STUDENTS’ PREFERENCES OF LEARNING MATERIALS DURING UNPRECEDENTED ONLINE LEARNING DUE TO COVID-19

Authors

  • ‘Atifah Hanim Rosli Department of Computer Science, Universiti Pertahanan Nasional Malaysia, Malaysia
  • Norshahriah Abdul Wahab Department of Computer Science, Universiti Pertahanan Nasional Malaysia, Malaysia
  • Syed Nasir Alsagoff Department of Computer Science, Universiti Pertahanan Nasional Malaysia, Malaysia
  • Mohd Rizal Mohd Isa Department of Computer Science, Universiti Pertahanan Nasional Malaysia, Malaysia
  • ‘Afizi Mohd Shukran Department of Computer Science, Universiti Pertahanan Nasional Malaysia, Malaysia

DOI:

https://doi.org/10.22452/mjcs.sp2021no1.4

Keywords:

Online learning, human computer interaction, gamification

Abstract

Teaching and learning processes in higher education have been affected due to the COVID-19 pandemic. Face-to face learning has been transitioned to online learning. This study explored student preferences for online materials during unprecedented online learning due to COVID-19. Through an online questionnaire, quantitative data was collected from 104 students from the Department of Computer Science, Faculty of Defence and Science Technology. The factors focused on in analysing the student’s preferences in online learning material include the layout, and multimedia analytics approach. The results present how multimedia analytics such as video, audio, graphic, and animation in online learning material play a significant role in the cognitive engagement and student’s motivation in online learning. Also, respondents preferred online learning materials with element of multimedia such as video and audio, rather than text only. This study presents suggestions on how to enhance online learning materials to improve online learning.

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Published

2021-12-17

How to Cite

Rosli, ‘Atifah H. ., Abdul Wahab, N. ., Alsagoff, S. N. ., Mohd Isa, M. R. ., & Mohd Shukran, ‘Afizi . (2021). STUDENTS’ PREFERENCES OF LEARNING MATERIALS DURING UNPRECEDENTED ONLINE LEARNING DUE TO COVID-19. Malaysian Journal of Computer Science, 38–44. https://doi.org/10.22452/mjcs.sp2021no1.4

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