mobile applications for education processes

Journal of New Approaches in Educational Research

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Moving Learning: A Systematic Review of Mobile Learning Applications for Online Higher Education Moviendo el aprendizaje: revisión sistemática del uso de los móviles para la enseñanza superior en línea

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Technological revolutionary changes have boosted mobile learning’s evolution from supplementary material for teaching to a flexible, strategic, and convenient resource, driving new paths in higher education. With global increases in wireless internet access and the advent of highly functional smartphones and tablets, which have impacted the rise in mobile device ownership, mobile learning has expanded its applications as a direct way to implement tailored learning settings. Notably, during the COVID-19 pandemic, together with other educational technologies, it became a solicited tool in remote education. In this systematic review, we will explore how educators and researchers have been documenting the development and impact of mobile learning tools in the teaching and learning process since the COVID-19 outbreak. Results show that, embedded with online higher education programs, mobile learning has empowered interaction in content creation, communication, and collaboration between learners and instructors, significantly impacting learning effectiveness. Moreover, although this technology is well established in higher education, it remains attractive for educators who actively use it because of its pedagogic potential.

Revolucionarios cambios tecnológicos han impulsado la evolución del aprendizaje con móviles. Estos dispositivos, han pasado de ser un material complementario para la enseñanza a convertirse en un recurso flexible, estratégico y práctico, impulsando nuevos caminos en la educación superior. Con el incremento global del acceso a Internet, la llegada de altamente funcionales smartphones y tabletas y el aumento de la adquisición de estos dispositivos, el aprendizaje con móviles ha ampliado sus aplicaciones como forma directa de implementar entornos educativos personalizados. En particular, desde el estallido del COVID-19, junto con otras tecnologías educativas, se convirtió en una herramienta muy utilizada en la educación a distancia. En esta revisión sistemática, exploraremos cómo los educadores e investigadores están documentando el desarrollo y el impacto de las herramientas de aprendizaje con móviles en el proceso de enseñanza durante la pandemia. Los resultados muestran que, integrado en los programas de educación superior en línea, el uso de los móviles con fines educativos potenció la interacción en la creación de contenidos, la comunicación y la colaboración entre alumnos e instructores, lo que repercutió significativamente en la eficacia del aprendizaje. Además, aunque esta tecnología está bien asentada en la enseñanza superior, sigue siendo atractiva para los educadores, que la utilizan activamente por su potencial pedagógico

INTRODUCTION

Mobile learning (also known as m-learning) has been characterized as a multifaceted process involving theoretical-based pedagogical approaches to tackle educational requirements ( Hao, Dennen, & Mei, 2017 ). Revolutionary changes in the 1980s, with the introduction of pocket and handheld computers, have been recognized as the first steps of what we today consider mobile learning ( Educause, 2019 ). With time, the functional advantages of mobile devices such as smartphones and tablets, compared to laptops or desktop computers, made them a solicited resource for teaching-learning ( Mâță et al., 2021 ). Likewise, the integration of smartphones and tablets into learning processes, the availability of powerful and intuitive mobile applications, and accelerating mobile internet connection have facilitated the creation and sharing of content ( Adanır & Muhametjanova, 2021 ).

The responsive design of mobile learning content available on all platforms also drives its success in online higher educational contexts ( Yu, Yan, & He, 2022 ). Understanding how to structure material for shorter attention spans, choosing optimized mobile-friendly formats, and maintaining active communication with students are key factors of faculty development ( Minichiello et al., 2021 ; O'Connor & Andrews, 2018 ; Pham & Chen, 2018 ). These design tenets promote a more consistent user experience across platforms and devices within the academic environment.

Unquestionably, integrating mobile devices as an educational asset also exposes the gap between those who can afford to have rapid access to the internet connection and those who cannot. In 2021 nearly 15 billion mobile devices were operating worldwide ( Radianti, Majchrzak, Fromm, & Wohlgenannt, 2020 ). However, up to 3.2 billion people did not have access to mobile internet services, even though they lived in areas with a mobile broadband network ( GSMA, 2022 ). The usage gap is notable in low- and middle-income countries; for example, up to 40% of Latin America and the Caribbean population and 53% of the population in Sub-Saharan Africa. In contrast, North America represents 24%, and Europe and Central Asia represent 26% ( Bahia & Delaporte, 2020 ). Moreover, there are still considerable differences in average mobile connection speeds worldwide, with the United Arab Emirates (125 Mbps), for example, being 25 times faster than Cuba (5 Mbps). Among other factors, this has a notable impact on the implementation of mobile learning initiatives, including those integrated with XR and AI resources via mobile connections ( Kemp, 2022 ).

Mobile learning has been a resource of attraction for researchers actively investigating its academic potential for many years ( Crompton & Burke, 2017 ; Liaw, Hatala, & Huang, 2010 ; Matzavela & Alepis, 2021 ; Motiwalla, 2007 ; Yu et al., 2022 ). Especially during the COVID-19 pandemic, mobile learning became a solicited tool in remote education ( Dhawan, 2020 ; Muthuprasad, Aiswarya, Aditya, & Jha, 2021 ).

In this systematic review, we will explore how educators and researchers have been documenting the development and impact of mobile learning tools in the teaching and learning process since the COVID-19 outbreak. To that end, we have designed the following questions:

RQ1. What is the geographical distribution of the publications, and which languages were used?

RQ2. Which sources are most frequently used for publication, and who are the most cited authors in the literature?

RQ3.Which devices, data collection, and research design methods were set out to support mobile learning and teaching, and within which disciplines are they integrated?

RQ4. What is the scope and nature of mobile learning applications in online higher education?

To address the research questions defined in this systematic review, we will localize, synthesize and analyze peer-reviewed publications with a precise, standardized, and reproducible search strategy following the Preferred Reporting Items for Systematic reviews and Meta-Analyses system (PRISMA; Page et al., 2021 ).

Additionally, we will employ the R program litsearchr to systematically define our search terms ( Grames, Stillman, Tingley, & Elphick, 2019 ). In order to compile a set of keywords relevant to our review, this package will run the Rapid Automatic Keyword Extraction (RAKE) algorithm ( Rose, Engel, Cramer, & Cowley, 2010 ), identifying keywords from the titles and abstracts from publications and extracting the author-tagged keywords.

A "naive search" was conducted on 6 June 2022 in Scopus, Web of Science, and EBSCO Education sources with no date restrictions to gather relevant publications, including the following terms (Figure 1): (("higher education" OR "college" OR "undergrad" OR "graduate" OR "postgrad") AND ("mobile application" OR "virtual reality" OR "augmented reality" OR "mixed reality" OR "haptic technology" OR "artificial intelligence") AND ("e-learning" OR "online learning" OR "virtual learning" OR "distance learning" OR "remote learning")). As a result, we identified records from Scopus (n = 2984), Web of Science (n = 529), and EBSCO Education sources (n = 24) and removed duplicated publications (n = 1026).

Potential keywords for the systematic review were extracted from the publications retrieved using the RAKE algorithm (500) and tagged method (523). Additionally, we quantitatively assessed the strength of the keywords compiled. Relevant terms frequently appeared with other terms from the set, and non-essential ones appeared associated with others (147 keywords removed). Finally, to define the search strategy for the Boolean searches in English and Spanish, the remaining keywords were organized into three groups: Emerging technologies, Education level, and Learning setting (Table 1).

Furthermore, we collected ten key publications to test the accuracy and recall of the systematic review search strategy using Scopus, Web of Science, and EBSCO Education. We were able to retrieve the ten papers selected using the search terms defined, confirming that we could run the final search string for the systematic review.

Final Search, Screening, Coding, and Data Extraction

Based on the Boolean search terms outlined (Table 1) and the inclusion and exclusion criteria (Table 2), the final search was limited to the three abovementioned databases, including titles, abstracts, and keywords of publications. A total of 424 initial observations were identified. This list was narrowed down after removing 70 duplicates.

Two further articles were excluded because they were accessible neither through journal publications nor by contacting authors. Afterwards, publications were filtered to those peer-reviewed research articles, reviews, and book chapters submitted after the COVID-19 outbreak in March 2020 (70 articles excluded). We set further exclusion criteria by only including those focused on mobile learning (181 papers discarded) in online higher education (46 publications removed).

Fifty-five publications remained for screening on full text and coding (Figure 1). We coded articles based on a hierarchical ontology of associations between subjects (Table 2). The codes used comprised: the author's name, year of publication, source name, times cited, country of origin of the first author, type of publication (research article, review, or book chapter), the language used, data collection method, type of mobile device, research design, technology application in higher education, domain, and scope of application. Data analyses and graphics were done using the R package tidyr ( Wickham, Vaughan, & Girlich, 2023 ), dplyr ( Wickham, François, Henry, Müller, & Vaughan, 2023 ), tidyverse ( Wickham et al., 2019 ), bibliometrix ( Aria & Cuccurullo, 2017 ), maps ( Becke, Wilks, Brownrigg, Minka, & Deckmyn, 2021 ), ggplot2 ( Wickham, 2016 ), ggraph ( Pedersen, 2021 ), and igraph ( Csárdi & Nepusz, 2006 ).

In this systematic review, we defined a set of categories to code the publications. First, we wanted to know the Type of device reported in each study. We identified four groups: 1) mobile devices (used as a generic term), 2) mobile phones (also encompassing smartphones), 3) laptops, mobile phones, and tablets, and 4) mobile phones and tablets.

In terms of Research design , we considered a combination of the Creswell and Creswell (2017) and Wendler (2012) frameworks suitable for our systematic review scope, including 1) quantitative, 2) qualitative, 3) mixed methods, and 4) design-oriented research.

The Data collection method followed by the authors was distributed across eight groups assigned following Cohen, Manion, and Morrison (2018) , Creswell and Creswell (2017) , Wendler (2012) , and Paré, Trudel, Jaana, and Kitsiou (2015) . Each article screened was assigned to one of the following categories: 1) case study, 2) development, 3) experimental design, 4) focus group and interview, 5) literature review, and 6) survey, along with a combination of methods such as 7) interview and survey, and 8) literature review, interview, and survey.

Moreover, we were interested in how mobile learning was applied in online higher education. To that end, we further analyzed only the primary research extracted by customizing eight categories following Crebert, Bates, Bell, Patrick, and Cragnolini (2004) , Zawacki-Richter, Marín, Bond, and Gouverneur (2019) , and Radianti et al. (2020) . A description can be found in Table X, and it includes 1) Adaptive learning systems and Personalization, 2) Analytical and Practical knowledge, 3) Assessment and Evaluation, 4) Behavioral and Psychological impact, 5) Best practices, 6) Communication and Collaboration, 7) Learning a language, and 8) Profile and Prediction.

Scope of Application

As part of the coding process, we aimed to assign, where possible, each article to a particular discipline. To that end, as indicated in Table 3, we followed and adapted the list of groups and fields provided by the UNESCO International Standard Classification of Education ( UNESCO Institute for Statistics, 2012 ). Additionally, we created the category No particular domain to group those papers that, due to the interdisciplinary nature of the study or the lack of additional details, did not fall within a specific discipline.

RQ1. What is the Geographical Distribution of the Publications, and Which Languages Were Used?

From mapping the literature reviewed, we recognized a progressive increase in publications addressing mobile learning resources in higher education over the past two years. Notably, 91% of the publications retrieved were research articles, and 9% were literature reviews. We traced 55 published pieces of research across 27 countries (Figure 2). The implementation of mobile learning for teaching-learning practices in higher education was localized to four continents. Figure 2 shows that most of the publications came from Asia (62%), followed by Europe (22%), Latin America (15%) and, to a lesser extent, Africa (2%). China was the country showing the largest publication productivity in mobile learning (n = 8, e.g., Cui, 2022 ; Ding et al., 2020 ; Fan et al., 2022 ; Lin et al., 2021 ; Yu et al., 2022 ). This trend was followed by Spain (n = 6; e.g., Navandar et al., 2021 ; Romero-Rodriguez et al., 2020 ; Verdes et al., 2021 ), Saudi Arabia (e.g., Almaiah et al., 2022 ; Iqbal et al., 2020 ) and India (n = 5; e.g., Mubayrik & Alabbad, 2021 ; Neffati et al., 2021 ). On the opposite side, for countries such as Ghana ( Yeboah & Nyagorme, 2022 ), Cyprus ( Cavus, 2020 ), Ecuador ( Rodríguez Muñoz & Mieres, 2020 ), and Norway ( Egilsdottir et al., 2021 ), only one publication was retrieved for each.

Furthermore, in Figure 3 the yearly contribution in both languages can be seen. A large majority (93%) of the publications mapped were published in English. Most were published in 2021, closely followed by those from the following year. In contrast, only 7% of the screened papers were in Spanish, and these were issued between 2020 and 2022 ( Borroto, Medina Olazabal, & Fonseca Montes E Oca, 2021 ; Rodríguez Muñoz & Formoso Mieres, 2020 ; Salas-Rueda, Ramírez-Ortega, Eslava-Cervantes, Castañeda-Martínez, & De-La-Cruz-Martínez, 2022 ; Vigil García et al., 2020 ).

RQ2. Which Sources Are Most Frequently Used for Publication, and Who are the Most Cited Authors in the Literature?

Figure 4 shows the journals most frequently found in our database with articles published between 2020 and the current year. At the top of the list were Education and Information Technologies (n = 5), followed by Sustainability (n = 4) and Electronics (n = 3). With two articles each, we also found IEEE Access, International Journal of Emerging Technologies in Learning, International Journal of Interactive Mobile Technologies, Revista Conrado, and Wireless Communications and Mobile Computing. The remaining 33 sources were only represented by one article in our analysis.

To get an updated picture of the most cited authors, we returned to the online databases on 26 August and revised the number of citations received by each of the publications reviewed. In this case, two research papers published in 2020 led the way: Romero-Rodriguez et al. (2020) with 35 citations and Ding et al. (2020) with 33 citations. They were closely followed by ( Akour, Alshurideh, Kurdi, Ali, & Salloum, 2021 ), cited 26 times. The Sankey diagram displayed in Figure 4 shows the interconnected relationship between the ten most cited authors, the keywords most frequently found in the articles, and the journals where they were published.

RQ3.Which Devices, Data Collection, and Research Design Methods Were Set Out to Support Mobile Learning and Teaching, and Within Which Disciplines Are They Integrated?

A matter relevant to this review was to identify the type of device reported in the literature analyzed. Over half of the papers reviewed (56%) indicated mobile phone use in mobile learning activities (Figure 5a). Notably, 28 of these papers specifically reported using smartphones. We also found that in 20% of the cases, authors used mobile device as a generic term without further clarification. Moreover, authors frequently combined several terms, such as mobile phones and tablets in 13% of records retrieved. Similarly, the use of laptops, mobile phones, and tablets was reported in 11% of the cases.

Furthermore, we traced the association between data collection and research design methods according to each type of device identified (Figure 5b). A majority of the papers (45%) focused on mobile learning were quantitative-based combined with a survey approach ( Akour et al., 2021 ; Almaiah et al., 2022 ; Yuan, Tan, Ooi, & Lim, 2021 ). The authors implemented a qualitative strategy in 25% of the studies analyzed and used the following as collection methods: surveys ( Sooryah & Soundarya, 2020 ; Vigil García et al., 2020 ), literature reviews ( Gupta, Khan, & Agarwal, 2021 ) case studies ( Borroto et al., 2021 ; Gurevych et al., 2021 ), and focus groups and interview ( Pramana et al., 2020 ). Only 7% of the publications reviewed used a mixed methods approach paired with a literature review, interviews, and surveys. Likewise, only 7% of the research was design-oriented and used development approaches for collecting data ( Ding et al., 2020 ; Márquez-Díaz, 2020 ; Verdes et al., 2021 ; X. Zhang, 2022 ).

RQ4. What Is the Scope and Nature of Mobile Learning Applications in Online Higher Education?

Figure 6shows the scope of application of research articles distributed across the types of devices identified. Particularly when considering the use of mobile phones, Engineering (n = 7; e.g., Diaz-Nunez et al., 2021 ; Laurens-Arredondo, 2022 ), Humanities (n = 6; e.g., Lan, 2022 ; Ugur-Erdogmus & Cakir, 2022 ), and Business and Administration (n = 5; e.g., Thedpitak & Somphong, 2021 ; Voshaar et al., 2022 ) predominated among all disciplines analysed. By looking in detail at the chart, it can be seen that publications reporting the use of either mobile devices (in general terms) or combined applications of laptops, mobile phones, and tablets are clustered together in the centre of the radar with one or two publications each across Arts ( Cui, 2022 ), Communication and Information ( Stephens, Rudiger, & Faires, 2021 ), Education Science ( Romero-Rodriguez et al., 2020 ), Sciences ( Borroto et al., 2021 ), Social Sciences ( L. Zhang & He, 2022 ), and Sports ( Ding et al., 2020 ). Notably, the four series of devices categorized had research papers where no particular domain or specific discipline was outlined, as illustrated in Figure 6 ( Almaiah et al., 2022 ; Althunibat, Almaiah, & Altarawneh, 2021 ; Antee, 2021 ).

Further to the above, using the eight categories described in Table 4, we assessed the relationship between the scope and the nature of mobile learning applications in the 50 research articles analyzed. The nature and aim of some studies coincided in part with multiple categories. In those cases, we assigned them to the one where their applicability is most significant.

Adaptive Learning Systems and Personalization

Research articles within this scope accounted for a significant proportion (22%) of those analyzed. Three studies were included in Humanities (Figure 7); two focused on History-related topics ( Sarkadi, Cahyana, & Paristiowati, 2020 ; Ugur-Erdogmus & Cakir, 2022 ), and the other on mobile application development to reduce difficulties in listening to lectures online in a foreign language ( Sooryah & Soundarya, 2020 ). We retrieved two Engineering-related publications. The first presented the design of a virtual world to make student and teacher access to knowledge through mobile learning more accessible and adaptative ( Márquez-Díaz, 2020 ). The second one reported the creation of an augmented reality platform for improving mobile e-learning in software engineering ( Neffati et al., 2021 ). In this same line, the paper by ( Cavus, 2020 ) tested a novel unified mobile system with instructors and students from Education, Engineering, Law, and Languages to customize interactive teaching activities.

A few publications supported mobile learning implemented with XR technologies. Two were in Science-related disciplines, one for teaching invertebrate zoology online ( Verdes et al., 2021 ) and the other for learning physics ( Gurevych et al., 2021 ). Ding et al. (2020) relied on virtual reality and mobile learning to improve physical education. Likewise, Eldokhny and Drwish (2021) assessed the effectiveness of augmented reality in online distance learning to support academic achievement in Computer Science education. Finally, an artificial neural network algorithm ( X. Zhang, 2022 ) found that a personalized mobile learning system may supplement and optimize the learning experience compared to traditional teaching.

Best Practices

This category accounted for 14% of all research articles reviewed. The scope of the application was not specified in the three publications (Figure 7). Almaiah et al. (2022) explored quality impacting mobile learning usage. At the same time, Coskun-Setirek and Tanrikulu (2021) presented a guideline for sustainable education with mobile learning initiatives. Finally, Althunibat et al. (2021) highlighted the benefits of institutional policy, change management, and top management support in the usability of mobile learning systems.

Interestingly, the two papers retrieved within the Education Science scope focused on advancing and applying mobile applications from different perspectives and regions. The results of Salas-Rueda et al. (2022) regarding the Innovation in University Teaching diploma in Mexico revealed the positive influence on student engagement and academic activities of introducing web games and mobile devices in teaching-learning practices, while Romero-Rodriguez et al. (2020) investigated the level of implementation of mobile learning in Spanish universities and the sociodemographic features impacting the advancement of best teaching practices. Following a similar trend, Teymurova et al. (2020) examined university teacher integration levels in mobile entrepreneurial learning. The final publication coded within this category analyzed student perceptions of mobile devices in the Library and Information Science course, using this information to design a mobile-friendly training program ( Stephens et al., 2021 ).

Profile and Prediction

14% of research papers coded fell within this category and were distributed across multiple disciplines. As illustrated in Figure 7, three articles looked at combined approaches for predicting technology acceptance and usability—the first implemented mobile learning and XR in a Psychology class ( Sprenger & Schwaninger, 2021 ). In the second, machine learning was employed to predict the usefulness, effectiveness, efficiency, and acceptance of mobile learning, although no specific application domain was specified ( Almaiah, Almomani, Al-Khasawneh, & Althunibat, 2021 ). The third study assessed Ghanaian distance learners' acceptance of WhatsApp as an educational tool at the University of Education during the pandemic ( Yeboah & Nyagorme, 2022 ).

The three remaining publications addressed matters linked to Business and Administration ( Herrador-Alcaide et al., 2020 ) and Journalism, Communication and Information ( Humida, Mamun, & Keikhosrokiani, 2021 ). Yuan et al. (2021) reported that learning content quality, user interface, and connectivity are the leading drivers influencing students' perceptions, ease of use and experience when using mobile learning. Meanwhile, L. Zhang and He (2022) proposed a machine learning algorithm to optimize and monitor student performance in Ideological and Political Education using mobile learning during the pandemic. To a lesser extent, with only nine publications retrieved, mobile learning also appeared in higher education teaching and learning.

Behavioural and Psychological Impact

Five research articles did not centre on one specific domain. Akour et al. (2021) applied machine learning algorithms to predict the benefits of using mobile learning platforms during the pandemic (Figure 7). After analyzing a dataset of 10,000 college students, Lin et al. (2021) suggested that mobile learning and news applications positively impact academic development while playing mobile games, using social media, listening to music and watching videos, and entertainment book-reading applications have negative implications, whilse Fan et al. (2022) highlighted attitude, need, emotion, ability, and reinforcement as essential characteristics in improving mobile learning motivation in higher education students. Following this line, Alturki and Aldraiweesh (2022) , using a technology acceptance model to evaluate satisfaction, behavioural intention, and perceptions, found that using mobile learning had an excellent and constructive influence on higher education students during the COVID-19 pandemic. Looking in the opposite direction, Loh et al. (2021) drew attention to the antecedents and consequences of technostress and fatigue on learners' intention to use mobile learning via social media.

The other two papers coded within this category relied on mobile learning, exploring, respectively, the drivers influencing its adoption in students from the College of Information Technology ( Almaiah et al., 2022 ), and combining mobile learning and augmented reality to explore their positive implications for motivation and education in Engineering-related programs ( Laurens-Arredondo, 2022 ).

Communication and Collaboration

In this category, the mapping of application domains of mobile learning was distributed across heterogenic disciplines in six research papers (Figure 7). Three articles used mobile learning as a resource for videoconferencing applications and instant messaging applications, strengthening interaction, communication and collaborative learning during teaching and learning processes in Engineering ( Diaz-Nunez et al., 2021 ; Kumar et al., 2022 ) and Medicine students ( Iqbal et al., 2020 ). One example can be taken from Diaz-Nunez et al. (2021), who found that students used mobile devices to access online learning activities and virtual classes to cope with learning and daily life during the pandemic. Similar applications were reported by Pramana et al. (2020) in a study conducted across 40 universities in Indonesia, although no specific domain was mentioned. The fifth paper added to this group investigated the effect of flipped teaching on cognitive load in online learning when using mobile devices in a graphic design course ( Chen, Fan, & Fang, 2021 ). Rodríguez Muñoz and Formoso Mieres (2020) noticed increased knowledge sharing, reconfiguration and reorganization of learning during the pandemic when using YouTube and WhatsApp with students of Professional Ethics, Entrepreneurship and Innovation.

Learning a Language

Figure 7 displays the emerging technologies and their corresponding application domains extracted from the research papers reviewed. In terms of language learning, mobile learning was favoured by most authors in three different disciplines. Three articles were classified within the Humanities disciplines. The first one showed the positive effects of mobile-assisted pronunciation training on students majoring in English Lan (2022) . The second focused on Japanese language learners, identifying three different types of students and investigating the critical factors pushing them to continue using language learning apps ( Huang & Chueh, 2022 ). The third, Vigil García et al. (2020) embedded WhatsApp in BA Education Major Foreign Languages activities to enhance communicative, interactive and intercultural competence in the teaching-learning process of the English language. Borroto et al. (2021) reported the application of mobile learning resources for teaching Biology online in Spanish for non-Spanish Speakers. Following this trend, Thedpitak and Somphong (2021) highlighted positive attitudes toward learning English as a foreign language using mobile applications among Thai students.

Assessment and Evaluation

Online education has benefited from mobile learning assessments and evaluations during the COVID-19 pandemic, as noted in the 12 articles assigned to this category in this literature review (Figure 7). Students frequently use smartphones in their daily lives and are progressively integrating them as assessment and evaluation resources in online education. Four papers using mobile learning were coded in this category. The first introduced a mobile educational application providing theoretical knowledge and question-based tests for computer engineering undergraduate students ( Kayaalp & Dinc, 2022 ). Singh et al. (2021) developed a progressive model calibrating the difficulty level based on learner understanding in Computer Science education, which will prepare institutions for the transition from paper-based to mobile-based online tests. Voshaar et al. (2022) measured how a gamified mobile learning application influenced exam success on a course in the field of Business and Administration Studies. The fourth study evaluated the change in undergraduate Sports Science course perception when using Instagram as a learning medium and the benefits of doing assignments via social networks ( Navandar et al., 2021 ).

Analytical and Practical Knowledge

16% of the research articles reviewed were coded within this category. As shown in Figure 7, one study focused on improving learner programming skills in Computer Engineering education Mir and Llueca (2020) . Egilsdottir et al. (2021) explored the application of mobile learning tools to enhance skills and knowledge transfer and reduce the gap between theory and practice in nursing education. Cui (2022) delved into the potential of using augmented reality and mobile applications in acquiring piano skills, providing a novel opportunity to revolutionize Arts education.

Mobile learning has progressively evolved from an in-class and asynchronous learning supportive resource to a critical part of the learning experience ( Educause, 2019 ; Gupta et al., 2021 ). Mainly influenced by the global increase in wireless internet access, which has impacted the rise in mobile device ownership, mobile learning has become a direct way to implement personalized learning settings ( Cavus, 2020 ; Neffati et al., 2021 ; Verdes et al., 2021 ).

The evidence from this systematic review indicates that an increasing number of mobile educational projects are actively being integrated into online higher education, teaching and learning, specifically since March 2020. The preferred use of mobile phones for mobile teaching and learning activities correlates with findings previously reported by Crompton and Burke (2017) and Wu et al. (2012) . Moreover, the publications reviewed suggest that learners retain more knowledge and are more interested in completing the assigned exercises when they feel inspired to learn. In this sense, significant technological advances play a relevant role in contributing to elevating instructional design so that educational materials that are more specifically applicable are provided to students at their appropriate level of learning.

The advent of highly functional smartphones and tablets has increased the preference for using these devices over laptops or computers in countries with emerging economies ( Diaz-Nunez et al., 2021 ; Márquez-Díaz, 2020 ; Mubayrik et al., 2021 ; Pramana et al., 2020 ; Sooryah & Soundarya, 2020 ). Using such devices helped learners to stay connected to academic activities and communicate with teachers and classmates during the COVID-19 pandemic. Despite the usage gap in low- and middle-income countries, there is a noticeable increase in the implementation of mobile learning resources ( Borroto et al., 2021 ; Diaz-Nunez et al., 2021 ; Humida et al., 2021 ; Rodríguez Muñoz & Formoso Mieres, 2020 ).

Based on previous experience and following experiments in universities supporting distance and online learning formats, many higher education institutions have introduced (or expanded) their mobile learning courses, allowing learners to continue their academic activities while shifting from face-to-face to virtual forms. This solution has empowered interaction in content creation, communication, and collaboration between learners and instructors and significantly impacted learning effectiveness ( Iqbal et al., 2020 ; Pramana et al., 2020 ).

Mobile learning has progressively evolved from supplementary material for teaching to a flexible, strategic, and convenient resource, driving new paths in higher education. Its acceptance and adoption are growing in higher education, with it being an easy, convenient, and flexible way to access learning materials anytime and anywhere ( Almaiah et al., 2021 ; Bernacki, Crompton, & Greene, 2020 ; Kumar et al., 2022 ; Sprenger & Schwaninger, 2021 ).

Notably, over the past two years, efforts have been made to make learning self-paced and collaborative using key technologies. Amid the COVID-19 outbreak, many higher education institutions faced multiple challenges when transitioning from face-to-face to virtual teaching. One of them was to provide materials that are accessible, useful, effective, and efficient to learners ( Almaiah et al., 2021 ; Herrador-Alcaide et al., 2020 ). In this context, mobile learning tools’ adoption, behaviour and integration into the educational process are critical factors in the training experience ( Akour et al., 2021 ). Integrating social media platforms, such as Instagram, into the learning process has also improved self-learning, increased online contribution and facilitated active participation ( Navandar et al., 2021 ).

The fact that educators now rely on technology to provide flexible and customized learning curricula more than ever before has led to a greater reliance on technology in the classroom. Notably, since Engineering and Humanities were the scopes of application more repeatedly reported in the literature, this allowed for a diverse appraisal. Seven of the articles reviewed describe the implementation of mobile learning in Engineering learning processes, showing the consolidation of its applicability in different categories in higher education ( Diaz-Nunez et al., 2021 ; Kayaalp & Dinc, 2022 ; Kumar et al., 2022 ; Laurens-Arredondo, 2022 ; Mir & Llueca, 2020 ). Following this line, studies distributed in the field of Humanities were evenly focused on language learning ( Huang & Chueh, 2022 ; Lan, 2022 ; Vigil García et al., 2020 ) and the adaptable and personalized potential ( Sarkadi et al., 2020 ; Ugur-Erdogmus & Cakir, 2022 ) of this technology towards building a constructivist and activity-based education.

Nowadays, embedded with other resources supporting AI, XR and Internet of Things devices, mobile learning is expanding and becoming more active, with the expectation that educational experiences can adapt to current learner needs and academic trajectories ( Chu, 2022 ; Laurens-Arredondo, 2022 ; Rangel-de Lázaro & Duart 2023 ). Still, co-design processes combining mobile learning with more traditional resources benefit learning. Building on co-design, new forms of collaboration between educators and researchers are developed, resulting in the development of innovations that impact teaching practice ( Couso, 2016 ; Voogt et al., 2015 ). As a result, teachers and students benefit from deepening educational designs, knowledge and development of new skills ( Penuel et al., 2022 ). Egilsdottir et al. (2021) followed this methodology to reduce the gap between theory and practice in basic physical assessment skills and knowledge transfer between university and clinical sites for nursing courses. The participants considered digital simulations with virtual patients, massive open online courses, and multimedia learning material, and evaluated their potential and benefits in academic and clinical contexts. Furthermore, these students endorsed the inclusion of multiple-choice tests and written assignments to deliver feedback and support learning progress.

Similarly, there is a continuing trend towards using XR and mobile learning to encourage academic achievement and gaining skills in virtual classrooms, as shown by Eldokhny and Drwish (2021) and Chessa and Solari (2021) when using XR in online distance learning through the pandemic. In some areas, VR seemed to be mature enough to be used for teaching procedural, practical knowledge, and declarative knowledge. Examples included Fire Safety, Surgery, Nursing, and Astronomy. In these cases, more professional VR applications were used. However, most articles indicated that VR for education is still in its experimental stages, involving prototyping and testing with students.

The literature reviewed indicates that mobile learning is a solicited resource for customizing courses and curricula to fit student needs and to encourage flexible learning to effectively impact a massive online learning experience ( Verdes et al., 2021 ; X. Zhang, 2022 ). This is more noticeable in those with complex academic trajectories who require synchronous and asynchronous tools, increasingly turning to online university education for their educational needs ( Herrador-Alcaide et al., 2020 ).

Interestingly, keeping track of and enhancing communication and collaboration in online education is also a critical concern when using mobile learning tools. Authors have relied on a vast diversity of existing platforms such as Whatsapp, Telegram, Microsoft Teams, Google Classroom, Google Meet, Zoom, and Edmodo, among many others, to investigate whether they are effective learning platforms that also facilitate engagement, collaborative learning, and ensure the wellbeing and security of students during the most critical times of COVID-19 ( Iqbal et al., 2020 ; Kumar et al., 2022 ; Pramana et al., 2020 ).

However, beyond the many benefits mobile learning provides to higher education, attention must be paid to its downsides, such as information overload, distraction, and time-wasting. Furthermore, there is a risk of discrimination against those who cannot access these services fully. Various factors may contribute to this problem, including complex interfaces, limited access to unstable smart devices, or a low network signal. As a result, some students may find themselves alienated from communication and collaboration within the educational environment. Contrary to other studies, after comparing technology acceptance of e-lectures, classroom response systems, classroom chat, and mobile virtual reality, Sprenger and Schwaninger (2021) noticed a decrease in the perceived usefulness and behavioural intention after three months of students using mobile virtual reality. The main reasons for such poor technology acceptance feedback were mainly related to functional and technical issues of mobile virtual reality. It is clear that the problems presented above are not new. However, it highlights the necessity for a crtitical re-evaluation of the appropriate implementation of emerging technologies in terms of curriculum design, educational policies, technological resource implementation, and digital competencies and skills at all higher education levels. Likewise, X. Zhang (2022) noticed that despite challenges, students believe that the traditional face-to-face method is the best way to carry out the entire teaching and learning process and that digital platforms should be used as a supplement to facilitate the educational process.

CONCLUSIONS

Here we presented a systematic review mapping the implementation and influence on online higher education of mobile learning after the COVID-19 pandemic outbreak. In this literature analysis, only peer-reviewed publications in English or Spanish published in Scopus, Web of Sciences, and EBSCO Education were considered. Moreover, as we included papers submitted after March 2020, we acknowledged that the data provided would, in most cases, have been collected before then. Nevertheless, upon careful evaluation, we recognized that the impact of the pandemic on university agents had influenced the process of producing the selected articles.

Despite it already having been present for years, mobile learning has been embedded in higher education by the pandemic. Since its start, face-to-face learning-teaching activities have had to migrate into virtual settings, and those already working in online environments have also needed to adapt to the new circumstances. All this has resulted in a need for tailored and effective support schemes for educators and learners.

Nowadays, implementing key emerging technologies has a critical role in shaping the future of online higher education. Consequently, educators and students will see digital resources as an accessible toolbox to amplify a personalized, active, learner-centred method. While institutions are getting ready to face new forms of educational settings, future critical implications of using mobile devices are pointing towards improving data literacy and skills, data security and protection against threats to personal privacy, and continuing with the normalization of hybrid and remote learning settings.

We cannot deny that applying mobile learning to educational settings requires an economic investment. However, as these technologies become more ubiquitous, their deployment costs decrease, making them more sustainable in the long term than traditional analogue learning. Looking ahead, it is plausible that this trend will continue evolving worldwide to make access to remote education more effective and adapted to current needs.

In the future, it would be beneficial to implement the search string developed here in a larger number of databases and languages to expand the scope of this review. Further, as education evolves to meet the needs of the current times, we aim to focus future research on other critical technologies such as micro-credentials, open educational resources, and XR and AI.

AUTHORS' CONTRIBUTION

Conceptualization, methodology, analysis, investigation, data curation, writing-original draft, review, editing, visualization: G.R.-d.L.

Conceptualization, writing-review & editing: J.M.D.

All authors have read and agreed to the published version of the manuscript.

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• Yuan, Y. P., Tan, G.-W.-H., Ooi, K. B. & Lim, W. L. (2021). Can COVID-19 pandemic influence experience response in mobile learning? Telematics and Informatics , 64 , 101676. https://doi.org/10.1016/J.TELE.2021.101676
• Zawacki-Richter, O., Marín, V. I., Bond, M. & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education - where are the educators? International Journal of Educational Technology in Higher Education , 16 (1). https://doi.org/10.1186/s41239-019-0171-0
• Zhang, L. & He, J. (2022). Optimization of Ideological and Political Education under the Epidemic via Mobile Learning Auxiliary Platform in the Era of Digitization. Hindawi , Special issue , 1–9. https://doi.org/10.1155/2022/6149995
• Zhang, X. (2022). The Influence of Mobile Learning on the Optimization of Teaching Mode in Higher Education. Wireless Communications and Mobile Computing .

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Mobile Learning: Transforming Education, Engaging Students, and Improving Outcomes

• Mobile Learning: Transforming Education and Engaging Students and Teachers

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Darrell m. west darrell m. west senior fellow - center for technology innovation , douglas dillon chair in governmental studies.

September 17, 2013

Editor’s Note: This paper is released in conjunction with the event Mobile Learning: Transforming Education and Engaging Students and Teachers hosted by the Center for Technology Innovation at Brookings on September 17, 2013.

Education in the United States

Education is at a critical juncture in the United States. It is vital for workforce development and economic prosperity, yet is in need of serious reform. American education was designed for agrarian and industrial eras, and does not provide all the skills needed for a 21 st century economy. [i]   This creates major problems for young people about to enter the laborforce.

Mobile learning represents a way to address a number of our educational problems. Devices such as smart phones and tablets enable innovation and help students, teachers, and parents gain access to digital content and personalized assessment vital for a post-industrial world. Mobile devices, used in conjunction with near universal 4G/3G wireless connectivity, are essential tools to improve learning for students. As noted by Irwin Jacobs, the founding chairman of Qualcomm, Inc., “always on, always connected mobile devices in the hands of students has the potential to dramatically improve educational outcomes.” [ii]   

This paper, part of our Mobile Economy Project , looks at ways that mobile devices with cellular connectivity improve learning and engage students and teachers. Wireless technology is a way to provide new content and facilitate information access wherever a student is located. It enables, empowers, and engages learning in ways that transform the learning environment for students inside and outside of school.   

Sadly, not every student has access to a computer and the Internet. And given the costs of hardware, it is not affordable for school districts to provide a personal computer to every student.However, most young people have phones, and this provides a real opportunity to transform instruction.

Mobile Technology and Mobile Learning

As mobile phones, tablets, and other connected devices become more prevalent and affordable, wireless technology can dramatically improve learning and bring digital content to students. Students love mobile technology and use it regularly in their personal lives. It therefore is no surprise that young people want to employ mobile devices to make education more engaging and personalize it for their particular needs.  

Technology-rich activities can sustain high levels of student engagement and peer collaboration  compared to less technology focused activities. Educators need to figure out how to harness mobile platforms for instructional purposes and employ them to boost educational learning. A majority (52 percent) of students in grades 6-12 believe that having access to a tablet computer is an essential component of their ultimate school. Fifty-one percent of school administrators agree with these sentiments as well. [iii]  

As a country, we need to educate the next generation of scientists, inventors, engineers, and entrepreneurs. Educating a workforce that is effective in a global context and adaptive as new jobs and roles evolve will help to support our economic growth. Mobile learning makes it possible to extend education beyond the physical confines of the classroom and beyond the fixed time periods of the school day. It allows students to access content from home, communicate with teachers, and work with other people online. The value of mobile devices is that they allow students to connect, communicate, collaborate and create using rich digital resources.

Key Features of the paper include:

• Comparison with Other Nations
• Challenges Facing U.S. Education
• How Mobile Enables Innovation
• Student and Teacher Engagement
• Recommendations for Action

[i] Darrell West, Digital Schools:  How Technology Can Transform Education , Brookings Institution Press, 2012.

[ii] Irwin Jacobs, “Modernizing Education and Preparing Tomorrow’s Workforce through Mobile Technology”, paper presented at the i4j Summit, March, 2013, p. 2.

[iii] Project Tomorrow Speak Up Survey, “From Chalkboard to Tablets:  The Emergence of the K-12 Classroom”, April, 2013.

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Drivers of teachers’ intentions to use mobile applications to teach science

Hüseyin ateş.

1 Department of Science Education, Kırşehir Ahi Evran University, Kırşehir, 40100 Turkey

Juan Garzón

2 Faculty of Engineering, Universidad Católica de Oriente, Rionegro, Colombia

Using mobile applications in science education has proven to be effective as it adds multiple benefits including learning gains, motivation to learn, and collaborative learning. However, some teachers are reluctant to use this technology for reasons derived from different factors. Hence, it is important to identify what factors affect teachers’ intentions to use mobile applications, in order to take actions aiming to encourage them to use this technology in their classes. Accordingly, this study proposes a model to predict science teachers’ intentions to use mobile applications in the teaching process. Our model merges the Technology Acceptance Model, the Flow Theory, and the Theory of Planned Behavior. It includes 11 hypotheses that were tested with 1203 pre-service and in-service science teachers from different cities in Turkey. Additionally, the study investigates the mediating role of attitude and perceived usefulness on teachers’ intentions to use mobile apps. Further, it examines the moderating role of the sample type on teachers’ behavioral intentions. The results indicate that all 11 hypotheses were significant to explain teachers’ intentions to use mobile applications. Finally, the study raises theoretical and practical implications to guide stakeholders to undertake actions to enrich educational settings through the use of mobile applications.

Introduction

The use of mobile applications (mobile apps) in education has positively transformed teaching and learning processes. As for science education, using mobile apps has proven to be effective as it adds multiple benefits including learning gains, motivation to learn, and collaborative learning (Bano et al., 2018 ; Camilleri & Camilleri, 2019 ; Crompton et al., 2016 ; Martín-Páez et al., 2019 ). However, some teachers are reluctant to use these technological aids for reasons derived from different factors (Al-Azawei & Alowayr, 2020 ; Bano et al., 2018 ; Kalogiannakis & Papadakis, 2019 ). Therefore, it is important to identify the factors affecting their intentions to use mobile apps, in order to take actions aiming to encourage them to use this technology in their classes. Science education involves similar academic contents and structure throughout the world; nonetheless, every country has different strategies to address this subject depending on political and cultural influences. In this study, we consider the Turkish model of science education. The curriculum for this model includes physical processes; life and living beings; and the earth and the universe and is taught in grades 5 to 8 (Turkish Ministry of National Education, 2018 ).

Some studies have focused on the analysis of the status, trends, advantages, and challenges of mobile apps in science education (Crompton et al., 2016 ). However, the existing literature lacks studies that identify teachers’ intentions to adopt and use this technology in the teaching process. Hence, this study proposes a model to predict science teachers’ intentions to use mobile apps in their classes. Our model merges three psychological-based behavioral theories, namely the Technology Acceptance Model (TAM), the Flow Theory (FT), and the Theory of Planned Behavior (TPB). Merging these theories provides theoretical and practical insights to guide stakeholders to undertake actions to enrich educational settings through the use of mobile applications. The TAM has been described as the most powerful theory to predict an individual’s intention to adopt a specific technology (Hansen et al., 2018 ). On its part, the emotional constructs of the FT, help identify which factors are most likely to influence teachers’ motivation to use mobile apps. Finally, the rational considerations of the TPB help understand how science teachers evaluate the cost–benefit relationship of using mobile apps. Hence, we postulate that merging these theories is relevant to examine associations between constructs to explain science teachers’ intentions to use mobile apps in educational settings.

To our knowledge, this is the first study to predict teachers’ intention to use mobile apps in science education in the Turkish context. However, our results can be generalized to the global context to guide the process of integrating mobile apps in the educational settings. The study compares the explanatory power of the proposed model with that of the TAM, FT, and TPB. It also examines the relative importance among the constructs to understand teachers’ intentions to use mobile apps for science teaching. Additionally, it investigates the mediating role of attitude and perceived usefulness on teachers’ intentions to use mobile apps. Further, the study examines the moderating effect of sample type within the research framework. Finally, the study raises some theoretical and practical implications to guide stakeholders to undertake actions aimed at enriching educational settings using mobile applications.

Literature review and study hypotheses

Mobile apps in science education.

The study by Crompton et al. ( 2016 ) analyzed 49 studies to identify the trends in the use of mobile applications in science education. The study found that elementary schools are the most common setting for research studies and that most studies focus on life sciences. Furthermore, the authors found that the majority of the studies take place in informal educational contexts and use smartphones as deployment technology. As for the benefits of using mobile apps in science, the study by Zydney and Warner ( 2016 ) establishes that perhaps the main benefit is learning gains. Furthermore, the study asserts that this technology can be used in situated learning contexts, which translates into knowledge retention and learning transfer. Similarly, the study by Jeno et al. ( 2019 ) employed the Self-Determination Theory to analyze the impact of mobile apps compared to traditional textbooks in science education. The study concluded that mobile applications extend the learning space, which facilitates collaboration and promotes interaction with course content, improving students’ learning and motivation. Finally, Bano et al. ( 2018 ) conducted a systematic review of 49 studies to identify the pedagogical approaches adopted when using mobile apps in education. The results indicate that collaborative learning is the most reported approach in the studies. Using mobile apps allows students to interact with their partners facilitating the understanding of abstract concepts from science, which raises collaborative learning as an important benefit of the use of mobile apps in science education.

Some studies have analyzed the factors that affect teachers’ intentions to use mobile technologies in science-related fields. The study by Udeani and Akhigb ( 2020 ) investigated in-service biology teachers’ perceptions of the use of smartphones in educational settings. The study included 32 in-service biology teachers, from a secondary school in Nigeria. The study considered the TAM questionnaire and the Mobile App Selection for Science (MASS) rubric. As a result, the study found that in-service biology teachers in Nigeria have positive perceptions about the pedagogical use mobile apps and that these perceptions are significant in their intentions to use the apps in educational settings. Similarly, the study by Kalogiannakis and Papadakis ( 2019 ) implemented the TAM to identify how the skills and attitude towards technology, affect teachers’ willingness to use mobile devices to teach natural sciences in kindergarten. The study included 75 pre-service kindergarten teachers from Greece. The results indicated that the pre-service teachers’ attitude toward the usefulness of mobile learning and their perceived ease of use had the strongest influence on their intention to use this technology in classes. Finally, the study by Khlaif ( 2018 ) investigated the factors influencing the adoption and acceptance of tablets as a mobile technology in middle schools in Palestine. The study included 15 teachers who were interviewed following an instrument designed according to the Unified Theory of Acceptance and Use of Technology (UTAUT). The results indicated that teachers’ attitudes are a critical factor in accepting tablet use in classroom, and in turn, their attitudes are influenced by the perception of technical support, instructional assistance, and infrastructure.

However, the aforementioned studies have some important limitations according to the purpose of our study. First,

the studies focused on one subject or one target group, which does not let them to accurately stablish general statements that advance the broad field of science education. Second these studies use relatively small samples, limiting their findings to a very specific context. Third, the studies use a single psychological-based behavioral theory. This implies that they do not complement the predictive power with the inclusion of additional theories, as suggested in previous studies (Manosuthi et al., 2020 ; Tamilmani et al., 2017 ; Taufique & Vaithianathan, 2018 ).

Proposed model

This study proposes a model to predict science teachers’ intentions to use mobile applications in the teaching process. To our purpose, it is necessary to identify both the behavioral intentions and actual behaviors of science teachers. This implies identifying both direct and indirect factors that influence teachers’ attitudes, which in turn, lead to behavior (Hill, 2017 ). These factors may include extrinsic and intrinsic attributes like social norms, compliance intentions, normative believes, perceived usefulness, perceived ease of use, perceived enjoyment, perceived cost–benefit relationship, and perceived self-efficacy to comply (Hofeditz et al., 2017 ). No psychological-based theory includes the analysis of all the factors mentioned above. Therefore, it is suitable to consider a combination of theories, which together produce a more robust theory to explain individuals’ intentions to adopt a specific behavior (Hansen et al., 2018 ). In addition, as explained in previous studies, merging two or more behavioral theories, often increases the power to explain individuals’ intentions that, ultimately, predicts individuals’ behavior.

Our model combines the TAM, FT, and TPB for three main reasons. First, TAM has become one of the most widely used models in technology-enhanced learning, due in part, because its simplicity and understandability. However, the fact that TAM employs only two constructs to explain behavioral intention, results in significant variation in the predicted effects between studies with different types of users and systems (Legris et al., 2003 ). Consequently, it is recommended to use the TAM jointly with other models, in order to extend its explanatory power (Lu et al., 2009 ). Second, perhaps the main advantage of the TPB is that it helps identify the direct determinants and the underlying beliefs that impact the individuals’ intentions to perform a specific behavior (Cheng, 2019 ). However, this framework fails to provide information on the attitudinal beliefs that would affect users’ attitudes toward the use of a specific system, thus requiring it to be complemented with other theories. Third, the FT focuses on the motivational aspects that lead to adopt a specific system. Different studies have shown that concerning educational contexts, motivation is as important as knowledge (Keller, 2009 ). When using mobile apps, individuals can experience the flow while being involved in educational scenarios. Therefore, we posit that using the FT is also applicable to explain teachers’ adoption of mobile apps to teach science. Figure  1 presents the proposed model.

Technology Acceptance Model (TAM)

The TAM is a model that explains the individuals’ behavioral intentions to use a technological innovation. This theory was proposed by Davis ( 1989 ) as an extension of the Theory of Reasoned Action (TRA) and poses that individuals’ technology acceptance is determined by two major variables, namely perceived ease of use and perceived usefulness. Perceived ease of use refers to the extent to which an individual believes that the use of a particular system is free of effort (Davis, 1989 ). On the other hand, perceived usefulness refers to the extent to which an individual believes that the use of a particular system would improve job performance (Davis, 1989 ). According to the TAM, perceived ease of use and perceived usefulness affect an individual’s attitude toward the use of a system and perceived ease of use has a direct impact on perceived usefulness. In turn, the individual’s intention to use a system is influenced by perceived usefulness (Teo & Noyes, 2011 ).

Because of its simplicity and understandability, this theory has become one of the most widely used models to explain teachers’ intentions to use technology. For example, Al-Emran et al. ( 2018 ) conducted a comprehensive analysis of 86 TAM studies related to mobile learning. The study highlighted the validity of the constructs of the TAM to examine the acceptance, attitudes, and actual use of mobile learning by students and teachers. Similarly, Scherer et al. ( 2019 ) conducted a meta-analysis of 114 TAM studies to explain teachers’ adoption of digital technology in education. The study validated the relevance of the TAM to explain behavioral intentions and the use of technology. The meta-analysis further highlighted that the TAM is equally relevant for several sub-groups, including pre-service and in-service teachers, teachers at different educational levels, and different countries. Finally, Granić and Marangunić ( 2019 ) conducted a systematic literature review of 71 studies to identify the importance of the TAM model according to the field of education, level of education, and deployment technology. The findings revealed that TAM is a leading scientific paradigm and credible model to facilitate the assessment of diverse technological deployments in educational contexts. Furthermore, the results indicated that perceived ease of use and perceived usefulness, are key elements to predict individuals’ acceptance of technology in all the analyzed educational contexts.

Based on the previous background, we posit that the TAM is suitable for explaining science teachers' intentions to use mobile apps in their classes. Next, we establish the first, second, third, and fourth hypotheses of this study:

• H1 : Perceived ease of use is positively related to the science teachers’ perceived usefulness of mobile apps ( H 1 : P E O U → P U ) .
• H2 : Perceived ease of use is positively related to the science teachers’ behavioral attitudes toward mobile apps ( H 2 : P E O U → A T T ) .
• H3 : Perceived usefulness is positively related to the science teachers’ behavioral attitudes toward mobile apps ( H 3 : P U → A T T ) .
• H4 : Perceived usefulness is positively related to the science teachers’ behavioral intentions to use mobile apps ( H 4 : P U → I N T ) .

Flow Theory (FT)

The FT defines flow like a state of deep absorption in an activity that is intrinsically enjoyable (Csikszentmihalyi, 2008 ). People in this state perceive that their performance is pleasant and successful, and the activity is worth doing for its own. There is no single definition of the necessary conditions that lead to flow. Koufaris ( 2002 ) proposed one of the most widely used FT models in education, as the proposed constructs have been successfully validated to explain teachers intentions to use technology. Koufaris’ model measures flow using three constructs: perceived enjoyment, perceived control, and concentration. In this model, perceived enjoyment refers to the extent to which the activity of using a specific system is perceived to be enjoyable in its own right, aside from any performance consequences resulting from system use (Venkatesh, 2000 ). On the other hand, concentration refers to the state of absolute absorption in an activity (Csikszentmihalyi, 2008 ). Finally, perceived control is defined as the level of an individual’s control over the environment and the individual’s actions (Koufaris, 2002 ). The study by Bower et al. ( 2020 ) and Hu et al. (Hu et al., 2020 ) state that perceived enjoyment is a key motivator for influencing teachers’ attitude toward the use technology and, ultimately, teachers’ intentions to use it. Similarly, perceived control is described as one of the constructs that most influences teachers’ intentions to use technology (Somchai & Damnoen, 2020 ; Teo et al., 2016 ). Finally, concentration leads to optimal learning experiences and, consequently, it also influences teachers’ attitude toward the use technology and intentions to use it (Shernoff et al., 2014 ). Therefore, considering the purpose of our study, we adopt the constructs proposed by Koufaris ( 2002 ) to identify the drivers of teachers' intentions to use mobile applications to teach science.

There is great potential for students to experience flow in the learning process. However, this potential is often wasted as some of the key conditions for flow are lacking in many of today's educational contexts. In this regard, Schmidt ( 2010 ) stresses the importance of analyzing students’ educational experience from the perspective of FT to understand the factors that promote students’ engagement in learning. In line with this, Oliveira et al. ( 2018 ) conducted a systematic literature review of 57 studies to identify the main benefits in bringing students to the flow state in technology-enhanced learning. The study found positive outcomes, highlighting students’ learning, students’ satisfaction, and students’ in-depth reflective process. Concerning science education, the study by Ellwood and Abrams ( 2018 ) analyzed students’ social interaction in inquiry-based science according to the FT. The study concluded that conditions that prompt flow state, including perceived enjoyment, perceived control, and concentration fostered enhanced student learning gains and motivation. In that sense, the study remarks the importance of emphasizing flow as a key part of the development process of the students. Finally, the study states that to promote flow, teachers must put more emphasis on fun, making learning so compelling that it seems there is no other option for students than to learn.

Based on the previous background, we posit that the constructs of the FT are suitable for explaining science teachers' intentions to use mobile apps in their classes. Next, we establish the fifth, sixth, seventh, and eighth hypotheses of this study. It is important to note that perceived control is similar to perceived behavioral control in the TPB, and therefore, we merged both constructs to postulate the 11 th hypothesis.

• H5 : Perceived enjoyment is positively related to the science teachers’ behavioral attitudes toward mobile apps ( H 5 : P E → A T T ) .
• H6 : Perceived enjoyment is positively related to the science teachers’ behavioral intentions to use mobile apps ( H 6 : P E → I N T ) .
• H7 : Concentration is positively related to the science teachers’ behavioral attitudes toward mobile apps ( H 7 : C O → A T T ) .
• H8 : Concentration is positively related to the science teachers’ behavioral intentions to use mobile apps ( H 8 : C O → I N T ) .

Theory of Planned Behavior (TPB)

The TPB links the beliefs of an individual with the behavior of the individual. This theory was proposed by Icek Ajzen in 1985 (Ajzen, 1985 ) as a complement of the Theory of Reasoned Action (TRA) by Fishbein and Ajzen ( 1975 ). The TPB states that three factors, namely attitude, subjective norm, and perceived behavioral control, shape the behavioral intentions of an individual. In turn, behavioral intention is assumed to be the closest determinant of human social behavior. The TPB defines attitude as the extent to which an individual positively or negatively values the performance of certain behavior (Fishbein & Ajzen, 1975 ). On the other hand, subjective norm refers to the perceived social pressure imposed by important referents, to engage or not in a behavior (Fishbein & Ajzen, 1975 ). Finally, perceived behavioral control refers to individuals’ perceptions about their abilities to perform a certain behavior (Icek, 1991 ).

Because of the volitional emphasis of the TPB, it has been successfully implemented to study many intentional aspects of educational technology. For example, the study by Valtonen et al. ( 2018 ) implemented the TPB to explain pre-service teachers’ readiness to use information technologies in education. The study validated the utility of the three constructs of the TPB to explain individuals’ intentions. Particularly, the study found subjective norm as the most significant construct to explain pre-service teachers’ intentions to use information technologies in educational settings. Additionally, the study by Gretterand and Yadav ( 2018 ) implemented the TPB to explain pre-service teachers’ thinking about teaching media literacy and the study by Sungur-Gül and Ateş ( 2021 ) tested the TPB to understand pre-service teachers’ mobile learning readiness. Similarly to the study by Valtonen et al. ( 2018 ), this study validated the utility of the TPB to explain pre-service teachers’ intentions use information technologies in education. However, this study found attitude as the most significant construct to explain pre-services teachers’ intentions to use information technologies in educational settings. Finally, the study by Somchai and Damnoen ( 2020 ) implemented the TPB to explain teachers’ intentions to continue to use online teaching at post Covid-19 pandemic. The study supported the utility of the TPB as a theory to analyze individuals’ intentions related to technological education. Particularly, perceived behavioral control was found to be the most significant construct in explaining teachers’ intentions to continue to use online teaching at post Covid-19 pandemic.

Based on the previous background, we posit that the constructs of the TPB are suitable for explaining science teachers' intentions to use mobile apps in their classes. Next, we establish the ninth, tenth, and eleventh hypotheses of this study:

• H9 : Behavioral attitude toward mobile apps is positively related to the science teachers’ behavioral intentions to use mobile apps ( H 9 : A T T → I N T ).
• H10 : Subjective norm is positively related to the science teachers’ behavioral intentions to use mobile apps ( H 10 : S N → I N T ) .
• H11 : Perceived behavioral control is positively related to the science teachers’ behavioral intentions to use mobile apps ( H 11 : P B C → I N T ) .

Sample and data collection

The study was conducted based on cross-sectional study. The participants of the study were pre-service and in-service science teachers who were determined based on a voluntary basis using the convenience sampling method. In Turkey, pre-service science teachers are trained in accordance with the elementary school science curriculum during their four-year higher education. On the other hand, at the middle school level (from 5 th grade to 8 th grade), science courses are taught by in-service science teachers.

The data were collected in a classroom environment at middle schools and universities in several cities in Turkey. Initially, the data was collected from 792 pre-service science teachers and 489 in-service science teachers. After the first examination on the scales, 78 outliers, incomplete, and unusable responses were excluded from the study. Hence, a total of 1203 usable scales were obtained from pre-service science teachers ( N = 735 ) and in-service science teachers ( N = 468 ) showing a valid response rate of 93.91%. Regarding the pre-service teachers, 66.4% were female and 33.6% were male, with ages between 17 and 26 years ( M age = 21.8 ) . As for in-service science teachers, 57.9% were female and 42.1% were male, with ages between 24 and 63 ( M age = 41.2 ) , and average occupational experiences was 18 years. A great majority of them (85.26%) had a bachelor's degree, while 14.74% completed postgraduate education.

Measurement tools

The scales in the current study were adapted from earlier studies (see Table ​ Table1). 1 ). The preparation of these scales from the first to the final version consists of several stages. First, initial scale items were arranged after extant literature was reviewed. Second, the first version of the scale items was pre-tested with 225 pre-service and in-service science teachers. Third, as the original version of the items and constructs are in English and the scales in the current study were prepared in Turkish, we used the blind translation-back-translation method to ensure consistency and accuracy (Bracken & Barona, 1991 ). The translated scales were comprehensively reviewed and improved by academicians who have language proficiency in both Turkish and English and have sufficient knowledge about national and international literature on the subject of this study. In addition, the scale was completed by three experts in the field of the department of science education and computer and instructional technologies.

Constructs, items, factor loadings and source

The self-determined scales consist of four parts. The first part of the scales includes items and constructs (perceived ease of use, three items and perceived usefulness, three items) involved in the TAM. Second, perceived enjoyment (three items) and concentration (three items) were obtained from the FT. In the third stage, attitude (four items), subjective norm (two items), and perceived behavioral control (three items) were operationalized in the TBP. Finally, intention was measured with four items. A total of 25 items were evaluated with a seven-point Likert type scale ranging from “Strongly disagree” (1) to “Strongly agree” (7). Table ​ Table1 1 presents items, constructs, and sources of scales used in the study.

Data analysis

The data were analyzed using SPSS and AMOS statistical programs. In accordance with Anderson and Gerbing ( 1988 ) two-step approach was used using maximum likelihood estimation. Firstly, a measurement model was estimated by conducting confirmatory factor analysis (CFA), and then structural equation modeling (SEM) was used to evaluate and compare the proposed model and test the hypotheses.

The first step of the analysis showed that the measurement model fit the data very well (comparative fit index [ CFI ] = 0.95 , The goodness of fit index [ GFI ] = 0.93 , The normed fit index [ NFI ] = 0.95 , Tucker-Lewis Index [ TLI ] = 0.94 , standardized root mean squared residual [ SRMR ] = 0.04 , root mean square error of approximation [ RMSEA ] = 0.05 ). Internal consistency of the data was examined via Cronbach’s alpha (α) and composite reliability and the results indicated that α values for each variable were higher than the recommended value of 0.07 (Bagozzi & Yi, 1988 ) and all the values of composite reliability were ranged from 0.78 to 0.91 which were greater than the recommended value of 0.6 (Bagozzi & Yi, 1988 ). In addition, construct validity was tested using convergent validity and discriminant validity (Hair et al., 2017 ; Kline, 2015 ). The results of construct validity indicated that since all the values of average variance extracted (AVE) were larger than the suggested value of 0.5 (Hair et al., 2017 ), convergent validity was provided. Discriminant validity was also provided because all values of the square root of the AVE were exceeded the correlation coefficients of constructs (Hair et al., 2017 ). Results toward the measurement model are involved in Table ​ Table2 2 .

Results toward the measurement model

Diagonal and bold values show the square root of AVE

Goodness of fit and predictive power of structural model

The current study merged TPB, TAM, and FT and proposed a more robust model to understand pre-service and in-service science teachers' intention to use mobile apps for science teaching. The goodness of fit results showed that the proposed model, TPB, TAM, and FT adequately fit the data. Results comparing models with the proposed model revealed that the proposed model ( χ 2 / df = 2.14 ) has superior fit to that of TPB ( χ 2 / df = 2.30 ) , TAM ( χ 2 / df = 2.69 ) , and FT ( χ 2 / df = 2.99 ) . The model ( R 2 = 0.52 ) also had a superior ability to explain intention than TPB ( R 2 = 0.47 ) , TAM ( R 2 = 0.42 ) , and FT ( R 2 = 0.39 ) . Model fit indices and predictive powers of models in the study are involved in Table ​ Table3 3 .

Results of goodness of fit and predictive powers

Hypothesis testing

SEM was used to examine the relationships among constructs in the proposed model. The results of hypothesis testing showed that PEOU had a positive influence on both PU ( β = 0.49 , p < 0.001 ) and ATT ( β = 0.34 , p < 0.001 ) , supporting H1 and H2. Paths from PU to ATT ( β = 0.32 , p < 0.001 ) and INT ( β = 0.36 , p < 0.001 ) were statistically significant, thus H3 and H4 were supported. H5 and H6 were also supported as a positive direct influence of PE on ATT ( β = 0.48 , p < 0.001 ) and INT to use mobile apps for science teaching ( β = 0.22 , p < 0.01 ) . It was also found that the paths from CO to ATT ( β = 0.16 , p < 0.01 ) and INT ( β = 0.19 , p < 0.01 ) were statistically significant, supporting H7and H8. Finally, among the constructs of TPB, ATT ( β = 0.28 , p < 0.001 ) , SN ( β = 0.21 , p < 0.01 ) , and PBC ( β = 0.24 , p < 0.01 ) were positively related to INT to use mobile apps for science teaching. Therefore, H9, H10, and H11 were supported. Results toward indirect relationships showed that PEOU had a positive indirect impact on ATT ( β = 0.15 , p < 0.05 ) . In addition, PEOU ( β = 0.11 , p < 0.05 ) , PU ( β = 0.12 , p < 0.05 ) , CO ( β = 0.10 , p < 0.05 ) and PE ( β = 0.13 , p < 0.05 ) were indirectly related to INT to use mobile apps for science teaching. Finally, within the proposed model, about 24% of the total variance in PU was explained by PEOU . In addition, PEOU, PU , PE, and CO accounted for 49% of the variance in ATT . Lastly, 52% of the variance in INT was explained by its antecedents. Results of the hypothesis test are indicated in Table ​ Table4 4 and Fig.  2 .

SEM results of the conceptual proposed model

* p  < 0.05 , ** p  < 0.01, *** p  < 0.001

Results from the hypothesis test

Examining the moderating effects of sample type

In the study, the invariance test for measurement and structural models was performed to test the moderating effect of sample type (Kline, 2015 ). In this study, as sample type, 735 pre-service science teachers and 468 in-service science teachers were involved in the study.

During the moderating analysis, in the first stage, statistical significance was tested between the non-restrict model and the full-metric invariance model. In the second stage, the baseline model and the nested model were compared in a certain path across the groups. Data analysis showed that both non-restrict model ( χ 2 = 1235.68 , df = 646 ; χ 2 / df = 1.91 , CFI = 0.95 , IFI = 0.96 , TLI = 0.95 , RMSEA = 0.048 ) and full-metric invariance model ( χ 2 = 1282.47 , df = 671 ; χ 2 / df = 1.91 , CFI = 0.95 , IFI = 0.95 , TLI = 0.95 , RMSEA = 0.049 ) generated a good fit to the data. It was also found that the chi-square difference test revealed that there was no significant difference between the non-restrict model and full-metric invariance model ( Δ χ 2 ( 25 ) = 46.79 , p > 0.01 ) . Accordingly, this finding supported the full-metric invariance.

Proposed relationships were added to full-metric invariance model to generate the baseline model. Result of the structural-invariance model showed that the baseline model is a great fit with data ( χ 2 = 1536.74 , df = 746 ; p < 0.001 , χ 2 / df = 2.06 , CFI = 0.91 , IFI = 0.91 , TLI = 0.90 RMSEA = 0.054 ) .

As a result of comparing the baseline model with the nested model, a series of significant relationships were found. The paths from PE ( Δ χ 2 ( 1 ) = 4.45 , p < 0.05 ) and CO ( Δ χ 2 ( 1 ) = 5.37 , p < 0.05 ) to INT were significantly different between pre-service teachers and in-service teachers. Results of the structural invariance test are presented in Table ​ Table5 5 .

Invariance test results for sample type related to the measurement and structural models

a Δ χ 2 ( 1 ) = 1.20 , p > 0.05 (insignificant)

b Δ χ 2 ( 1 ) = 2.30 , p > 0.05 (insignificant)

c Δ χ 2 ( 1 ) = 1.87 , p < 0.05 (insignificant)

d Δ χ 2 ( 1 ) = 1.91 , p > 0.05 (insignificant)

e Δ χ 2 ( 1 ) = 2.37 , p > 0.05 (insignificant)

f Δ χ 2 ( 1 ) = 4.45 , p < 0.05 (significant)

g Δ χ 2 ( 1 ) = 2.07 , p > 0.05 (insignificant)

h Δ χ 2 1 = 5.37 , p < 0.05 (significant)

i Δ χ 2 1 = 1.70 , p > 0.05 (insignificant)

j Δ χ 2 1 = 1.85 , p > 0.05 (insignificant)

k Δ χ 2 1 = 1.75 , p > 0.05 (insignificant)

* p  < 0.01, ** p  < 0.001

Discussion and implications

The proposed model combined the TPB, TAM, and FT into one comprehensive theoretical framework to examine pre-service and in-service science teachers' intention to use mobile apps for science teaching. In addition, the study investigated the mediating role of attitude and perceived usefulness on intention and the moderating importance of sample type are assumed important factors on teachers’ behavioral intentions. All hypotheses in the proposed model were supported. In addition, the results of the study showed that attitude and perceived usefulness played a mediating role to explain behavioral intention. Furthermore, sample type had an important moderating variable to examine the influence of perceived enjoyment and concentration on pre-service and in-service science teachers' intention to use mobile apps for science teaching.

Theoretical implications

First, the positive role of mobile apps in science learning has been confirmed in many studies (Camilleri & Camilleri, 2019 ), therefore, in this study, it is assumed that mobile apps help teachers in their teaching process. Some of earlier studies examined the role of psychological variables to predict to intention to use mobile applications in science education (e.g., Kalogiannakis & Papadakis, 2019 ). However, there have been a few studies that specifically investigate factors affecting or in-service teachers’ intentions to use mobile technologies such as ipads and mobile based assessment for science teaching (e.g., Hu & Garimella, 2014 ; Nikou & Economides, 2019 ).The results revealed in the present study are theoretically important since antecedents of both pre-service and in-service science teachers’ behavioral intentions to use mobile apps for science teaching were first determined.

Second, the study attempted to integrate three theories including TPB, TAM, and FT so as to explain behavioral intentions toward the use of mobile apps in science courses within the context of educational technology. In past studies, the extended framework integrating belief-related, volitional, non-volitional, and motivation-based factors was applied in exploring individuals’ various technology acceptance intentions (Cheng, 2019 ; Lu et al., 2009 ).Therefore, merging these models has been proposed as a holistic approach and has been confirmed to be robust in explaining individuals' behavioral intentions. Moreover, the results showed that each construct in the proposed model was significantly related to pre-service and in-service science teachers’ behavioral intentions to use mobile apps for science teaching.

Third, the study results showed that the additional paths proposed by combining TPB, TAM, and FT were significantly supported. Specifically, perceived ease of use and perceived usefulness had a positive impact on attitude, which was positively related to intention. This implies that pre-service and in-service science teachers who believe that using mobile apps for science teaching would be free of effort and increases their productivity tend to evaluate this technology in science classes as positive. The results also indicated that the stronger the teachers' positive attitudes, the higher their intention to use mobile applications for science teaching. These findings are consistent with those of Teo et al. ( 2016 ) and supported the validity of TAM (Davis, 1989 ). In addition, perceived enjoyment and concentration played an essential role in explaining attitude and intention. In other words, increasing the enjoyment of using mobile apps for science teaching and the degree of focus on the effectiveness of using mobile apps strengthens teachers' attitudes, which in turn strengthens their intention to use mobile apps in science teaching. These results are consistent with some studies that identified the prominent role of the perceived enjoyment and concentration in explaining teachers’ technology acceptance in education (Bower et al., 2020 ; Hu et al., 2020 ). Therefore, the study made important contributions to the literature by revealing the importance of these crucial constructs’ relationships within the context of using mobile applications in science teaching.

Fourth, the study expanded the theoretical conceptual framework by emphasizing the moderating role of sample type in explaining behavioral intentions with regards to using mobile applications in science teaching in the integrated model that merged TPB, TAM, and FT. The results showed that sample type occupied an important moderating role in the relationships between perceived enjoyment and intention and concentration and intention. In particular, pre-service teachers demonstrated greater beta values than the in-service teachers in all the relationships. It can be inferred that when teachers start the teaching profession, they are less likely to have fun with mobile technology, and they are less likely to focus too much on that technology. Earlier studies supported these findings. For example, Venkatesh et al. ( 2012 ) stated that as people gather experience, the attraction of innovation that contributes to the impact of enjoyment and fun on technology use will decrease. In a similar vein, Lu et al. ( 2009 ) found that perceived enjoyment and concentration have a higher effect on technology acceptance intentions of students than working professionals. In this sense, the present study validated and expanded current literature by empirically revealing the moderating role of sample type within the context of the use of mobile applications in science teaching for the first time.

Practical implications

From a practical point of view, the study provided important results since the findings are useful to curriculum makers, teacher educators, school principals, policymakers, and mobile application developers. The study revealed that, similar to past studies, perceived ease of use, perceived usefulness, attitude, subjective norm, and perceived behavioral control play important role in understanding pre-service and in-service science teachers’ intention to use mobile apps for science teaching. Therefore, teacher educators and curriculum makers should attach importance to the role of easiness and usefulness of mobile apps, favorable evaluations toward mobile apps, ideas of significant others, and non-volitional factors on pre-service teacher education. Another result from this study that should be considered is that pre-service and in-service science teachers are influenced differently by the same constructs (i.e., perceived enjoyment and concentration) and pre-service teachers who are younger than other group tend to have more fun from mobile applications in science teaching than in-service science teachers. Accordingly, considering the great importance of mobile applications in science education (Bano et al., 2018 ; Crompton et al., 2016 ; Jeno et al., 2019 ; Zydney & Warner, 2016 ) and the significant increase in the number of studies carried out in recent years (Liu et al., 2021 ), mobile application developers and policymakers should bear in mind that mobile apps should be developed in a way that attracts the attention of in-service teachers and enables them to be more focused. It is also among the things that should be taken into consideration by those who have a voice in developing the program, that the apps should be made more fun while teachers are using them.

Limitation and future research directions

Although the present study had a variety of contributions to the literature, it has some limitations which need to be kept in mind for further research. The study is limited to only pre-service and in-service science teachers in Turkey, so generalization beyond this sample group can lead to misinterpretation and reduce external validity and therefore may cause sampling bias. In the study, as data were collected with self-reported scales, participants may not have stated their true thoughts and have answered in a way that supports social desirability. One of the important limitations is about testing the moderating effects of personal characteristics. More specifically, as there is a considerable disproportion in the distribution of some variables such as gender, the study only tested the moderator effect of sample type on intention to use mobile apps for science teaching. However, it is still unclear to what extent the moderator variables influence the intention to use educational technologies, especially mobile apps. Thus, future studies should continue to test the moderator role of a number of variables such as gender, age, experience, and sample group. Finally, since actual behavior towards the use of mobile apps was not involved in the proposed model, we used intention instead. However, even though intention is the best predictor of behavior (Icek, 1991 ), it doesn’t measure actual behavior. Hence, in future studies, longitudinal research methods may provide the transforming of science teachers’ intentions to behaviors related to the use of mobile applications in science teaching by performing in-depth and within-person analyses.

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• Open access
• Published: 06 November 2018

The future role of mobile learning and smartphones applications in the Iraqi private universities

• Mohammad Abdulrahman Al-Mashhadani   ORCID: orcid.org/0000-0003-4579-5743 1 &
• Marwah Firas Al-Rawe 2  

Smart Learning Environments volume  5 , Article number:  28 ( 2018 ) Cite this article

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The higher education sector has witnessed a drastic change due to new advanced technologies including computers and smartphones. As a result, higher education will need to establish a solid foundation aided by information communication technologies (ICT) where mobile applications can extend learning opportunities for students and graduates so they meet the requirements of the fast-changing jobs market. Many studies conducted in various contexts have revealed the drastic change of using mobile applications (henceforth apps) and advanced communication which help students develop their skills by means of using the digital environment.

The study aims at identifying the general impression of Iraqi private universities students about the future role of ICT and the mobile learning in higher education. Al-Maarif University College is selected as a case study to measure the extent of students’ reliance on the use of modern smartphones applications in research, study, and skills development in the field of specialization. The study also sheds light upon specifying the important variables and methods for enhancing the role of the mobile learning as a part of the electronic education for the private education sector in Iraq.

Introduction

Many drastic changes have taken place for the higher education sector because of the new developments in information communication technologies using computers, smartphones and their apps. International organizations such as United Nations have recognized information communication technologies as a useful tool at different learning sectors. Accordingly, many developed countries invest information communication technologies in the infrastructure. Focusing on technology-based learning methods is to cope with the various learning methods among young people and even third world countries are making efforts to benefit from technological expansion in the field of computers and smartphones (Olasoji et al. 2014 ).

Smartphones and iPads are popular amongst college students due to their being easily carried, wireless, containing many apps making it easy for the student to do multiple tasks at one stand, and connecting while roaming. All of these have helped increase the popularity of mobile devices due to their ability to handle multiple tasks. Furthermore, commercial competitive industry has compelled manufacturers to present new creative features of competitive traits (Ismail et al. 2013 ).

Thus, it has been noticed that those devices have a great impact upon the nature of higher education, the advanced learning methods, and the future role of those devices in developing and specifying alumni skills.

Because smartphones extend the learning environment the addition of learning environment by using smartphones and its apps represent a highly developed trend in higher education sector and e-learning, because of the easily transmitted teaching experiences via smartphones, as well as the use of educational programs and the transfer of information outside the routine use of information communication technologies in higher education institutions (Ozuorcun and Tabak, 2012 ).

At the Iraqi educational institutions, e-learning is considered as a new mode of the advanced academic learning. The pre-stage of the present study has shown that a few numbers of the Iraqi Official Universities have adopted computer-based teaching strategies for their students. This is attributed partially to the high cost investment for this sector. Launching from this point, special attention is paid for the private higher education in Iraq, the adoption of the e-learning strategy, and the increase in the mobile educational apps using mobile for those universities are considered a good arena for those programs for the following reasons:

The feasibility of those devices and their apps for the educational process for private and official universities students.

The future look to upgrade the private universities outcomes to cope with the requirements of the future jobs market.

The financial possibilities available for the private education sector in Iraq and the possible communication and negotiation with the private employment sector.

The research questions

The following questions sum up the research contributions:

To what extent private universities students depend on mobile apps?

Can the students visualize the role and the impact of information communication technology for their study?

In what situations do students prefer using mobile apps for the learning process?

Is there a need to add the training on mobile apps-usage to the programs of curricula?

Aim and objectives

The study aim at discovering the general attitude and vision of private universities students towards the role of mobile apps for learning, training, and speciality-skill development and the future role of the mobile apps on private higher education. Al-Maarif University College at Al-Anbar governorate is the case study. The specified objectives were:

Estimating the scope of using information communication technology among private Universities students.

Identifying the students’ anticipation on the future role of smartphone apps.

Recognizing how far it is needed for training students on smartphones apps to enhance their speciality and moulding it in the curricula.

Recognizing how far students are able to handle with the information communication technology.

Specifying websites, social media, and e-forum role for the learning process and how the students handle with these sites by using smartphones.

Depending on the research questions, the study hypotheses are as the following:

There is a significant impact between smartphone apps usage abilities and developing those skills to develop quality assurance regarding educational outputs and the compatibility of educational outputs for the electronic labour market.

There is a direct correlation between smartphones apps professional usage for the learning process, training and skill- development for the private Universities alumni.

The future look of students about smartphones apps for the learning process is associated with the lack of training on these apps.

E-learning and M-Learning

E-learning is still developing slowly in third world countries. The concept of e-learning in most departments in the Iraqi universities focuses on learning computer components and some Microsoft office applications. This deprives students and learners from reaching out the learning materials and methods of identifying the new educational products through computer and mobile phones apps which have fast growing tendencies in the e-markets.

The rapid growth of mobile apps has helped make mobile devices a new tool for learning because, on the one hand, those devices are easily carried and on the other they increasingly support and shorten learning modes and cooperative e-learning (Aghaee and Larsson, 2013 ).

Mobile learning is defined as the type of learning that can be accomplished by using mini computers. Those include smartphones, iPads, and the like which are all considered modes of e-learning (Zhang, 2015a , b ).

Traxler et al. specify mobile learning as all the digital and wireless technological types that are presented for the public and used by higher education learners. Other researchers deplore the concept of mobile learning as the transmission of learning between learners at the same time by using mobile phones (Traxler 2007 ).

Mobile learning has become a relatively new tool for the learning process of many students who found it easy to use the many options available for them such as websites, net pages concerned with learning and training, and mobile apps that facilitate and support the learning activities.

Smartphones and iPads contribute to leaning process greatly as students use the educational content they offer in such a way that let them control their content especially when there are no laptops or desktops available (Kimura, n.d. ).

Published studies concerned with mobile learning appeared in 2000. Sharples discussed in Computer and Learning Journal the possibility of using new designs for personal mobile phones that can support teaching programs for students for different specialities and the many opportunities for them (Sharples 2000 ). Based on Sharples, many articles and researches have been conducted circulating around mobile learning and its relation to e-learning.

In recent years, many researchers have focused on mobile learning, its statistics, users of those teaching modes as conducted by Liu et al. (Liu et al. 2009 ). A study of Paul TJ James has focused on the dependency of mobile devices in doing learning and education. This dependency is not itself in all countries in which the researchers have discovered this case separately vis those researchers (James 2008 ).

Mobile learning is relatively new among students as its launching has not exceeded five years. Crompton et al. has tackled the mobile learning in educational fields. It has been found that the spread of mobile phone apps is very common in various university context specifically university primary studies. The study has also found that most previous studies and researches had focused on designing mobile learning systems while there is a necessity to conduct the effects of mobile learning (Crompton and Burke, 2014 ).

Lohr’s study has presented the use of iPads for higher education sector. The study reveals that those devices enhance the learning experience but not the outcome of the educational institutions (Lohr 2011 ).

The current studies provide a general insight for the current trends of mobile learning for universities and educational institutions. Furthermore, those studies do not provide a detailed analysis for the private educational institutions.

The role of Mobile apps for higher education

According to the International Union of communication and the International Bank league of information communication technology report in 2016, Iraq is considered a good place for using smartphones for various fields (Mobile cellular subscriptions n.d. ).

Higher education sector has been undergoing a multiple usage of mobile apps in various worldwide universities (Ten billion downloads n.d. ). Some of those apps have been used as teaching tools, study guide, college apps marketing, freshmen guide, and admission and registration regulations (Mobile Learning Application 2017 ). Those apps aim at preparing students for college life experiences and saving time and energy for study. Teaching based apps help students write down lectures, testing their knowledge, and peers cooperation (Zhang, 2015a , b ).

Mobile apps have been developed to be used on smartphones and iPads. Their earlier versions such as mobile tune games, tune editor, calculators, and calendars have been developed and increased rapidly. Companies and app developers and engineers start producing certain app categories targeting certain users including various speciality college students. But generally, those apps serve college students in different departments.

Strain explained that mobile apps marketing was mainly concerned with mobile application industry that manufacturers various platforms for certain users. Since then, higher education has dealt with mobile application industry intensively. For instance, Google has launched its educational mobile apps in 2006, while Apple has in 2008.

For years, educational mobile apps has become millions profit fund especially those concerned with college students. Besides, mobile apps in higher education sector represent a subsidiary field used for fund raising and probably designed for special aspect of the student’s experience (GSMA establishment).

Mobile apps can be considered learning aids. Medical students can find anatomy app a useful tool for learning. Also, mobile apps help in astronomical supervision and phenomena and those that mimic the lab environment for students of organic chemical departments and many others ((Suki 2013 ); (Fraknoi 2011 ); (Dekhane and Tsoi, 2012 )).

Numerous studies reveal that students predict a positive impact from mobile learning. That is, students think that mobile phones help them engage with relevant material and raise their confidence as learners (Mueller et al. 2012 ). Moreover, those mobile phones and apps contain many categories having learning tools and traits, short, mid, and final exams notifications, learning videos issued by teaching staff, and others that achieve success for students’ learning process (Sass 2015 ). The availability of those mobile phones, students are interested to cope with the college updates through those apps instead of desktop computer. Students believe that their colleges should support such apps. While some studies show that students spend more time using desktop computer to reach out the same information they can have in less time if they use mobile apps. This gives rise to students to use mobile apps.

As a response to this demand, universities have developed an app specified for university, college, or department. Those apps are not educational but referential to help students reach out college announcements, calendars, exams seating plans and schedules, training and developmental courses and many other activities. This increasing usage must be coped with an increase in e-training of how to use those apps and the best methods to utilize information technology and communication resources those apps provide.

Data collection and analysis

The study has been conducted at Al-Maarif University College – Anbar - Iraq. Research sample consists of some students from departments of Law, English Language, Finance and Banking, Arabic Language, and Medical Laboratory Techniques Departments. A questionnaire has been conducted for data collection. It consists of 16 questions including the dependent and stable research variables. 100 copies have been distributed among research sample and only 92 ones have been regained. This questionnaire is divided into qualitative and quantitative. The quantitative data consists of (10) closed questions while the quantitative data consists of (6) questions representing the outcomes of research variables.

Quantitative data analysis (closed questions)

The first ten questions of the questionnaire have been divided into four axes:

Knowing how to use mobile phones apps in the education process.

Using mobile phones apps and websites for learning.

Training and skill development using mobile phones apps.

E-research and e-lectures by using mobile phones apps.

Students’ answers percentages for the first ten closed questions are presented in (Table 1 ).

Answers have been analysed according to Likert’s triple scale using SPSS program as in (Table 2 ). The internal consistency (Cronbach’s alpha factor) for the four axes was 0.805.

After examining the relation between the research variables, it has been found that there is a positive correlation between the axis “knowing how to use of mobile apps” and the axis “training and developing those skills”. This relation is manifested by Pearson correlation of (0.736) at a correlation level (0.01). This relation shows although students have not received any training, their knowledge and personal-taught skills for those apps are the motives to develop the required learning app usage. This is an indication of the importance of “knowing how to use and how to use” mobile phones and apps in developing students’ skills and motivating them to gain experience throughout professional usage of those apps and this support the first hypothesis as in (Table 3 ).

Table 3 shows a positive correlation between study based e-research and training and developing skills in which the correlation is (0.612) at a correlation level (0.01). There is an increase correlation when an increase of mobile apps training and their insertion as a teaching mode causes an increase in research on the Internet looking for resources and e-lectures which validates the second hypothesis.

Qualitative data analysis (open questions)

Examine the research sample answered about the time consumed on Internet for resource search and learning requirements, the percentages of those answered are as the following:

The reasons of such usage and reactions are as the following:

Lack of training of the using speciality-related mobile apps.

Difficulty in using pages and websites that support the learning process and related courses.

Language problems in all learning apps are developed with a foreign language.

The future anticipation of students about the role of smartphones and their support for e-learning throughout e-lectures. Percentages have revealed that answers classification as the following:

Reasons vary between the lack of support of private universities and colleges for those programs and the poor computer and smartphones technology teaching curricula especially in the humanitarian specialities.

Answers for the open-ended section concerning computer and smartphones technology and its role in enhancing learning methods and activities, percentages have revealed:

Concerning the section of the quality of electronic devices students’ preferred use for learning and coping with scientific advances of studying, specialization, and educational requirement, percentages reveal the following:

However, the responses to item (D) by the sample (92 students) that supported the use of mobile and mobile apps as an effective tool in learning and skills development were not identical in all departments as in Fig.  1 . The departments of English language and Medical laboratory techniques strongly supported the use of smart phone applications in the smart learning environment. Because of the large number of mobile applications on the web-stores that support effectively the learning processes and skill development in the above departments.

The use of mobile, laptop and iPads in learning process and skill development

The departments of Arabic language and law did not support the use of smart phone applications as their colleagues in other departments because most applications do not directly support the Arabic language and the weakness of use English language.

It has been shown that the majority of students prefer using smartphones for learning and coping with scientific advances. Students’ answers concerning the open section of supporting the insertion of computer and smartphones technology training validate research hypotheses. 86.95% of students have agreed upon the insertion of speciality-related computer and smartphones technology training in curricula. This validates the third hypothesis.

The last section concerning websites and pages students prefer using for learning purposes and skill enhancement by using smartphones, its percentages are as illustrated in (Fig. 2 ).

Websites searching by using smartphones

Conclusion and suggestions

Results of the present study are summarized as the following:

Optimal usage of computer and smartphones apps can enhance the outcomes of private universities and colleges providing well-trained and electronically qualified alumni for the requirements of working industry market.

Many international universities and colleges have started to update higher education sector systems by using information technology and communication and depending on it for reconstruction investment.

The increasing investment in information technology and communication will help increase private universities and college’s scientific integrity and novelty of those establishments by their adaptation of the new various teaching programs.

Suggestions

There is the need to highlight the role of technology for higher education sector and prepare the proper procedures to equip students with the best methods for the best usage.

There must be as part of private college curricula a serious tendency for the insertion of information technology and communication training programs by of using on the new and requirement-based applications.

The study presents a new hypothesis in accordance with the use of technology as a teaching tool. Thus, colleges are required to be aware of these technologies to facilitate and direct the learning process.

The past five years have come up with a tremendous outcome in the advanced techniques and strategies of information technology by focusing on investing in the cloud auctions and super-similar devices. Furthermore, profit-change management in the higher education sector can be handled throughout this technology in which Iraqi private universities and colleges would be the raw material for this change.

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MAA carried out the molecular genetic studies, participated in the sequence alignment, participated in the design of the study, performed the statistical analysis and drafted the manuscript. MFA participated in the revision of English language and helped to draft the manuscript. Both authors read and approved the final manuscript.

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Al-Mashhadani, M.A., Al-Rawe, M.F. The future role of mobile learning and smartphones applications in the Iraqi private universities. Smart Learn. Environ. 5 , 28 (2018). https://doi.org/10.1186/s40561-018-0077-7

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The Complete Guide To Building Educational Apps In 2024: From Concept To Launch

February 05, 2024

The average consumer spends $5.05 on mobile apps per smartphone as of the 3rd quarter of 2023. It is statistics by Statista . Mobile applications help us to communicate, entertain ourselves, and get information. Many apps are used for educational purposes. Universities and schools worldwide are already using mobile apps to facilitate the educational process. But how do you create effective mobile apps for education?

This article discusses types of educational apps, core features of educational applications, and the education application development process.

What is app development for education?

Types of educational apps, how to build an educational app: core features, popular technologies for educational application development, examples of mobile applications for education, education application development process.

Educational app is software designed specifically to enhance and simplify the learning process and provide additional features for users. It is designed for various devices, such as smartphones and tablets, making it accessible and easy to use. One of the key features of educational apps is flexibility. Users can choose from various subjects, topics, and difficulty levels, allowing them to tailor the learning experience to individual needs and interests. Some educational applications have adaptive algorithms that automatically determine the level of knowledge and select the appropriate material.

Educational apps are a powerful tool for modern education that can make learning more accessible, personalized, and effective. They are a part of digital transformation in education .

They usually contain a lot of interactive content, such as video, audio, animations, texts, and quizzes, which makes the learning process visual and attractive. The learning process becomes more motivating and engaging through gamification, promoting long-term learning. Also, an important aspect of educational apps is the ability to track progress and evaluate results. Many apps offer statistics, error analysis, and recommendations for improvement, allowing users to evaluate their achievements and identify weaknesses for further development.

3 main advantages of app development for education

Pros of educational apps:

• Anytime & anywhere accessibility. Learners can study at their own pace and without geographical limitations.
• Interactivity. Interactive tasks allow learners to interact and understand the material more thoroughly.
• Adaptability. Many learning apps use ML algorithms to adapt to each learner’s proficiency level.

Educational apps can complement traditional teaching methods but should not completely replace them.

You can develop different types of educational apps. This variety allows users to choose the most appropriate tool for learning and development. Here are the main types of educational apps:

• Language learning apps. One of the popular trends in the field of educational applications is learning foreign languages. Such apps offer extensive lessons, dictionaries, grammar rules, and interactive exercises. They help people learn vocabulary, improve pronunciation, and practice reading, writing, and listening skills. Some of them offer adaptive courses that automatically adjust the complexity of the material to the user’s level of knowledge.
• Science learning apps. These applications help you learn different scientific disciplines, such as math, physics, chemistry, and biology. They reinforce knowledge by providing theoretical material, formulas, examples, and interactive problems. Users can absorb new knowledge more easily by visualizing and explaining complex concepts.
• Programming applications. Programming is becoming an increasingly sought-after skill, and many learning apps offer courses to learn different programming languages, algorithms, and technologies. They provide an understanding of the basics and provide hands-on assignments and projects to practice skills and improve your portfolio.
• Art learning apps. This category includes apps designed for learning music, painting, design, photography, and other creative disciplines. They offer theoretical knowledge, master classes from professionals, and practical assignments to develop creative skills and express yourself.
• Apps for developing cognitive skills. These apps aim to improve memory, attention, logical thinking, and other cognitive functions. They contain a variety of workouts, puzzles, games, and challenges designed to stimulate the mind and keep the brain active.
• Self-development and personal growth apps. This category includes apps that help improve communication skills, conflict resolution, self-motivation, time organization, and other important aspects of personal growth. They provide tips, theoretical materials, and practical exercises for self-reflection and development of emotional intelligence.
• Test prep apps. Many students have difficulty preparing for exams, and these apps are designed to make the preparation process more systematic and effective. They provide tutorials, tips, sample tests and exams, and the ability to track progress and analyze mistakes.
• Apps for teachers and parents. This category of applications helps teachers and parents organize the learning process by providing tools for creating lesson plans, tracking student progress, communicating with parents and colleagues, and evaluating the effectiveness of instruction.
• Professional development apps. These applications are designed for professionals in different industries who want to upgrade their skills, learn, or master new technologies. These apps offer specialized courses, seminars, webinars, and other educational materials.
• Encyclopedic apps. These apps contain a wealth of information on various topics and subjects, giving users quick access to facts, definitions, statistics, and other information. They can be helpful for a wide range of users, whether students, teachers, researchers, or just curious users who want to learn something new or check facts.

Modern educational apps cover various topics and areas, allowing users to learn conveniently and interactively. Thanks to their flexibility and accessibility, these educational apps are becoming an increasingly popular tool for people of different ages and professions who want to improve their skills, deepen their knowledge in a particular field, or simply enrich their horizons.

Educational software development should consider core features to ensure an effective and convenient learning process. Here are the main features that you should implement during educational app development:

• Personalization. Apps should allow the user to choose their level of knowledge, interests, and learning objectives. This will allow the learning material to be tailored to individual needs and preferences, making learning more effective and motivating.
• Interactivity. Good learning apps should include various content such as text, audio, video, animations, and interactive elements. This approach makes the learning process visual, engaging, and interesting.
• Gamification. Introducing gamified elements such as achievements, points, rankings, rewards, and levels promotes user engagement and retention, making learning more engaging and stimulating.
• Progress tracking. The app should provide the ability to track learning progress, record the results of tests and quizzes, analyze mistakes, and provide recommendations on how to improve results. This will help users monitor their progress and identify areas that need more work.
• Feedback. Feedback from teachers, experts, or other users is important for developing and adjusting the learning process. It helps the user to better understand their mistakes and receive constructive criticism for further growth.
• Offline access. Learning apps should provide access to materials even when no internet connection, allowing users to continue learning at any time and place.
• Social integration. The ability to share successes, discuss challenges, and ask questions in the user community or through social media helps create a supportive and mutually beneficial learning environment. This facilitates sharing experiences and knowledge among users.
• Regular content updates. Apps should regularly update their educational content, add new courses and lessons, and incorporate user feedback to improve content. This is necessary to maintain user interest and keep information up-to-date.
• Cross-platform. Learning apps should be available on different devices and platforms, such as smartphones, tablets, computers, and web browsers.
• User-friendly interface. Apps should have an intuitive and simple interface, providing quick access to content and features without unnecessary steps. This is important for a comfortable and productive learning experience.

Custom app development should consider a variety of functionalities. These functionalities aim to meet users’ individual needs, keep them motivated, and provide effective learning. Thanks to these features, modern educational apps can significantly simplify and enrich the learning process, making it accessible, engaging, and effective for users of different ages and knowledge levels.

Many technologies can be used to create mobile apps for education. Below are 4 of the most popular technologies for learning app development:

• React Native. It is an open-source mobile app-building platform based on JavaScript and React. It allows developers to create Android and iOS apps using the same code.
• Flutter. It is an open-source mobile app-building platform developed by Google. It uses the Dart programming language and allows developers to create beautiful, high-performance Android and iOS apps.
• Kotlin. It is a programming language that can be used to create mobile apps for Android. It is considered more modern and user-friendly than Java and allows developers to create more efficient code.
• Swift. It is a programming language that can be used to create mobile apps for iOS. Apple developed it and has many features that make it easier to create iOS apps.

The educational app tech stack depends on your requirements, budget, and deadlines.

Many educational mobile apps are available on the App Store and Google Play. Below are several examples of mobile applications for education.

It is a mobile app that provides access to over 3,000 courses from leading universities and organizations worldwide. The app allows users to learn new topics, earn certificates, and participate in online courses.

It is a mobile application for learning foreign languages. It takes a game-based approach to learning and allows users to learn in 36 languages. The app contains a variety of lessons, including grammar, pronunciation, reading, and writing.

Khan Academy

It is a mobile app that provides access to free educational resources such as video lessons, tests, and exercises. The app allows users to study math, science, history, economics, etc.

It is a mobile app for learning, memorizing, and repeating material. It contains multiple sets of cards that can be used to learn various subjects, including foreign languages, math, history, and more. The app also contains a game feature that allows users to repeat material by playing a game.

Creating mobile apps for education requires certain skills and knowledge. The education application development process consists of :

• Discovery phase . The first step in creating a mobile app for education is research. You need to understand what problems you want to solve with the app and what features it should have. You also need to study the target audience and their needs.
• App design. After research, you can start designing the mobile app. This is where you determine how the app interface will look, what features will be available, and how they will work.
• App development. After designing, the development of the app begins. For this, you must choose the platform you will develop the app (iOS or Android). Then, you can use special tools like Android Studio or Xcode to create the app.
• App testing & optimization. After developing the app, testing & optimization follows. You must ensure the application is secure and meets all the requirements. Testing of the app can be done manually or with the help of automated tests.
• App release & marketing. After successful testing, you can release the app on the App Store or Google Play. After the release, promotion & marketing of the app follow. You must create an attractive app description, take screenshots, create a video review, and decide on the pricing policy.

Each stage of educational application development has its own peculiarities and nuances that require careful planning, coordination, and control. At SoloWay Tech , we use a comprehensive approach to mobile app development. We pay attention to all stages of development to ensure the creation of a high-quality, effective, and successful educational application.

Mobile apps for education are a new way of learning that can improve the efficiency of the educational process. They can be used to learn different subjects and languages, as well as to increase student motivation. When creating mobile apps for education, it is necessary to consider users’ needs and use modern technologies such as React Native, Flutter, Kotlin, and Swift. Besides, a good marketing strategy and a user-friendly interface are necessary to successfully promote the app. Want to develop your own educational app? Contact us!

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Use of smartphone applications in english language learning—a challenge for foreign language education.

1. Introduction

Is the use of mobile apps beneficial and/or effective, in the learning of English as a foreign language? (If so, why, in what ways, and how?)

• The period of the publishing of the article was limited from 1 January 2015 up to 30 April 2019;
• Only reviewed full-text studies in scientific journals in English were included;
• Only experimental/quasi-experimental studies were included;
• The primary outcome focused on the association of the effectiveness of the use of smartphone apps in the learning of English as a foreign language.
• Conference papers, e.g., [ 7 , 8 , 16 ], review studies, e.g., [ 1 , 3 ], and original papers not focusing on smartphone apps for the learning of English as a second language, e.g., [ 17 , 18 ], were excluded.

4. Discussion

5. conclusions, author contributions, acknowledgments, conflicts of interest.

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Kacetl, J.; Klímová, B. Use of Smartphone Applications in English Language Learning—A Challenge for Foreign Language Education. Educ. Sci. 2019 , 9 , 179. https://doi.org/10.3390/educsci9030179

Kacetl J, Klímová B. Use of Smartphone Applications in English Language Learning—A Challenge for Foreign Language Education. Education Sciences . 2019; 9(3):179. https://doi.org/10.3390/educsci9030179

Kacetl, Jaroslav, and Blanka Klímová. 2019. "Use of Smartphone Applications in English Language Learning—A Challenge for Foreign Language Education" Education Sciences 9, no. 3: 179. https://doi.org/10.3390/educsci9030179

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Developing Mobile Apps for Educational Purposes

Education and the need to timely acquire it is something we continuously complain about but can’t live without. It is the ultimate toolbox of every modern human being. Becoming a literate member of society has long ceased to be a luxury, it is a must. But as the time goes on, demands rise, pandemics hit, and so on, up-to-date education must transform accordingly in order to stay accessible, efficient, and useful in general.

Mobile learning, among other modern formats, helps achieve just that. Student loans, SATs, pricey tutors, and heavy books are things of the past. Today, all the paperwork is replaced by affordable and handy educational mobile apps. You too may aim to reform teaching/studying with the app idea you have in mind. So let’s go through all the why’s and how’s of educational applications. 

Why Mobile Learning?

For over a century, education processes have taken place in a classroom – be it at school, university, or specialized courses. Technology, and especially its mobility, have transformed the way students perceive education into an interactive process that can be easily continued even after they leave the classroom. 

Providing the next level of educational convenience, a technologically-driven, mobile approach to studying brings a number of ultimate benefits to the table.

Accessibility & affordability

Back in the day, there was a Stanford professor of computer sciences that decided to launch online classes in several of his subjects. Certainly, he expected to get to educate a couple ten thousand students. However, he did not expect this number to go over a hundred for each course. 

The world is huge: there are people from various countries, speaking different languages, having different financial and physical capabilities, etc. Technology has enabled absolutely everyone, no matter their background or social aspect, to afford to study. All it takes is figuring out what exactly you want to learn and looking up the relevant app. 

Engagement enhancement

In the US, students massively praised remote education opportunities for their ultimate convenience and affordability during the latest wave of enrollment in 2021. That’s why they do not consider studying as something too boring and out of date. In fact, it comes naturally when associated with such a common thing as a smartphone. 

Providing students with easy-to-use interactive applications allows maintaining the communication between them and the educational institution or the brand, or whoever the provider is. 

Collaboration

Apps provide means for 24/7 communication with fellow students and teachers, which positively influences the amount of time they spend in the app and teaches them the basics of networking. 

Continuousness

According to Statista, people spend about 4 hours per day on their smartphones. Mobile application gives the opportunity to continue studying whenever and wherever one may need. It turns learning into an ongoing process that never ends. Instead of being a short-term relationship, your app may become their daily source of entertainment through learning. 

Types of Educational Apps

Education apps make up the third (9.6%) and second (10.4%) most downloaded category of apps in App Store and Google Play respectively. And while some may associate education only with the dull school curriculum, it is the opposite. All those piano playing, language studying, puzzle solving and online learning. The education app development does not stand still introducing more and more interesting concepts. So far the most distinct types of mobile apps for education are: 

Multipurpose learning platforms

Educational platforms do not limit themselves to only one course or one scientific sphere. One would be able to find and enroll in any course of even a full-scale graduate program no matter the age, financial status, nationality or any other obstacles (e.g., Google Classroom , iTunes U , Stepik , etc.). 

Let’s look at the example of Coursera that started as a Stanford-only online platform and developed into the site of enormous possibilities in education. Thus, while it sounds impressive, creating a similar compatible product requires a lot of funds, time, and database capacity.

Specific subject learning app

Countless apps focus on providing the studying process for only one particular subject varying from Duolingo for language studies to Yousician for mastering new music instruments.

Supportive apps

These are the apps that do not teach. Instead, they help to ease the studying process. Some apps deal with small tasks like solving the equation written in the notebook ( Photomath ) or correcting the grammar ( Grammarly ).

Educational games

Studying is good, but interactive studying is better. Training the brain inside a gamified environment allows students to take their mind off heavy stuff while continuing to pick up something new. Khan Academy’s app does a great job at engaging users through adventurous gamification.

Learning management app

These are apps that can be used collectively by members of a specific educational institution or separately by students for their purposes (e.g., Schoology , Canvas Student , etc.). They are designed to handle the formalities and ease the communication between school and student regarding personal schedules, attendance control, work submission, grading and so on.

Educational apps for preschoolers and toddlers

The brain of the small toddler works differently from those old enough to attend school. Their attention span is shorter and comprehending abilities are still in the phase of early development. Particular applications aimed at children aged 0-5 are bright, gamified and interactive to grab kid’s interest and make sure they learn in the process of being entertained (check out Endless Alphabet and Prodigy Math Game ). 

Main Set of Features for Any Educational App

Usually, the application development process consists of similar common phases: planning, design, set of features, testing and deployment. You can read more about it here . 

Educational apps are not different. They may include the most different features and learning modules, but the most common features every educational application development team should foresee are:

Registration/Log-in

Though creativity cannot be taught, it can certainly be nurtured. Find a routine that works for you. Routines can be positive if they reinforce a healthy, creative mindset; they can be counterproductive if they actually keep you from being creative. 

While breaking your routine once in a while to force new ways of thinking is good, what if growing/learning/experiencing new things was built into your routine as a given? The people who speak negatively about routine have probably not developed a routine that puts them on a path of internal growth. 

The key is to discover creative rituals that put you in a more creative mindset.

Customizable profile

The most significant part of the education app user community is students. They should have an ability to have a personal page with information about who they are, what faculty or grade they belong to, what classes they take, what assignments are due, and access to their grades (if it can also show the approximate GPA, that’d be awesome). 

To develop this feature your education app developers will need from 115 to 140 hours. 

Show users the sudden changes in the timetable based on classes they take or teach in case of lecturers. 

Average development time – 130 hours. 

Courses page

Surely, every class or course should have its own separate page with a detailed plan, lectures, schedule, assignments, information about the lecturer themselves, a list of students attending and any other essential information. 

Development is going to take – 80 hours. 

Audio & Video streaming

The mechanics behind a streaming is that the ongoing stream goes to the server where it is converted and sent to the user that watches the broadcast. At the same time, the video is recorded and stored if needed. However, the time limits for storing are decided by the developers and depend on storing and processing capacities of servers. 

Apart from online courses taken in real time, users also need to have an ability to re-watch the lecture or re-listen to the broadcast that is a part of their curriculum. So it’d be better to think about the server part in advance. 

For a simple MVP, about 80 hours for frontend and 80 hours for backend will be enough. However, the top-notch steaming feature can take up as far as 600 hours to build. 

Some students would like to check out the courses their friends take or learn about what they will be having next year. Developing a detailed search with different features is going to enhance their user experience. 

Time needed 110 hours. 

Push notifications

Students and lecturers would like to get notified about all the slightest changes that occur in their studying/teaching process like shifts in timetables, new assignments and grades, deadlines and so on. 

Creating push notifications takes about 90 hours.

Offline mode

Yes, the offline mode. Give your students the ability to access all necessary data offline with downloadable lectures and course materials, saved answers to tests, etc. this way they won’t be able to say that connection was poor, so they did not revise the content. 

Time for building the offline mode takes about 60 hours.

The most valuable thing to tune is the database that is going to store all the information about ongoing, past and future courses, personal information of every user and their education process, and all course materials. 

The amount of time needed to set up a database successfully cannot be calculated before actually doing it. In real life, it can take months just to set it up. 

Approximate Time-Cost Estimate

In short, education has turned into a lifelong process, and mobile application is one of the tools that allows making it real. 

The mobile education industry is growing momentum as the development process is relatively simple. There is no need for complicated integrations; the most important parts are the intuitive design and logic behind the app. Moreover, you do not have to generate the contest, as it is either available online or developed by faculty staff themselves. 

If you have an idea how to brighten up the education process, we are ready to implement it for you. Contact us at [email protected] .

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Mobile Applications for education processes

1. mobile applications for education processes, 3. what is mobile application, 4. conclusion, 5. 3 types of app, 6. 4 advantages of using mobile apps in the classroom, 7. 1.ebooks and online study, 8. 2.miscellaneous functions, 9. 3.enhanced parent teacher communication, 10. 4.new learning methods.

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Windows installation guide.

• October 05, 2023 15:57

Minecraft Education is available in the Microsoft Store

Before you begin

Before installing Minecraft Education, ensure these prerequisites are met.

• Your PC must meet the system requirements.
• Users need to have the correct permissions based on the setup and installation method used at your organization.
• If installing the app from the Microsoft Store, all apps must be up to date. Minecraft Education cannot be installed if there are updates pending for other apps.

Installation Options

Minecraft Education is available as a desktop installer and through the Microsoft Store. Both versions function the same and have the same features. The difference is in how Minecraft is downloaded and installed. The Windows desktop version is downloaded from the Minecraft Education website. 

To install Minecraft via device management tools, you can choose to install and update via the Microsoft store or using a traditional desktop installer.

The version you choose may depend on your setup. These are the recommended Minecraft Education versions based on common setups.

• When Minecraft Education is installed with the Microsoft Store, app updates are installed through the Microsoft Store. If you block updates to apps, Minecraft Education will not update.
• The Microsoft Store and desktop installer versions of Minecraft Education are incompatible with each other. If you want to switch from one to the other, you must uninstall the other version.
• Delivery Optimization is only supported for the store version of Minecraft Education.

Installation instructions

Install on devices enrolled into microsoft intune using microsoft store app integration.

Intune can deploy apps from the Microsoft Store. For more information, see Add Microsoft Store apps to Microsoft Intune . To deploy Minecraft Education to your Intune managed devices, follow these steps:

• Navigate to Microsoft Intune admin console
• Select Apps , then select All Apps
• Select Microsoft Store app (new) and chooses Select
• Select Search the Microsoft Store app (new)
• Search for Minecraft Education
• Choose Select
• System means install for all users (recommended for most scenarios)
• User means only install for the targeted user or current user of a device
• On the scope tags screen, select scope tags if necessary, then select Next
• Required assignments are installed without user interaction.
• Available assignments enable Minecraft Education to be installed from Company Portal by the targeted users.
• After you’ve made your selection, select Next
• Then select Create
• Result: Minecraft Education will be installed by Microsoft Intune on the targeted users or devices at the next check-in or be made available in Company Portal for optional install.

Instruct users to install from the Microsoft Store

Provide the following instructions for your students and teachers to get the app themselves from the Microsoft Store.

• Open the Microsoft Store app
• Follow instructions to get the app

Install desktop version

Follow these steps to manually install the Windows desktop version of Minecraft Education.

• Download the Minecraft Education desktop installer .
• Result:  The installation file begins downloading to your PC.
• Use the following command line to install the application quietly:
• <exe name. eg MinecraftEducation_x86_1.20.1200.0> /qn

The full list of command line options are:

3. If your software deployment tool has a detection method, you can use the following options:

Install the Microsoft Store version manually

Follow these steps to manually install the Microsoft Store version of Minecraft Education.

• Download the  Minecraft Education appxbundle.
• Result:  If a pop-up asks approval to open the app installer, select  Open Installer
• From the app installer, ensure  Launch when ready is selected and select  Install .
• Result:  After Minecraft Education finishes installing, Minecraft Education opens.
• Note: This requires the Desktop App Installer application to be installed.

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A definitive plan for your college admissions process.

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CAMBRIDGE, MASSACHUSETTS - JULY 08: A view of the campus of Harvard University on July 08, 2020 in ... [+] Cambridge, Massachusetts. Harvard and Massachusetts Institute of Technology have sued the Trump administration for its decision to strip international college students of their visas if all of their courses are held online. (Photo by Maddie Meyer/Getty Images)

Navigating the college admissions process can be a daunting journey for students and parents alike. However, with a comprehensive plan and strategic approach , this journey can be transformed into a manageable and rewarding experience. Here’s a definitive plan for navigating the college application process.

Laying The Foundation

The first step in the college application process is to organize and plan meticulously. Begin by finalizing your college list , which will be the road map for your applications. This involves researching colleges, understanding their requirements, and aligning them with your career goals and interests. Your high school’s internal tools, such as Naviance and Scoir, are fantastic resources to help you dive deeply into your options. Speaking with college-based contacts , such as alumni of your high school, and taking virtual tours can provide insight into the experiences at specific college campuses.

Familiarize yourself with application platforms like Common App and Coalition App. These platforms will be your gateway to submitting your applications. So, understanding how to navigate them efficiently is key. Maintain a checklist to ensure all components of your application are completed and submitted on time. Remember, the Common App opens on August 1, and it’s essential to check for any changes to prompts and requirements.

Recently, some universities have adjusted their requirements for standardized testing, including Harvard, Yale, Dartmouth, Brown, MIT, and Caltech. It’s important to stay updated on each college’s requirements, as policies may vary. Staying informed and prepared will help you navigate these changes smoothly.

Gather letters of recommendation, transcripts, and other supporting documents to ensure a complete application package. Tools like application platforms and checklists will be invaluable in keeping you organized and on track.

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Once you have your list, creating a comprehensive master calendar is essential. Tools like Google Calendar or Notion can help you map out all your deadlines so nothing slips through the cracks. This master calendar will be your guide as you navigate through the myriad of tasks ahead.

Crafting Your Personal Narrative

Your personal statement is a critical component of your application, offering a glimpse into who you are beyond grades and test scores. Begin brainstorming topics that reflect your unique experiences and passions. Reflect deeply on significant life events, challenges, and achievements that have shaped you. Seek inspiration from past successful essays to provide you with examples of compelling narratives that resonate with admissions officers.

As you draft your personal statement, remember that revision is key. Seek feedback from trusted advisors and mentors to refine your essay. Tools like Grammarly and the Hemingway App can assist in ensuring your writing is clear, concise, and impactful. Having the essay assessed by a trusted team of reviewers with experience in admissions can support you in ensuring your narrative will resonate with the audience of college admissions officers .

Tackling Supplemental Essays

Supplemental essays provide an opportunity to demonstrate your fit for specific colleges. Taking virtual and in-person tours can provide you with personalized data to show how your story fits your targeted colleges. Start by drafting essays for early application schools. These essays should highlight specific examples why you are a good match. Show your enthusiasm for the school and your intended major, and use specific examples to illustrate your points.

Finalizing Early Applications

As early application deadlines approach, it’s crucial to finalize all materials. This includes completing final revisions on essays and preparing additional documents like resumes and activity lists. Attention to detail can make the difference between a good application and a great one. Make sure every component is perfect before submission.

Don't forget to check in with your teachers regarding your deadlines that they can align the timing of their letters of recommendation with your college submissions.

Early Application Submissions And Refinements

With your early applications ready, submit them and continue refining essays for regular decision schools. Stay organized and ensure all deadlines are met. Conduct thorough final reviews of your early applications and begin preparing regular decision essays. This phase is about ensuring everything is polished and ready for submission.

Perform final proofreads of your early application essays and start drafting and refining essays for remaining colleges. Remember, meticulous preparation and thoughtful reflection are essential to achieving your academic dreams.

Finalizing Regular Decision Applications

As you move closer to the end of the process, focus on finalizing all regular decision application essays and materials. Gather letters of recommendation, transcripts, and other supporting documents to ensure a complete application package. Tools like application platforms and checklists will be invaluable in keeping you organized and on track.

Submit all remaining applications and confirm receipt to ensure everything has been successfully submitted. This final step certifies that all your hard work culminates in successful submissions.

Await Additional Requirements

Colleges may invite you to interview or to submit additional information after your initial required submission. Stay on top of notifications to your application portals and proactively check inside of your portal to ensure you haven’t missed any additional requests. For example, last cycle, some colleges such as Brown and the University of Chicago gave the option of a video introduction inside their portals after submission.

If your family is applying for financial aid, be sure to check for any deadlines related to the FAFSA, CSS profile, and individual scholarship essays.

The college admissions process is a marathon, not a sprint. By following a structured plan and using available resources, you can navigate this journey with confidence and poise. Remember, the key to success lies in detailed preparation, thoughtful reflection, and continuous improvement. With a clear plan and the right support, you can transform the college application process from a daunting task into a rewarding journey.

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Mobile Applications in Modern Social and Cultural Educational Practices

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• First Online: 21 January 2023
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• Yuliia Polovynchak 5 &
• Viktoriia Bondarenko 5  

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 159))

Included in the following conference series:

• International Conference of Artificial Intelligence, Medical Engineering, Education

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The paper is devoted to the study of the development of educational mobile applications. By comparing the specifics of their distribution over the past five years, the authors found out the main trends in their distribution. Firstly, the formation of complex, multi-thematic and multi-format platforms for providing access to training courses has been defined as such. Secondly, the tendency to formalize self-education (the possibility of obtaining official certificates confirming the successful completion of the course). Thirdly, the growing role of various types of mobile applications as tools in the classical learning process. The principle of collaboration of different institutions in the creation of complex and high-tech mobile applications has also been noted as a trend. The connection between changes in the audience of educational services and the specifics of mobile applications as their tools has been substantiated. Emphasis has been placed on such characteristics of mobile applications as interactivity, virtuality, multimodality, personalization, and gamification.

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Acknowledgment

Yuliia Polovynchak made conclusions regarding the socio-cultural impact of modern digital capabilities of mobile applications.

Viktoriia Bondarenko studied mobile applications as one of the tools of education and self-education.

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International Center of Informatics and Computer Science, Faculty of Applied Mathematics, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine

Zhengbing Hu

School of Computer Science, Hubei University of Technology, Wuhan, China

Halmos College of Arts and Sciences, Nova Southeastern University, Fort Lauderdale, FL, USA

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Polovynchak, Y., Bondarenko, V. (2023). Mobile Applications in Modern Social and Cultural Educational Practices. In: Hu, Z., Ye, Z., He, M. (eds) Advances in Artificial Systems for Medicine and Education VI. AIMEE 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 159. Springer, Cham. https://doi.org/10.1007/978-3-031-24468-1_31

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DOI : https://doi.org/10.1007/978-3-031-24468-1_31

Published : 21 January 2023

Publisher Name : Springer, Cham

Print ISBN : 978-3-031-24467-4

Online ISBN : 978-3-031-24468-1

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