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Moca, M.; Badulescu, A. Role of Mobile Learning in Education. Encyclopedia. Available online: https://encyclopedia.pub/entry/46123 (accessed on 16 June 2024).
Moca M, Badulescu A. Role of Mobile Learning in Education. Encyclopedia. Available at: https://encyclopedia.pub/entry/46123. Accessed June 16, 2024.
Moca, Mihaela, Alina Badulescu. "Role of Mobile Learning in Education" Encyclopedia, https://encyclopedia.pub/entry/46123 (accessed June 16, 2024).
Moca, M., & Badulescu, A. (2023, June 27). Role of Mobile Learning in Education. In Encyclopedia. https://encyclopedia.pub/entry/46123
Moca, Mihaela and Alina Badulescu. "Role of Mobile Learning in Education." Encyclopedia. Web. 27 June, 2023.
Role of Mobile Learning in Education
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Due to the considerable technological breakthroughs in the education sector, new tools have been developed to improve learning. Motivating students to use new devices for learning rather than just for amusement, however, is a difficulty. The COVID-19 pandemic prompted the adoption of technological devices for course delivery, thereby highlighting the significance of mobile learning (m-learning) and allowing educators, students, and other stakeholders in the education sector to recognize its potential, advantages, drawbacks, and challenges. 

mobile-devices m-learning technology acceptance model

1. Introduction

The teaching and learning pedagogy have undergone significant changes in recent decades due to technological advancements [1][2][3]. With technology being ubiquitous in today’s society, the educational system must adapt to the needs of the new generation of students [4]. The prevalence of mobile devices and wireless connectivity has introduced a new educational paradigm, commonly referred to as mobile learning or m-learning. It comes as no surprise that teachers have been looking for ways to introduce mobile devices into traditional and electronic learning in order to enable students to learn anytime, anywhere, at their own pace, as a shift from “traditional” to “electronic” and later to “mobile” learning [5][6]. Traditional pedagogical approaches have become inefficient over time compared to students’ lifestyles, so there is a need for an adaptation and evolution of these approaches [7]. The COVID-19 pandemic has underscored the importance of flexible and intelligent educational systems. Moreover, the pandemic has also demonstrated that mobile learning has immense potential, and education systems worldwide are increasingly exploring, promoting, and embracing its new features [3][8][9][10]. This trend could indicate the sustainability of m-learning as an educational system.
During the pandemic, the education systems used these technological systems to ensure the continuity of the students’ education [11][12]. The unexpected social isolation brought students and teachers to the situation of connecting through the mobile devices, the transition to remote teaching being realized suddenly and in an unplanned manner [13]. With regard to the education systems in the central-eastern part of Europe, which includes the present study as well, the research carried out during and after the pandemic, in different countries, highlighted the relatively common elements regarding the advantages and disadvantages of m-learning [2]. A research conducted in Romania identified several benefits such as program flexibility, adaptation to diverse learning styles, and access to numerous useful digital tools. However, concerns regarding isolation, anxiety, limited creativity, and student evaluation difficulties were also reported. Nevertheless, a significant portion of students and teachers expressed a positive attitude towards e-learning [14].
A theoretical and empirical cross-country study involving Poland, Croatia, and Serbia [10][15][16] examined the advantages and disadvantages of e-learning during and after the COVID-19 period from the perspective of students and teachers. The study concluded that while there are disadvantages, students believe that the benefits of e-learning outweigh them. Additionally, the study demonstrated that digitization and the adoption of technology-driven pedagogical approaches have been beneficial in the field of education, particularly in economic disciplines.
Preoccupations related to the factors that influenced the adoption of e-learning during COVID-19 in Hungary were also presented in the paper [17], where the analysis focused on the influence of age and gender on the desire, the intention to use e-learning tools, gender having the biggest impact. In the Czech Republic, a comparative analysis between the first and second waves of the pandemic revealed a growing positive attitude towards distance learning compared to in-person classes, aligning with the situations observed in other aforementioned countries [18].
The increasing global usage of mobile devices and the steady growth of internet penetration have led to the adoption of mobile learning. Global statistics data show that, for a population of 8.02 billion [19] at the beginning of 2023, the number of unique mobile subscribers at the end of the first quarter of 2023 was about 5.5 billion people worldwide [20]. At the same time, the number of internet users reached 5.16 billion people worldwide and 4.76 billion social media users [21]. These statistics shows that the mobile technologies are a global context and therefore, this reality cannot be ignored by the educational systems around the world, which should reflect their worldwide usage [22]. As a result, unlike conventional pedagogical approaches, education must take use of the online world because this is where young students interact and connect [23]. The paradigm shift in education is therefore mandatory to ensure future education resilience in the face of changes regarding learning and communication among students.
There is a wide range of reasons why adopting m-learning techniques is important, which includes better access to resources and learning material and the possibility of flexible teaching and learning activities, mostly to be aligned with institutional and business aims [4][24][25]. Possible changes in teaching activities points to the ways in which teachers can use mobile devices as a support element in the teaching content [2][14], while flexible learning refers to the ways in which students have the opportunity to manage their learning activities, at times and places chosen by themselves [8][15][26]. For these technologies to align with educational institutions requires that they be economically efficient by reducing the costs of expensive hardware by adopting wireless technology and mobile learning, for example, and that they provide information to a large number of students regardless of their location [27]. In addition to these arguments that relate more to the practical and technical aspects of teaching-learning, it has been shown in various studies that m-learning has the potential, through different tools, to bring other benefits, such as strengthening cognitive motivation of students [24], of involvement and attention, etc. The benefits of m-learning were summarized in a systematic review by Saikat et al. [3] as follows: the availability of resources, the improvement of communication, the development of the students’ technical skills, a better operationalization of activities and, last but not least, financial benefits. In addition, the novelty effect of different m-learning tools positively influences autonomous motivation, internalization and learning achievements of students [28]. Another argument would be that the support that mobile learning can offer to support metacognitive and cognitive processes in self-regulated learning (SRL), helping students to take control of their learning process, in order to be successful in the academic activity [26].
On the contrary, certain studies have cast doubt on the actual advantages of mobile learning and its limitations. The implementation of m-learning poses numerous challenges, some of which include limited resources, content-related issues across all subject areas (including economic education) [29][30], technical difficulties arising from inadequate knowledge and skills of instructors and students [31][32], distraction from work tasks [33], a large number of users, and the need for online connectivity [29]. The evaluation of mobile learning can also be problematic as it needs to be both transparent and secure, while ensuring that students do not receive assistance from others [34][35]. Furthermore, problems with connectivity, data protection, privacy, and confidentiality may arise in the m-learning environment, as noted by Saikat et al. [3]. One particular challenge that is relevant is the inability to conduct laboratory work for courses that require it in online education. As a result, students studying medicine, engineering, and other technical or economic fields (such as accounting and commerce) are deprived of practical learning experiences in the context of mobile learning, as highlighted by Currie et al. [36].
Despite indisputable arguments regarding the usefulness of mobile technology, it is also important to asses students’ readiness for mobile learning, because just owning and using mobile devices in everyday life does not necessarily mean that students are willing to use them in learning activities [37]. In light of the COVID-19 pandemic, there is a significant focus on this topic, particularly concerning the assessment of students’ acceptance of m-learning and the factors that contribute to the formation of behavioral intentions. The efficacy of m-learning is currently being debated in light of the students’ return to physical classrooms and face-to-face interaction with educators. If this system proves to be sustainable, questions remain about its form and the conditions under which it would be implemented. This issue has garnered considerable attention, as demonstrated by studies conducted by Al-Rahmi et al. [38], Alturki and Aldraiweesh [8], and Al-Emran et al. [39]. Such an analysis must be carried out differently on high school students, university students or for lifelong learning adults because there are essential differentiations between these categories of learners. One important aspect to consider is the availability to purchase the mobile devices, as for college students and adults this is much higher than for the high school students [40]. This must be corroborated with the learning motivation that differs markedly at various stages of academic training and after. Another argument is that universities are much more prepared and willing to introduce different applications and elements of m-learning as an official policy of institutions, than high schools, where teachers usually act individually. University autonomy allows a more efficient university management in achieving an adequate and high-performance information technology infrastructure, as well as in raising students’ awareness towards new technologies [41].

2. Mobile Learning

There is a wide range of research on mobile learning. With the development of wireless technology, the field has continuously grown and is experiencing rapid evolution in the last few years, especially after the period of the COVID-19 pandemic. Upon analyzing the literature, it was observed that the terms “mobile learning” and “m-learning” are used interchangeably with a surplus of definitions. This has led to confusion and an absence of clear pedagogical theoretical framework in research on mobile learning. Therefore, there is ongoing debate regarding the meanings of these terms and their impact on educational issues [42].
There is also an aspect related to the ambiguity of term “mobile” that has to be highlighted: The term ’mobile’ refers to either mobile technologies, learner mobility or content mobility where each of these aspects has an important meaning [43]. Most conceptualizations define mobile learning from the perspective of the technological devices used and suggest that mobile learning is delivered or achieved entirely or largely through mobile technologies, even if this approach is considered too technocentric and presents some constraints [5]. Another definition given by Almaiah and Alismaiel [41] defines m-learning as a new learning technology that helps students carry out their educational activities, using mobile devices with which they can access courses, assignments, quizzes or tools evaluation. Practically, it can be observed that the term mobile learning is a topic frequently associated in research with how to use mobile devices, rather than focusing on solving educational problems, respectively improving learning performance [44].
Maybe the most important aspect that differentiate mobile learning from other pedagogical approaches is the ability for the students to perform learning activities without being tied to a certain fixed location, by using mobile devices to access and communicate information, through wireless technology [45]. This model of distance education, using mobile devices, is very favorable and advantageous for the students, who have the opportunity to be educated independent of time and environment [46]. A study by Grant [42] synthesized the current definitions of the terms and concluded that a learning environment involving mobile learning must have certain characteristics to generate learner engagement. These include the student having mobility, being autonomous, having mobile devices available to them at all times, having data services that are always available, having content that is mobile and adapted to the students’ needs and context, and incorporating tutors (embedded).
Therefore, the design and the implementation of mobile learning requires an approach in which the pedagogical and technical aspects are relevant and compatible. Thus, several studies have been conducted on the efficiency of mobile devices in the field of education, on learners’ readiness, or on acceptance of mobile learning by the students [25][47][48] or by the teachers [49]. Some studies have analyzed the most relevant variables that influence the university students’ attitude towards mobile technologies [50][51] or the determinants of the acceptance of mobile technologies among teachers [52]. On the technical side, other studies focus on tools and applications that can be used in mobile learning, as well as their benefits and limitations [4][24]. The use of mobile communication combined with internet tools create a stronger connection between instructor and student without increasing the pressure sometimes the student could feel from their instructors, a bond which might have the effect of increasing students’ motivation [53]. Also, the inclusion in the learning process of a mobile application for student self-assessment or assessment produces an improvement in student achievement and a positive students’ attitude towards new technologies [54][55]. In the literature, the mobile learning research conducted along these directions has focused on investigating the benefits and drawbacks of this type of learning.
These research directions raise technical and pedagogical cultural related issues. The sustained technological developments in the last years gradually eliminate the technological limitations of m-learning related to the small screen size of mobile devices, network speed, battery life or the limited memory of the devices. This happens even if the hardware devices and technical systems are created and marketed for corporate, retail, or recreational users and their use for educational purposes is parasitic and of secondary use [40]. Still, it is difficult to adapt a pedagogical culture to a mobile format, because this implies an adaptation of all the actors involved in the teaching and learning processes, respectively learners, instructors, curricula, educational contents and institutions [56]. Also, a bibliometric mapping shows that the most used keywords in research on mobile learning are mobile devices, mobile technologies, smartphone, tablet and higher education. Also, in recent years, the most frequently addressed topics were related to educational technologies and educational strategies [57].
Recent research on m-learning has focused on the role of mobile applications and social media in promoting critical thinking skills, comprehension, analysis, and synthesis during the learning process. However, it has been noted by Audrin and Audrin [58], Pedro et al. [32], Hosain et al. [59], and Eynon [60] that the use of these applications can also have negative effects that need to be recognized and understood. It should be noted that these applications and social media platforms are primarily designed for commercial purposes, and their use in formal education can be detrimental to learning as they are more geared towards leisure activities. Moreover, existing research on m-learning does not adequately cover the educator’s perspective on the use of mobile applications, and there is a lack of theoretical and pedagogical foundations that make the integration of different m-learning strategies incompatible with the curriculum [32][61]. As a result, the orchestration of mobile devices with didactic methods and strategies requires constant adaptation, which generates a strong interest in research, irrespective of the field in which they are applied.

References

  1. Granić, A. Educational Technology Adoption: A systematic review. Educ. Inf. Technol. 2020, 27, 9725–9744.
  2. Dečman, N.; Rep, A. Digitalization in Teaching Economic Disciplines: Past, Current and Future Perspectives. Bus. Syst. Res. 2022, 13, 1–7.
  3. Saikat, S.; Dhillon, J.S.; Wan Ahmad, W.F.; Jamaluddin, R.A. A Systematic Review of the Benefits and Challenges of Mobile Learning during the COVID-19 Pandemic. Educ. Sci. 2021, 11, 459.
  4. Hartley, K.; Andújar, A. Smartphones and Learning: An Extension of M-Learning or a Distinct Area of Inquiry. Educ. Sci. 2022, 12, 50.
  5. Kukulska-Hulme, A.; Traxler, J. Designing for mobile and wireless learning. In Rethinking Pedagogy for a Digital Age; Beetham, H., Sharpe, R., Eds.; Routledge: London, UK; Routledge: New York, NY, USA, 2007; pp. 180–192.
  6. Krotov, V. Critical Success Factors in M-Learning: A Socio-Technical Perspective. Commun. Assoc. Inf. Syst. 2015, 36, 6.
  7. Bile, A. Development of intellectual and scientific abilities through game-programming in Minecraft. Educ. Inf. Technol. 2022, 27, 7241–7256.
  8. Alturki, U.; Aldraiweesh, A. Students’ Perceptions of the Actual Use of Mobile Learning during COVID-19 Pandemic in Higher Education. Sustainability 2022, 14, 1125.
  9. Almaiah, M.A.; Al-Otaibi, S.; Lutfi, A.; Almomani, O.; Awajan, A.; Alsaaidah, A.; Alrawad, M.; Awad, A.B. Employing the TAM Model to Investigate the Readiness of M-Learning System Usage Using SEM Technique. Electronics 2022, 11, 1259.
  10. Mališ, S.S.; Sačer, I.M.; Žager, K. Landscape of e-Learning during COVID-19: Case Study of Economic Disciplines in Croatia. Bus. Syst. Res. 2022, 13, 8–27.
  11. Nikou, S.; Maslov, I. An analysis of students’ perspectives on e-learning participation—The case of COVID-19 pandemic. Int. J. Inf. Learn. Technol. 2021, 38, 299–315.
  12. Sukendro, S.; Habibi, A.; Khaeruddin, K.; Indrayana, B.; Syahruddin, S.; Makadada, F.A.; Hakim, H. Using an extended Technology Acceptance Model to understand students’ use of e-learning during COVID-19: Indonesian sport science education context. Heliyon 2020, 6, e05410.
  13. Hodges, B.C.; Moore, S.; Lockee, B.B.; Trust, T.; Bond, A. The difference between emergency remote teaching and online learning. Educ. Rev. 2020, 27. Available online: https://er.educause.edu/articles/2020/3/the-difference-between-emergency-remote-teaching-and-online-learning (accessed on 24 May 2023).
  14. Ionescu, C.A.; Paschia, L.; Gudanescu Nicolau, N.L.; Stanescu, S.G.; Neacsu Stancescu, V.M.; Coman, M.D.; Uzlau, M.C. Sus-tainability Analysis of the E-Learning Education System during Pandemic Period—COVID-19 in Romania. Sustainability 2020, 12, 9030.
  15. Głodowska, A.; Wach, K.; Knežević, B. Pros and Cons of e-Learning in Economics and Business in Central and Eastern Europe: Cross-country Empirical Investigation. Bus. Syst. Res. 2022, 13, 28–44.
  16. Brozović, M.; Ercegović, M.; Meeh-Bunse, G. e-Learning in Higher Institutions and Secondary Schools during COVID-19: Crisis Solving and Future Perspectives. Bus. Syst. Res. 2022, 13, 45–71.
  17. Jamalova, M.; Bálint, C. Modelling Students’ Adoption of E-Learning during the COVID-19 Pandemic: Hungarian Perspective. Int. J. Emerg. Technol. Learn. 2022, 17, 275–292.
  18. Andres, P.; Dobrovská, D.; Vanecek, D.; Miština, J. The Impact of the Pandemic Crisis on Technology Standard of Traditional University Education. In Mobility for Smart Cities and Regional Development—Challenges for Higher Education; Auer, M.E., Hortsch, H., Michler, O., Köhler, T., Eds.; ICL 2021—Lecture Notes in Networks and Systems; Springer: Cham, Switzerland, 2021; Volume 390.
  19. Available online: https://www.worldometers.info/world-population/ (accessed on 23 March 2023).
  20. Available online: https://www.gsmaintelligence.com/data/ (accessed on 25 March 2023).
  21. Available online: https://www.statista.com/statistics/617136/digital-population-worldwide/ (accessed on 24 March 2023).
  22. Traxler, J. 2013 Mobile learning: Shaping the frontiers of learning technologies in global context. In Mobile Learning: Shaping the Frontiers of Learning Technologies in Global Context; Huang, R., Kinshuk, J., Michael, S., Eds.; Spinger: Berlin/Heidelberg, Germany, 2013; pp. 237–251.
  23. Cladis, A.E. A shifting paradigm: An evaluation of the pervasive effects of digital technologies on language expression, creativity, critical thinking, political discourse, and interactive processes of human communications. E-Learn. Digit. Media 2018, 17, 341–364.
  24. Lebedeva, M.; Taranova, M.; Beketov, V. Assessment of academic achievements in m-learning. Educ. Inf. Technol. 2022, 28, 5945–5965.
  25. Kumar, S.; Sigh, B. What drives students to adopt m-learning apps? The role of e-WOM in signalling theory perspective. Behav. Inf. Technol. 2022.
  26. Baars, M.; Viberg, O. Mobile Learning to Support Self-Regulated Learning: A Theoretical Review. Int. J. Mob. Blended Learn. 2022, 14, 1–12.
  27. Traxler, J.; Kukulska-Hulme, A. 2005 Evaluating mobile learning: Reflections on Current Practice. In Proceedings of the mLearn 2005: Mobile Technology: The Future of Learning in Your Hands, Cape Town, South Africa, 25–28 October 2005.
  28. Jeno, L.M.; Vandvik, V.; Eliassen, S.; Grytnes, J.-A. Testing the novelty effect of an m-learning tool on internalization and achievement: A Self-Determination Theory approach. Comput. Educ. 2019, 128, 398–413.
  29. Wairiya, M.; Shah, A.; Sahu, G.P. Mobile Learning Adoption: An Empirical Study. In Proceedings of the 2020 IEEE 10th In-ternational Conference on Cloud Computing, Data Science & Engineering (Confluence), Uttar Pradesh, India, 29–31 January 2020; pp. 757–761.
  30. Bolu, C.A.; Azeta, J.; Mallo, S.J.; Ismaila, S.O.; Dada, J.O.; Aderounmu, S.; Ismail, A.; Oyetunji, E. Engineering Students’ Virtual Learning Challenges during COVID-19 Pandemic Lockdown: A Case Study. In Proceedings of the 2020 IFEES World Engineering Education Forum-Global Engineering Deans Council (WEEF-GEDC), Cape Town, South Africa, 16–19 November 2020; pp. 1–5.
  31. Afonso, P.; Trindade, B.; Santos, D.; Pocinho, R.; Silveira, P.; Silva, P. Teachers’ Adaptation to Technologies during the Pandemic by COVID-19. In Proceedings of the Eighth International Conference on Technological Ecosystems for Enhancing Multiculturality, Salamanca, Spain, 21–23 October 2020; pp. 817–820.
  32. Pedro, L.F.M.G.; Barbosa, C.M.M.O.; Santos, C.M. A critical review of mobile learning integration in formal educational contexts. Int. J. Educ. Technol. High. Educ. 2018, 15, 10.
  33. Nyasulu, C.; Chawinga, W.D. Using the decomposed theory of planned behavior to understand university students’ adoption of WhatsApp in learning. E-Learn. Digit. Media 2019, 16, 413–429.
  34. Mena, J.; Singh, B.; Clarke, A. New challenges for teacher education introduced by the use of ICT in the classrooms. In Proceedings of the Eighth International Conference on Technological Ecosystems for Enhancing Multiculturality, Salamanca, Spain, 21–23 October 2020; pp. 859–861.
  35. Crick, T.; Knight, C.; Watermeyer, R.; Goodall, J. The Impact of COVID-19 and “Emergency Remote Teaching” on the UK Computer Science Education Community. In Proceedings of the United Kingdom & Ireland Computing Education Research Conference, Glasgow, UK, 3–4 September 2020; pp. 31–37.
  36. Currie, G.; Hewis, J.; Nelson, T.; Chandler, A.; Nabasenja, C.; Spuur, K.; Barry, K.; Frame, N.; Kilgour, A. COVID-19 Impact on Undergraduate Teaching: Medical Radiation Science Teaching Team Experience. J. Med. Imaging Radiat. Sci. 2020, 51, 518–527.
  37. Corbeil, J.; Valdes-Corbeil, M. Are you ready for mobile learning? Educ. Quat. 2007, 30, 51–58.
  38. Al-Rahmi, A.M.; Al-Rahmi, W.M.; Alturki, U.; Aldraiweesh, A.; Almutairy, S.; Al-Adwan, A.S. Acceptance of mobile technologies and M-learning by university students: An empirical investigation in higher education. Educ. Inf. Technol. 2022, 27, 7805–7826.
  39. Al-Emran, M.; Arpaci, I.; Salloum, S.A. An empirical examination of continuous intention to use m-learning: An integrated model. Educ. Inf. Technol. 2020, 25, 2899–2918.
  40. Traxler, J. Defining, Discussing and Evaluating Mobile Learning: The moving finger writes and having writ…. Int. Rev. Res. Open Distrib. Learn. 2007, 8, 1–13.
  41. Almaiah, M.A.; Alismaiel, O.A. Examination of factors influencing the use of mobile learning system: An empirical study. Educ. Inf. Technol. 2019, 24, 885–909.
  42. Grant, M.M. Difficulties in defining mobile learning: Analysis, design characteristics, and implications. Educ. Technol. Res. Dev. 2019, 67, 361–388.
  43. Kukulska-Hulme, A. Will mobile learning change language learning? ReCALL 2009, 21, 157–165.
  44. Reeves, T.C.; Reeves, P.M. Reorienting educational technology research from things to problems. Learn. Res. Pract. 2015, 1, 91–93.
  45. Kukulska-Hulme, A. Mobile usability and user experience. In Mobile Learning: A Handbook for Educators and Trainers; Kukulska-Hulme, A., Traxler, J., Eds.; Routledge: London, UK, 2005; pp. 45–56.
  46. Koruku, A.; Alkan, A. Differences between m-learning (mobile learning) and e-learning, basic terminology and usage of m-learning in education. Procedia Soc. Behav. Sci. 2011, 15, 1925–1930.
  47. Gόmez-Ramirez, I.; Valencia-Arias, A.; Duque, L. Approach to m-learning acceptance among university students: An integrated model of tpb and tam. Int. Rev. Res. Open Distrib. Learn. 2019, 20, 141–164.
  48. Alyoussef, I.Y. Factors Influencing Students’ Acceptance of M-Learning in Higher Education: An Application and Extension of the UTAUT Model. Electronics 2021, 10, 3171.
  49. Teo, T. A path analysis of pre-service teachers’ attitudes to computer use: Applying and extending the technology acceptance model in an educational context. Interact. Learn. Environ. 2010, 18, 65–79.
  50. Teo, T.; Zhou, M. Explaining the intention to use technology among university students: A structural equation modeling approach. J. Comput. High. Educ. 2014, 26, 124–142.
  51. Al-Rahmi, A.M.; Al-Rahmi, W.M.; Alturki, U.; Aldraiweesh, A.; Almutairy, S.; Al-Adwan, A.S. Exploring the Factors Affecting Mobile Learning for Sustainability in Higher Education. Sustainability 2021, 13, 7893.
  52. Sánchez-Prieto, J.C.; Olmos-Migueláñez, S.; García-Peñalvo, F.J. Informal tools in formal contexts: Development of a model to assess the acceptance of mobile technologies among teachers. Comput. Hum. Behav. 2016, 55, 519–528.
  53. Rau, P.-L.P.; Gao, Q.; Wu, L.-M. Using mobile communication technology in high school education: Motivation, pressure, and learning performance. Comput. Educ. 2008, 50, 1–22.
  54. e-Marcos, L.; Hilera, J.; Barchino, R.; Jiménez, L.; Martínez, J.J.; Gutiérrez, J.A.; Gutiérrez, J.M.; Otόn, S. An experiment for improving students performance in secondary and tertiary education by means of m-learning auto-assessment. Comput. Educ. 2010, 55, 1069–1079.
  55. Zainuddin, Z.; Shujahat, M.; Haruna, H.; Chu, S.K.W. The role of gamified e-quizzes on student learning and engagement: An interactive gamification solution for a formative assessment system. Comput. Educ. 2020, 145, 103729.
  56. Cheon, J.; Lee, S.; Crooks, S.M.; Song, J. An investigation of mobile learning readiness in higher education based on the theory of planned behavior. Comput. Educ. 2012, 59, 1054–1064.
  57. Goksu, I. Bibliometric mapping of mobile learning. Telemat. Inform. 2020, 56, 101491.
  58. Audrin, C.; Audrin, B. Key factors in digital literacy in learning and education: A systematic literature review using text mining. Educ. Inf. Technol. 2022, 27, 7395–7419.
  59. Hossain, S.F.A.; Nurunnabi, M.; Hussain, K. Continuous mobile devices usage tendency in the TPACK-based classroom and academic performance of university students. Technol. Pedagog. Educ. 2021, 30, 589–607.
  60. Eynon, R. Becoming digitally literate: Reinstating an educational lens to digital skills policies for adults. Br. Educ. Res. J. 2021, 47, 146–162.
  61. Price, S.; Davies, P.; Farr, W.; Jewitt, C.; Roussos, G.; Sin, G. Fostering geospatial thinking in science education through a customisable smartphone application. Br. J. Educ. Technol. 2012, 45, 160–170.
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