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Impact of motivation and technology factors to predict satisfaction and continued intentions toward online courses

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  • Qing Wang

    (School of Economics and Management, Huazhong Agricultural University, Wuhan 430072)

  • Muhammad Saqib Khan

    (Huazhong University of Science and Technology 1037, Luoyu Road, Wuhan, 430074)

Abstract

The rapid developments and diffusion of new technologies abruptly changed world dynamics. This study pursued the motivational factors (controlled and autonomous) and technology factors (perceived ease of use and perceived usefulness) to predict the students perceived satisfaction and continued intention toward MOOCs. Using an online survey, this research collected data from 333 students, and analysis performed through PLS-SEM. The findings revealed that controlled motivation positively influenced the perceived satisfaction. However, autonomous motivation positively affected students perceived satisfaction and continued intention toward MOOCs. The technology factors such as PEU strongly impacted PU. Similarly, PU positively impacted students perceived satisfaction and continued intention toward MOOCs. This research guides essential theoretical insights and provides practical guidelines to educational institutions and technologists to develop and implement systems and strategies in online environments. Key Words:Controlled motivation, autonomous motivation, technology acceptance model, perceived satisfaction, continued intention

Suggested Citation

  • Qing Wang & Muhammad Saqib Khan, 2021. "Impact of motivation and technology factors to predict satisfaction and continued intentions toward online courses," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 10(3), pages 501-513, April.
    • Handle: RePEc:rbs:ijbrss:v:10:y:2021:i:3:p:501-513
    DOI: 10.20525/ijrbs.v10i3.1148
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    References listed on IDEAS

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    1. Fred D. Davis & Richard P. Bagozzi & Paul R. Warshaw, 1989. "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, INFORMS, vol. 35(8), pages 982-1003, August.
    2. Necmi K. Avkiran & Christian M. Ringle (ed.), 2018. "Partial Least Squares Structural Equation Modeling," International Series in Operations Research and Management Science, Springer, number 978-3-319-71691-6.
    3. Qing Wang & Muhammad Saqib Khan & Muhammad Kamran Khan, 2021. "Predicting user perceived satisfaction and reuse intentions toward Massive Open Online Courses (MOOCs) in the Covid-19 pandemic," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 10(2), pages 1-11, March.
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