Online Learning Makes Student Perform Better: A Quantitative Study of Interactivity During Class and Academic Performance Among USIM Students

Affandi Yusran Suhadi; Norsimaa Mustaffa

doi:10.33102/jcicom.vol3no1.84

Authors

Affandi Yusran Suhadi Universiti Sains Islam Malaysia https://orcid.org/0009-0005-9009-6695
Dr. Norsimaa New Media Program, Faculty of Management and Leadership, USIM

DOI:

https://doi.org/10.33102/jcicom.vol3no1.84

Keywords:

Online learning, Student performance, Interactivity during class, Academic performance, USIM students, Quantitative study, E-learningVirtual education, Distance learning, Online education, Learning outcomes, Academic achievement, Student engagement, Educational technology Blended learning

Abstract

The purpose of this thesis is to investigate the effect of interactivity in online learning on student academic performance. Online learning has become a popular method of education, but the lack of interaction in some online courses has been a concern. This study aims to explore the ways in which interactivity in online learning can be enhanced to improve student academic performance. The research was conducted using a quantitative method, with a sample of students enrolled in online courses at a university. Data was collected through a survey, which measured students’ perceptions of interactivity in their online course and their academic performance. The results of the study showed that there is a positive correlation between interactivity in online learning and student academic performance. The findings suggest that incorporating interactive elements, such as discussion boards, collaborative projects, and real-time interactions, can improve student engagement and ultimately lead to better academic outcomes. This research contributes to the understanding of how interactivity in online learning can be used to enhance student academic performance and can serve as a reference for educators and instructional designers in developing interactive online courses.

Downloads

Download data is not yet available.

Author Biography

Dr. Norsimaa, New Media Program, Faculty of Management and Leadership, USIM

References

Al-Salman, S., and Haider, A. S. (2021). Jordanian University Students’ views on emergency online learning during COVID-19. Online Learn. 25, 286–302. doi: 10.24059/olj.v25i1.2470

Ben-Eliyahu, A., Moore, D., Dorph, R., & Schunn, C. D. (2018). Investigating the multidimensionality of engagement: affective, behavioral, and cognitive engagement in science across multiple days, activities, and contexts. Contemporary Educational Psychology, 53, 87–105.

Fortune M, Spielman M and Pangelinan D 2011 Students’ perceptions of online or face-toface learning and social media in hospitality, recreation and tourism Journal of Online Learning and Teaching 7(1) pp 1-16

Gleason, James P., "THE IMPACT OF INTERACTIVE FUNCTIONALITY ON LEARNING OUTCOMES: AN APPLICATION OF OUTCOME INTERACTIVITY THEORY" (2009). University of Kentucky Doctoral Dissertations. Paper 793. http://uknowledge.uky.edu/gradschool_diss/793

Hatlevik, O. E., Throndsen, I., Loi, M., & Gudmundsdottir, G. B. (2018). Students’ ICT self-efficacy and computer and information literacy: Determinants and relationships. Computers & Education, 118, 107–119.

Haider, A. S., and Al-Salman, S. (2020). Dataset of Jordanian university students’ psychological health impacted by using E-learning tools during COVID-19. Data in Brief 32:106104. doi: 10.1016/j.dib.2020.106104

Hu, M. , & Li, H. (2017, June). Student engagement in online learning: A review. 2017 International Symposium on Educational Technology (ISET), 39–43. 10.1109/ISET.2017.17

Jacqueline Wong, Martine Baars, Dan Davis, Tim Van Der Zee, Geert-Jan Houben & Fred Paas (2019) Supporting Self-Regulated Learning in Online Learning Environments and MOOCs: A Systematic Review, International Journal of Human–Computer Interaction, 35:4-5, 356-373, DOI: 10.1080/10447318.2018.1543084

Kauffman H. (2015). A review of predictive factors of student success in and satisfaction with online learning. Research in Learning Technology, 23. https://doi.org/10.3402/rlt.v23.26507 Centers for Disease Control and Prevention. (26 September, 2019). Increase in Developmental Disabilities. https://www.cdc.gov: https://www.cdc.gov/ncbddd/developmentaldisabilities/features/increase-in-developmental-disabilities.html

Kemp N and Grieve R 2014 Face-to-face or face-to-screen? undergraduates’ opinions and test performance in classroom vs. online learning Educational Psychology 5 pp. 1-14

Littlefield J. (2018). The difference between synchronous and asynchronous distance learning. https://www.thoughtco.com/synchronous-distance-learning-asynchronous-distancelearning-1097959 Martin, F. , & Bolliger, D. U. (2018). Engagement matters: Student perceptions on the importance of engagement strategies in the online learning environment. Online Learning, 22(1), 205–222. 10.24059/olj.v22i1.1092

Miao, T.-C., Gu, C.-H., Liu, S., & Zhou, Z. K. (2020). Internet literacy and academic achievement among Chinese adolescent: A moderated mediation model. Behaviour & Information Technology, 1–13. https:// doi. org/ 10. 1080/ 01449 29X. 2020. 18310 74

Michael Anderson, ‘Moving from online to hybrid course delivery: Increasing positive student outcomes’, Journal of Research in Innovative Teaching 6.1 (2013), pp. 80-87

Newmann, F. M., Wehlage, G. G., & Lamborn, S. D. (1992). The significance and sources of student engagement. In F. Newmann (Ed.), Student engagement and achievement in American secondary schools (pp. 11-39). New York, NY: Teachers College Press Parkes,

M., Stein, S., Reading, C. (2014). Student preparedness for university e-learning environments. The Internet and Higher Education, 25, 1–10

Singh V., Thurman A. (2019). How many ways can we define online learning? A systematic literature review of definitions of online learning (1988-2018). American Journal of Distance Education, 33(4), 289–306.

Stec, M., Smith, C., and Jacox, E. (2020). Technology enhanced teaching and learning: exploration of faculty adaptation to iPad delivered curriculum. Technol. Knowl. Learn. 25, 651–665. doi: 10.1007/s10758-019- 09401-0

Song, L., Singleton, E. S., Hill, J. R., Koh, M. H. (2004). Improving online learning: Student perceptions of useful and challenging characteristics. The Internet and Higher Education, 7(1), 59–70

Stern, J. (2020). Introduction to Online Teaching and Learning. Available online at: http://www.sloan-c.org/resources/index.asp (accessed November, 2020). Tsai, C. C., & Lin, C. C. (2004). Taiwanese adolescents' perceptions and attitudes regarding the Internet: Exploring gender differences. Adolescence, 39(156), 725–734.

Yen Chaw, L., & Meng Tang, C. (2019). Driving High inclination to complete massive open online courses (MOOCs): Motivation and engagement factors for learners. The Electronic Journal of e-Learning, 17(2), 118–130.

Yin, H. (2018). What motivates Chinese undergraduates to engage in learning? Insights from a psychological approach to student engagement research. Higher Education, 76(5), 827–847.

Yilmaz, R. (2017). Exploring the role of e-learning readiness on student satisfaction and motivation in flipped classroom. Computers in Human Behavior, 70, 251–260.