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A Model of Motivational and Technological Factors Influencing Massive Open Online Courses’ Continuous Intention to Use

Author

Listed:
  • Samer Ali Al-shami

    (Institute of Technology Management and Entrepreneurship, Universiti Teknikal Malaysia Melaka, Melaka 76100, Malaysia)

  • Salem Aldahmani

    (Institute of Technology Management and Entrepreneurship, Universiti Teknikal Malaysia Melaka, Melaka 76100, Malaysia)

  • Massila Kamalrudin

    (Fakulti Teknologi Maklumat dan Komunikasi, Universiti Teknikal Malaysia Melaka, Melaka 76100, Malaysia)

  • Nabil Hasan Al-Kumaim

    (Faculty of Technology Management and Technopreneurship, Universiti Teknikal Malaysia Melaka, Melaka 76100, Malaysia)

  • Abdullah Al Mamun

    (Graduate School of Business, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia)

  • Mohammed Al-shami

    (Yemen Faculty of Education, Sana’a University, Sana’a 1247, Yemen)

  • Mustafa Musa Jaber

    (Department of Medical Instruments Engineering Techniques, Al-Turath University College, Baghdad 10021, Iraq
    Department of Medical Instruments Engineering Techniques, Alfarahidi University, Baghdad 10021, Iraq)

Abstract

Massive open online courses have been regarded as effective technological innovations that improve educational systems in the era of digitalisation. However, only 10% of the registered students complete their courses. This study aims to examine the motivational and technological factors and contextual features on students’ continuous intention to use. A questionnaire was gathered from 315 of students in the UAE and revealed that social motivational and technological factors driven by the technology acceptance model and technology task fit theory significantly influenced the students’ continuance intention to use. This study also revealed that contextual features including language use and course accreditation are important indicators determining students’ behaviours toward the use. Hence, this study proposed an integrative model to explain ways to improve continuance intention to use. This study contributes to the sustainable use of massive open online courses in developing countries through an integrative model.

Suggested Citation

  • Samer Ali Al-shami & Salem Aldahmani & Massila Kamalrudin & Nabil Hasan Al-Kumaim & Abdullah Al Mamun & Mohammed Al-shami & Mustafa Musa Jaber, 2022. "A Model of Motivational and Technological Factors Influencing Massive Open Online Courses’ Continuous Intention to Use," Sustainability, MDPI, vol. 14(15), pages 1-23, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:9279-:d:874571
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    References listed on IDEAS

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    1. Liyong Wan & Shoumei Xie & Ai Shu, 2020. "Toward an Understanding of University Students’ Continued Intention to Use MOOCs: When UTAUT Model Meets TTF Model," SAGE Open, , vol. 10(3), pages 21582440209, July.
    2. Liao, Chechen & Palvia, Prashant & Chen, Jain-Liang, 2009. "Information technology adoption behavior life cycle: Toward a Technology Continuance Theory (TCT)," International Journal of Information Management, Elsevier, vol. 29(4), pages 309-320.
    3. Ann Bourke, 2000. "A Model of the Determinants of International Trade in Higher Education," The Service Industries Journal, Taylor & Francis Journals, vol. 20(1), pages 110-138, January.
    4. Robert M. Fuller & Alan R. Dennis, 2009. "Does Fit Matter? The Impact of Task-Technology Fit and Appropriation on Team Performance in Repeated Tasks," Information Systems Research, INFORMS, vol. 20(1), pages 2-17, March.
    5. Raquel L. Pérez-Nicolás & Carlos Alario-Hoyos & Iria Estévez-Ayres & Pedro Manuel Moreno-Marcos & Pedro J. Muñoz-Merino & Carlos Delgado Kloos, 2021. "Evaluation of an Algorithm for Automatic Grading of Forum Messages in MOOC Discussion Forums," Sustainability, MDPI, vol. 13(16), pages 1-18, August.
    6. Sujeet Kumar Sharma, 2019. "Integrating cognitive antecedents into TAM to explain mobile banking behavioral intention: A SEM-neural network modeling," Information Systems Frontiers, Springer, vol. 21(4), pages 815-827, August.
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