms (Jewitt et al., 2011 ), then to the use of mobile devices and digital games (e.g., Tamim et al., 2015 ; Sung et al., 2016 ; Talan et al., 2020 ), as well as e-books (e.g., Savva et al., 2022 ), to the more recent advanced technologies, such as AR and VR applications (e.g., Garzón & Acevedo, 2019 ; Garzón et al., 2020 ; Kalemkuş & Kalemkuş, 2022 ), or robotics and AI (e.g., Su & Yang, 2022 ; Su et al., 2022 ). As this evolution shows, digital technologies are a concept in flux with different affordances and characteristics. Additionally, from an instructional perspective, there has been a growing interest in different modes and models of content delivery such as online, blended, and hybrid modes (e.g., Cheok & Wong, 2015 ; Kazu & Yalçin, 2022 ; Ulum, 2022 ). This is an indication that the value of technologies to support teaching and learning as well as other school-related practices is increasingly recognized by the research and school community. The impact results from the literature review indicate that ICT integration on students’ learning outcomes has effects that are small (Coban et al., 2022 ; Eng, 2005 ; Higgins et al., 2012 ; Schmid et al., 2014 ; Tamim et al., 2015 ; Zheng et al., 2016 ) to moderate (Garzón & Acevedo, 2019 ; Garzón et al., 2020 ; Liao et al., 2007 ; Sung et al., 2016 ; Talan et al., 2020 ; Wen & Walters, 2022 ). That said, a number of recent studies have reported high effect sizes (e.g., Kazu & Yalçin, 2022 ).

Current work and trends in the study of the impact of digital technologies on schools’ digital capacity

Based on these findings, several authors have suggested that the impact of technology on education depends on several variables and not on the technology per se (Tamim et al., 2011 ; Higgins et al., 2012 ; Archer et al., 2014 ; Sung et al., 2016 ; Haßler et al., 2016 ; Chauhan, 2017 ; Lee et al., 2020 ; Lei et al., 2022a ). While the impact of ICTs on student achievement has been thoroughly investigated by researchers, other aspects related to school life that are also affected by ICTs, such as equality, inclusion, and social integration have received less attention. Further analysis of the literature review has revealed a greater investment in ICT interventions to support learning and teaching in the core subjects of literacy and STEM disciplines, especially mathematics, and science. These were the most common subjects studied in the reviewed papers often drawing on national testing results, while studies that investigated other subject areas, such as social studies, were limited (Chauhan, 2017 ; Condie & Munro, 2007 ). As such, research is still lacking impact studies that focus on the effects of ICTs on a range of curriculum subjects.

The qualitative research provided additional information about the impact of digital technologies on education, documenting positive effects and giving more details about implications, recommendations, and future research directions. Specifically, the findings regarding the role of ICTs in supporting learning highlight the importance of teachers’ instructional practice and the learning context in the use of technologies and consequently their impact on instruction (Çelik, 2022 ; Schmid et al., 2014 ; Tamim et al., 2015 ). The review also provided useful insights regarding the various factors that affect the impact of digital technologies on education. These factors are interconnected and play a vital role in the transformation process. Specifically, these factors include a) digital competencies; b) teachers’ personal characteristics and professional development; c) school leadership and management; d) connectivity, infrastructure, and government support; e) administration and data management practices; f) students’ socio-economic background and family support and g) the socioeconomic context of the school and emergency situations. It is worth noting that we observed factors that affect the integration of ICTs in education but may also be affected by it. For example, the frequent use of ICTs and the use of laptops by students for instructional purposes positively affect the development of digital competencies (Zheng et al., 2016 ) and at the same time, the digital competencies affect the use of ICTs (Fu, 2013 ; Higgins et al., 2012 ). As a result, the impact of digital technologies should be explored more as an enabler of desirable and new practices and not merely as a catalyst that improves the output of the education process i.e. namely student attainment.

Conclusions

Digital technologies offer immense potential for fundamental improvement in schools. However, investment in ICT infrastructure and professional development to improve school education are yet to provide fruitful results. Digital transformation is a complex process that requires large-scale transformative changes that presuppose digital capacity and preparedness. To achieve such changes, all actors within the school’s ecosystem need to share a common vision regarding the integration of ICTs in education and work towards achieving this goal. Our literature review, which synthesized quantitative and qualitative data from a list of meta-analyses and review studies, provided useful insights into the impact of ICTs on different school stakeholders and showed that the impact of digital technologies touches upon many different aspects of school life, which are often overlooked when the focus is on student achievement as the final output of education. Furthermore, the concept of digital technologies is a concept in flux as technologies are not only different among them calling for different uses in the educational practice but they also change through time. Additionally, we opened a forum for discussion regarding the factors that affect a school’s digital capacity and transformation. We hope that our study will inform policy, practice, and research and result in a paradigm shift towards more holistic approaches in impact and assessment studies.

Study limitations and future directions

We presented a review of the study of digital technologies' impact on education and factors influencing schools’ digital capacity and transformation. The study results were based on a non-systematic literature review grounded on the acquisition of documentation in specific databases. Future studies should investigate more databases to corroborate and enhance our results. Moreover, search queries could be enhanced with key terms that could provide additional insights about the integration of ICTs in education, such as “policies and strategies for ICT integration in education”. Also, the study drew information from meta-analyses and literature reviews to acquire evidence about the effects of ICT integration in schools. Such evidence was mostly based on the general conclusions of the studies. It is worth mentioning that, we located individual studies which showed different, such as negative or neutral results. Thus, further insights are needed about the impact of ICTs on education and the factors influencing the impact. Furthermore, the nature of the studies included in meta-analyses and reviews is different as they are based on different research methodologies and data gathering processes. For instance, in a meta-analysis, the impact among the studies investigated is measured in a particular way, depending on policy or research targets (e.g., results from national examinations, pre-/post-tests). Meanwhile, in literature reviews, qualitative studies offer additional insights and detail based on self-reports and research opinions on several different aspects and stakeholders who could affect and be affected by ICT integration. As a result, it was challenging to draw causal relationships between so many interrelating variables.

Despite the challenges mentioned above, this study envisaged examining school units as ecosystems that consist of several actors by bringing together several variables from different research epistemologies to provide an understanding of the integration of ICTs. However, the use of other tools and methodologies and models for evaluation of the impact of digital technologies on education could give more detailed data and more accurate results. For instance, self-reflection tools, like SELFIE—developed on the DigCompOrg framework- (Kampylis et al., 2015 ; Bocconi & Lightfoot, 2021 ) can help capture a school’s digital capacity and better assess the impact of ICTs on education. Furthermore, the development of a theory of change could be a good approach for documenting the impact of digital technologies on education. Specifically, theories of change are models used for the evaluation of interventions and their impact; they are developed to describe how interventions will work and give the desired outcomes (Mayne, 2015 ). Theory of change as a methodological approach has also been used by researchers to develop models for evaluation in the field of education (e.g., Aromatario et al., 2019 ; Chapman & Sammons, 2013 ; De Silva et al., 2014 ).

We also propose that future studies aim at similar investigations by applying more holistic approaches for impact assessment that can provide in-depth data about the impact of digital technologies on education. For instance, future studies could focus on different research questions about the technologies that are used during the interventions or the way the implementation takes place (e.g., What methodologies are used for documenting impact? How are experimental studies implemented? How can teachers be taken into account and trained on the technology and its functions? What are the elements of an appropriate and successful implementation? How is the whole intervention designed? On which learning theories is the technology implementation based?).

Future research could also focus on assessing the impact of digital technologies on various other subjects since there is a scarcity of research related to particular subjects, such as geography, history, arts, music, and design and technology. More research should also be done about the impact of ICTs on skills, emotions, and attitudes, and on equality, inclusion, social interaction, and special needs education. There is also a need for more research about the impact of ICTs on administration, management, digitalization, and home-school relationships. Additionally, although new forms of teaching and learning with the use of ICTs (e.g., blended, hybrid, and online learning) have initiated several investigations in mainstream classrooms, only a few studies have measured their impact on students’ learning. Additionally, our review did not document any study about the impact of flipped classrooms on K-12 education. Regarding teaching and learning approaches, it is worth noting that studies referred to STEM or STEAM did not investigate the impact of STEM/STEAM as an interdisciplinary approach to learning but only investigated the impact of ICTs on learning in each domain as a separate subject (science, technology, engineering, arts, mathematics). Hence, we propose future research to also investigate the impact of the STEM/STEAM approach on education. The impact of emerging technologies on education, such as AR, VR, robotics, and AI has also been investigated recently, but more work needs to be done.

Finally, we propose that future studies could focus on the way in which specific factors, e.g., infrastructure and government support, school leadership and management, students’ and teachers’ digital competencies, approaches teachers utilize in the teaching and learning (e.g., blended, online and hybrid learning, flipped classrooms, STEM/STEAM approach, project-based learning, inquiry-based learning), affect the impact of digital technologies on education. We hope that future studies will give detailed insights into the concept of schools’ digital transformation through further investigation of impacts and factors which influence digital capacity and transformation based on the results and the recommendations of the present study.

Acknowledgements

This project has received funding under Grant Agreement No Ref Ares (2021) 339036 7483039 as well as funding from the European Union’s Horizon 2020 Research and Innovation Program under Grant Agreement No 739578 and the Government of the Republic of Cyprus through the Deputy Ministry of Research, Innovation and Digital Policy. The UVa co-authors would like also to acknowledge funding from the European Regional Development Fund and the National Research Agency of the Spanish Ministry of Science and Innovation, under project grant PID2020-112584RB-C32.

Data availability statement

Declarations.

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International business students studying accountancy: Can technology be used to develop a deeper approach to learning taxation and law

30 Pages Posted:

Fiona Martin

UNSW Business School

Kayleen Manwaring

University of New South Wales (UNSW) - UNSW Law & Justice

Date Written: August 09, 2024

University students across the world increasingly come from diverse backgrounds. Australian data from 2023 states that there are approximately 440,000 overseas students studying in the higher education (university) system. Whilst this diversity considerably enriches university communities, it also necessitates that increased support structures are put in place by academic and administrative staff for those students who have diverse English language abilities, cultural backgrounds and academic ability. We as university lecturers who teach accountancy students therefore need to be proactive in developing new strategies that will meet changing and diverse demands without conflicting with established academic values. This paper examines two unique approaches to learning and teaching that each use technology to assist accountancy students to a deeper understanding of the learning material they are required to grapple with. The first uses adaptive E-Learning (AEL) as developed by the software team Smart Sparrow to teach aspects of income tax law to accounting students. The second concentrates on how technological approaches can be used to enrich face-to-face learning experiences and encourage active engagement and the development of critical thinking, independent learning, and oral and aural language skills.

Keywords: legal education, e-Learning, mind maps

Suggested Citation: Suggested Citation

Fiona Anne Martin (Contact Author)

Unsw business school ( email ).

UNSW Business School High St Sydney, NSW 2052 Australia

University of New South Wales (UNSW) - UNSW Law & Justice ( email )

Kensington, New South Wales 2052 Australia

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Jessica Grose

What teachers told me about a.i. in school.

By Jessica Grose

Opinion Writer

Leila Wheless, a North Carolina teacher who has been an educator since 1991, tried to keep “an open heart” about using artificial intelligence in her middle school English and language arts classroom. She reviewed the guidance of her state’s generative A.I. “ recommendations and considerations ” for public schools. But the results of her students’ A.I. use were dispiriting.

“For one particular assignment related to the novel ‘Persepolis,’ I had students research prophets,” Wheless explained, because the main character fantasizes about being a prophet. But, she told me via email, internet searches that incorporated A.I.:

Gave students jewels such as “the Christian prophet Moses got chocolate stains out of T-shirts” — I guess rather than Moses got water out of a rock(?). And let me tell you, eighth graders wrote that down as their response. They did not come up to me and ask, “Is that correct? Moses is known for getting chocolate stains out of T-shirts?” They simply do not have the background knowledge or indeed the intellectual stamina to question unlikely responses.

After I wrote a series in the spring about tech use in K-12 classrooms , I asked teachers about their experiences with A.I. because its ubiquity is fairly new and educators are just starting to figure out how to grapple with it. I spoke with middle school, high school and college instructors, and my overall takeaway is that while there are a few real benefits to using A.I. in schools — it can be useful in speeding up rote tasks like adding citations to essays and doing basic coding — the drawbacks are significant.

The biggest issue isn’t just that students might use it to cheat — students have been trying to cheat forever — or that they might wind up with absurdly wrong answers, like confusing Moses with Mr. Clean. The thornier problem is that when students rely on a generative A.I. tool like ChatGPT to outsource brainstorming and writing, they may be losing the ability to think critically and to overcome frustration with tasks that don’t come easily to them.

Sarah Martin, who teaches high school English in California, wrote to me saying, “Cheating by copying from A.I. is rampant, particularly among my disaffected seniors who are just waiting until graduation.”

When I followed up with her over the phone, she said that it’s getting more and more difficult to catch A.I. use because a savvier user will recognize absurdities and hallucinations and go back over what a chatbot spits out to make it read more as if the user wrote it herself. But what troubles Martin more than some students’ shrewd academic dishonesty is “that there’s just no grit that’s instilled in them. There’s no sense of ‘Yes, you’re going to struggle, but you’re going to feel good at the end of it.’”

She said that the amount of time her students are inclined to work on something that challenges them has become much shorter over the seven years she’s been teaching. There was a time, she said, when a typical student would wrestle with a concept for days before getting it. But now, if that student doesn’t understand something within minutes, he’s more likely to give up on his own brain power and look for an alternative, whether it’s a chatbot or asking a friend for help.

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