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Mobile Learning in Higher Education: A Systematic Literature Review

Author

Listed:
  • Quadri Noorulhasan Naveed

    (College of Computer Science, King Khalid University, Abha 61413, Saudi Arabia)

  • Heena Choudhary

    (Department of Humanities and Social Sciences, Malaviya National Institute of Technology Jaipur, Jaipur 302017, India)

  • Naim Ahmad

    (College of Computer Science, King Khalid University, Abha 61413, Saudi Arabia)

  • Jarallah Alqahtani

    (College of Computer Science and Information Systems, Najran University, Najran 66462, Saudi Arabia)

  • Adel Ibrahim Qahmash

    (College of Education, King Khalid University, Abha 61413, Saudi Arabia)

Abstract

Mobile learning (M-Learning) has become a popular and effective method of education that leverages the ubiquity of mobile devices. M-Learning has digitally transformed the process of teaching and learning. It has tremendous potential to empower all sections of society through education and training. This study presents a systematic literature review of M-Learning. The articles were retrieved from Scopus and Web of Science databases. After applying inclusion and exclusion criteria, a final selection of 161 articles published between 2016 and 2022 was included in the review. To analyze the articles, the researchers employed the TCCM (Theory, Context, Characteristics, Methods) framework, which facilitated addressing the research questions. This review identified various theories, such as behaviorism, constructivism, cognitivism, situated learning, problem-based learning, context awareness learning, socio-cultural theory, collaborative learning, conversational learning, lifelong learning, informal learning, activity theory, connectivism, navigation, and location-based learning, that are used to support and guide the implementation of M-Learning. In terms of context, developing countries contributed to 70.8% of the studies, while developed countries contributed to 29.1%. Further, a majority of the studies, 93%, involved students followed by faculty members and only two studies involved staff from higher education management. A total of 19 unique characteristic factors have been identified, such as personal, intention, attitude, usage, utility, ease of use, learnability, social, technological, pedagogical, anxiety, enjoyment, accessibility, knowledge, experience, trust, price, and habit. A quantitative research design was used in 90% of the studies, followed by mixed methods research design in 7% of the studies, and qualitative research design in only 3% of the studies. Further, this article synthesizes previous research findings and highlights gaps for future research. Overall, this review contributes to the understanding and advancement of M-Learning as a valuable educational platform.

Suggested Citation

  • Quadri Noorulhasan Naveed & Heena Choudhary & Naim Ahmad & Jarallah Alqahtani & Adel Ibrahim Qahmash, 2023. "Mobile Learning in Higher Education: A Systematic Literature Review," Sustainability, MDPI, vol. 15(18), pages 1-22, September.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:18:p:13566-:d:1237366
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    References listed on IDEAS

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    1. Iuliana Mihaela Lazar & Georgeta Panisoara & Ion Ovidiu Panisoara, 2020. "Digital technology adoption scale in the blended learning context in higher education: Development, validation and testing of a specific tool," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-27, July.
    2. Quadri Noorulhasan Naveed & Mohammad Mahtab Alam & Nasser Tairan, 2020. "Structural Equation Modeling for Mobile Learning Acceptance by University Students: An Empirical Study," Sustainability, MDPI, vol. 12(20), pages 1-17, October.
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    6. Lin, Shu Hsu & Lee, Hsing-Chen & Chang, Ching-Ter & James Fu, Changjui, 2020. "Behavioral intention towards mobile learning in Taiwan, China, Indonesia, and Vietnam," Technology in Society, Elsevier, vol. 63(C).
    7. Mahmood Al-Bashayreh & Dmaithan Almajali & Ahmad Altamimi & Ra’ed Masa’deh & Manaf Al-Okaily, 2022. "An Empirical Investigation of Reasons Influencing Student Acceptance and Rejection of Mobile Learning Apps Usage," Sustainability, MDPI, vol. 14(7), pages 1-14, April.
    8. Saud S. Alghazi & Amirrudin Kamsin & Mohammed Amin Almaiah & Seng Yue Wong & Liyana Shuib, 2021. "For Sustainable Application of Mobile Learning: An Extended UTAUT Model to Examine the Effect of Technical Factors on the Usage of Mobile Devices as a Learning Tool," Sustainability, MDPI, vol. 13(4), pages 1-22, February.
    9. Jasmine A. L. Yeap & T. Ramayah & Pedro Soto-Acosta, 2016. "Factors propelling the adoption of m-learning among students in higher education," Electronic Markets, Springer;IIM University of St. Gallen, vol. 26(4), pages 323-338, November.
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