Keep Learning: Student Engagement in an Online Environment
Keywords:Student engagement, motivation to learn, self-efficacy, online learning, and online education
Student engagement is a key factor in promoting learning and academic achievement. This study explores the factors underlying student engagement and the best practices advocated by students and faculty to engage students. Results revealed that student motivation to learn and self-efficacy are positively associated with student engagement. In addition, self-efficacy partially mediated the relationship between motivation to learn and student engagement. Finally, both faculty and students suggested diverse and inclusive techniques to engage students. Online education may become our new reality, and adjustment to this new world requires shifting to a new pedagogical paradigm.
Abid, T., Zahid, G., Shahid, N., and Bukhari, M. (2021). Online Teaching Experience during the COVID-19 in Pakistan: Pedagogy–Technology Balance and Student Engagement. Fudan Journal of the Humanities and Social Sciences, 1-25.
Allen, M., Mabry, E., Mattrey, M., Bourhis, J., Titsworth, S., and Burrell, N. (2004). Evaluating the effectiveness of distance learning: A comparison using meta‐analysis. Journal of communication, 54(3), 402-420.
Arbuckle, J. L. (1997). Amos user's guide version 3.6. Chicago. SmallWaters Corporation.
Azila-Gbettor, E. M., Mensah, C., Abiemo, M. K., and Bokor, M. (2021). Predicting student engagement from self-efficacy and autonomous motivation: A cross-sectional study. Cogent Education, 8(1), 1942638.
Bandura, A. (1977). Self-efficacy: toward a unifying theory of behavioral change. Psychological review, 84(2), 191.
Bandura, A. (1982). Self-efficacy mechanism in human agency. American psychologist, 37(2), 122.
Bandura, A. (1986). The explanatory and predictive scope of self-efficacy theory. Journal of social and clinical psychology, 4(3), 359-373.
Bandura, A. (1991). Social cognitive theory of self-regulation. Organizational behavior and human decision processes, 50(2), 248-287.
Bandura, A. (2001). Social cognitive theory: An agentic perspective. Annual review of psychology, 52(1), 1-26.
Bandura, A. (2006). Guide for constructing self-efficacy scales. Self-efficacy beliefs of adolescents, 5(1), 307-337.
Banna, J., Lin, M. F. G., Stewart, M., and Fialkowski, M. K. (2015). Interaction matters: Strategies to promote engaged learning in an online introductory nutrition course. Journal of online learning and teaching/MERLOT, 11(2), 249.
Bao, Ii. 2020. COVID‐19 and online teaching in higher education: A case study of Peking University. Human Behavior and Emerging Technologies 2(2):113–115.
Brophy, J. (1987). Synthesis of research on strategies for motivating students to learn. Educational leadership, 45(2), 40-48.
Chen, B., Chang, Y. H., Ouyang, F., and Zhou, W. (2018). Fostering student engagement in online discussion through social learning analytics. The Internet and Higher Education, 37, 21-30.
Chen, E., Kaczmarek, K., and Ohyama, H. (2020). Student perceptions of distance learning strategies during COVID‐19. Journal of dental education.
Chiu, T. K. (2021). Student engagement in K-12 online learning amid COVID-19: A qualitative approach from a self-determination theory perspective. Interactive Learning Environments, 1-14.
Coates, H. (2005). The value of student engagement for higher education quality assurance. Quality in higher education, 11(1), 25-36.
Coleman, P. K., and Karraker, K. H. (1998). Self-efficacy and parenting quality: Findings and future applications. Developmental review, 18(1), 47-85.
Deci, E. L., and Ryan, R. M. (2008). Self-determination theory: A macrotheory of human motivation, development, and health. Canadian psychology/Psychologie canadienne, 49(3), 182.
Dixson, M. D. (2015). Measuring student engagement in the online course: The Online Student Engagement scale (OSE). Online Learning, 19(4), n4.
D’Mello, S. K. (2021). Improving student engagement in and with digital learning technologies. OECD Digital Education Outlook 2021 Pushing the Frontiers with Artificial Intelligence, Blockchain and Robots: Pushing the Frontiers with Artificial Intelligence, Blockchain and Robots, 79.
Floyd, F. J., and Widaman, K. F. (1995). Factor analysis in the development and refinement of clinical assessment instruments. Psychological assessment, 7(3), 286.
Fredricks, J. A., Blumenfeld, P. C., and Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of educational research, 74(1), 59-109.
Gist, M. E., and Mitchell, T. R. (1992). Self-efficacy: A theoretical analysis of its determinants and malleability. Academy of Management review, 17(2), 183-211.
Hartnett, M. (2016). Motivation in online education. Singapore: Springer.
Judge, T. A., and Bono, J. E. (2001). Relationship of core self-evaluations traits—self-esteem, generalized self-efficacy, locus of control, and emotional stability—with job satisfaction and job performance: A meta-analysis. Journal of applied Psychology, 86(1), 80.
Kelloway, E. K. (1998). Using LISREL for structural equation modeling: A researcher's guide. Sage.
Knowles, M. S., Holton, E. F., and Swanson, R. A. (2005). The adult learner 6th edition. Burlington, MA: Elsevier.
Kuh, G. D. (2009). The national survey of student engagement: Conceptual and empirical foundations. New directions for institutional research, 2009(141), 5-20.
Kuh, G. D., Kinzie, J. L., Buckley, J. A., Bridges, B. K., and Hayek, J. C. (2006). What matters to student success: A review of the literature (Vol. 8). Washington, DC: National Postsecondary Education Cooperative.
Lear, J. L., Ansorge, C., and Steckelberg, A. (2010). Interactivity/community process model for the online education environment. Journal of online learning and teaching, 6(1), 71-77.
Little, T. D., Cunningham, W. A., Shahar, G., and Widaman, K. F. (2002). To parcel or not to parcel: Exploring the question, Iighing the merits. Structural equation modeling, 9(2), 151-173.
Luszczynska, A., Gutiérrez‐Doña, B., and Schwarzer, R. (2005). General self‐efficacy in various domains of human functioning: Evidence from five countries. International journal of Psychology, 40(2), 80-89.
Manning-Ouellette, A., and Black, K. M. (2017). Learning leadership: A qualitative study on the differences of student learning in online versus traditional courses in a leadership studies program. Journal of Leadership Education, 16(2), 59.
Martin, F., and 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.
Masika, R., and Jones, J. (2016). Building student belonging and engagement: insights into higher education students’ experiences of participating and learning together. Teaching in Higher Education, 21(2), 138-150.
Millican, J., and Bourner, T. (2011). Student‐community engagement and the changing role and context of higher education. Education+ Training.
Noe, R. A. (1986). Trainees' attributes and attitudes: Neglected influences on training effectiveness. Academy of management review, 11(4), 736-749.
Noe, R. A., and Wilk, S. L. (1993). Investigation of the factors that influence employees' participation in development activities. Journal of applied psychology, 78(2), 291.
O'Leary, A. (1992). Self-efficacy and health: Behavioral and stress-physiological mediation. Cognitive therapy and research, 16(2), 229-245.
Pajares, F. (2002). Self-efficacy beliefs in academic contexts: An outline.
Pajares, F., and Schunk, D. H. (2001). Self-beliefs and school success: Self-efficacy, self-concept, and school achievement. Perception, 11(2), 239-266.
Pintrich, P. R., and De Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of educational psychology, 82(1), 33.
Price, D. V., and Tovar, E. (2014). Student engagement and institutional graduation rates: Identifying high-impact educational practices for community colleges. Community College Journal of Research and Practice, 38(9), 766-782.
Reeve, J. (2013). How students create motivationally supportive learning environments for themselves: The concept of agentic engagement. Journal of educational psychology, 105(3), 579.
Robbins, S. B., Lauver, K., Le, H., Davis, D., Langley, R., and Carlstrom, A. (2004). Do psychosocial and study skill factors predict college outcomes? A meta-analysis. Psychological bulletin, 130(2), 261.
Schunk, D. H. (1989). Social cognitive theory and self-regulated learning. In Self-regulated learning and academic achievement (pp. 83-110). Springer, New York, NY.
Siemens, L., Althaus, C., and Stange, C. (2013). Balancing students’ privacy concerns while increasing student engagement in e-learning environments. In Increasing Student Engagement and Retention in E-Learning Environments: In 2.0 and Blended Learning Technologies. Emerald Group Publishing Limited.
Simmering, M. J., Posey, C., & Piccoli, G. (2009). Computer self‐efficacy and motivation to learn in a self‐directed online course. Decision Sciences Journal of Innovative Education, 7(1), 99-121.
Singh, K., and Abdullah, B. (2020). Influence of self-efficacy on student engagement of senior secondary school students. Executive Editor, 11(01), 119.
Skrypnyk, O., Joksimović, S., Kovanović, V., Gašević, D., and Dawson, S. (2015). Roles of course facilitators, learners, and technology in the flow of information of a cMOOC. The International Review of Research in Open and Distributed Learning, 16(3).
Soffer, T., and Nachmias, R. (2018). Effectiveness of learning in online academic courses compared with face‐to‐face courses in higher education. Journal of Computer Assisted Learning, 34(5), 534-543.
Tannenbaum, S. I., Mathieu, J. E., Salas, E., and Cannon-BoIrs, J. A. (1991). Meeting trainees' expectations: The influence of training fulfillment on the development of commitment, self-efficacy, and motivation. Journal of applied psychology, 76(6), 759.
Zeiss, A. M., Gallagher-Thompson, D., Lovett, S., Rose, J., and McKibbin, C. (1999). Self-efficacy as a mediator of caregiver coping: Development and testing of an assessment model. Journal of clinical Geropsychology, 5(3), 221-230.
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