Using the Online Engagement Framework to Improve Student Engagement in Online Courses: Based on Process Data Analysis of Two Different Courses

Main Article Content

Wei Xu
Zhao-Ying Yu
Xiang-Ming Wu

Abstract

Online learning has grown rapidly over the past decade or so to become an important part of higher education. There have been more studies highlighting the importance of student learning engagement in traditional classrooms, while research on how to effectively enhance multidimensional student engagement in online courses is still relatively limited. This study aims to explore the effectiveness of the Online Engagement Framework(OEF) in enhancing learners' multidimensional online learning engagement in different online course types by applying it. Therefore, a quasi-experimental study was conducted, involving 120 students who were randomly allocated to two distinct course types. Process data from both courses were systematically collected, processed, and analyzed to evaluate the practical effectiveness of the framework. The results of the study show that the two online courses designed using the OEF have different degrees of improvement in learners' behavioral, cognitive, emotional and social engagement. In contrast, practical courses performed better in cognitive and emotional engagement, while students in theoretical courses were more actively participated in discussions and social interactions, demonstrating higher social engagement. This study provides an important theoretical basis and practical guidance for the design and optimisation of future online courses, which can help to promote students' learning engagement in online courses and improve the effectiveness and quality of online learning.

Article Details

Section

Digital Learning and E-Learning

References

Adeyeye, B., Ojih, S. E., Bello, D., Adesina, E., Yartey, D., Ben-Enukora, C., & Adeyeye, Q. (2022). Online Learning Platforms and Covenant University Students’ Academic Performance in Practical Related Courses during COVID-19 Pandemic. Sustainability, 14(2), 878. https://doi.org/10.3390/su14020878

Al-Obaydi, L. H., Shakki, F., Tawafak, R. M., Pikhart, M., & Ugla, R. L. (2023). What I know, what I want to know, what I learned: Activating EFL college students' cognitive, behavioral, and emotional engagement through structured feedback in an online environment. Frontiers in Psychology, 13, 1083673-1083673. https://doi.org/10.3389/fpsyg.2022.1083673

Alraimi, K. M., Zo, H., & Ciganek, A. P. (2015). Understanding the moocs continuance: the role of openness and reputation. Computers & Education, 80, 28-38. https://doi.org/10.1016/j.compedu.2014.08.006

Busteed, S. (2025). Communication and the student experience in the time of covid-19: An autoethnography. Language Teaching Research : LTR, 29(2), 885-903. https://doi.org/10.1177/13621688211067001

Cabrejas, M. M., & Mendoza, R. O. (2023). College Students’ Engagement and Self-Regulated Learning Strategies: Its Influence to The Academic Performance in The Flexible Learning Modality. British Journal of Multidisciplinary and Advanced Studies, 4(3), 73-84. https://doi.org/10.37745/bjmas.2022.0193

Chan, S. L., Lin, C. C., Chau, P. H., Takemura, N., & Fung, J. T. C. (2021). Evaluating online learning engagement of nursing students. Nurse Education Today, 104, 104985. https://doi.org/10.1016/j.nedt.2021.104985

Coti, C., Loddo, J. V., & Viennet, E. (2015). Practical activities in network courses for MOOCs, SPOCs and eLearning with Marionnet. 2015 International Conference on Information Technology Based Higher Education and Training (ITHET). IEEE. https://doi.org/10.1109/ITHET.2015.7218043

Dao, P., & Sato, M. (2021). Exploring fluctuations in the relationship between learners’ positive emotional engagement and their interactional behaviours. Language Teaching Research, 25(6), 972-994. https://doi.org/10.1177/13621688211044238

Darabi, A., Arrastia, M. C., Nelson, D. W., Cornille, T., & Liang, X. (2011). Cognitive presence in asynchronous online learning: a comparison of four discussion strategies. Journal of Computer Assisted Learning, 27(3), 216-227. https://doi.org/10.1111/j.1365-2729.2010.00392.x

Delgado, C., & Wolf, L. (2017). Time on task: perceived and measured time in online courses for students and faculty. Journal of Nursing Education and Practice, 7(5), 27-32. https://doi.org/10.5430/jnep.v7n5p27

Deng, Q., Li, Y., & Zheng, L. (2017). Digital education reform for improving interaction between students and instructors. In X. Liu & X.-C. Zhang (Eds.), 14th Conference on Education and Training in Optics and Photonics: ETOP 2017 (p. 188). SPIE. https://doi.org/10.1117/12.2269871

Ding, Z., Liu, R. D., Ding, Y., Yang, X., & Yang, Y. (2025). Moderation is the key: taking too easy or too hard courses increases academic cyberloafing. Education and Information Technologies, 1-26. https://doi.org/10.1007/s10639-025-13546-0

El-Bishouty, M. M., Aldraiweesh, A., Alturki, U., Tortorella, R., & Kinshuk. (2019). Use of felder and silverman learning style model for online course design. Educational Technology Research and Development, 67(1), 161-177. https://doi.org/10.1007/s11423-018-9634-6

Evans, P., Vansteenkiste, M., Parker, P., Kingsford-Smith, A., & Zhou, S. (2024). Cognitive load theory and its relationships with motivation: A self-determination theory perspective. Educational Psychology Review, 36(1), 7. https://doi.org/10.1007/s10648-023-09841-2

Farrell, O., & Brunton, J. (2020). A balancing act: A window into online student engagement experiences.International Journal of Educational Technology in Higher Education, 17(1), 1–19. https://doi.org/10.1186/s41239-020-00199-x

Fewella, L. N. (2023). Impact of covid-19 on distance learning practical design courses. International Journal of Technology & Design Education, 33(5), 1703-1726. https://doi.org/10.1007/s10798-023-09806-0

Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: potential of the concept, state of the evidence. Review of Educational Research, 74(1), 59-109. https://doi.org/10.3102/00346543074001059

Fredricks, J. A., Filsecker, M., & Lawson, M. A. (2016). Student engagement, context, and adjustment: addressing definitional, measurement, and methodological issues. Learning & Instruction, 43, 1-4. https://doi.org/10.1016/j.learninstruc.2016.02.002

Goopio, J., & Cheung, C. (2021). The MOOC dropout phenomenon and retention strategies. Journal of Teaching in Travel & Tourism, 21(2), 177-197. https://doi.org/10.1080/15313220.2020.1809050

Gorsky, P., Caspi, A., Antonovsky, A., Blau, I., & Mansur, A. (2010). The relationship between academic discipline and dialogic behavior in open university course forums. International Review of Research in Open and Distributed Learning, 11(2), 49-72. https://doi.org/10.19173/irrodl.v11i2.820

Grau, V., Lorca, A., Araya, C., Urrutia, S., Ríos, D., Montagna, P., & Ibaceta, M. (2018). Socially shared regulation of learning and quality of talk: Age differences in collaborative group work in classroom contexts. New Directions for Child and Adolescent Development, 2018(162), 11-39. https://doi.org/10.1002/cad.20261

Greene, & Barbara, A. (2015). Measuring cognitive engagement with self-report scales: reflections from over 20 years of research. Educational Psychologist, 50(1), 14-30. https://doi.org/10.1080/00461520.2014.989230

Gunuc, S., & Kuzu, A. (2015). Student engagement scale: development, reliability and validity. Assessment & Evaluation in Higher Education, 40(4), 587-610. https://doi.org/10.1080/02602938.2014.938019

Hadwin, A. F., Järvelä, S., & Miller, M. (2011). Self-regulated, co-regulated, and socially shared regulation of learning. Handbook of self-regulation of learning and performance, 30, 65-84. https://doi.org/10.1007/s11191-010-9259-6

Harris, S. C., Zheng, L., & Kumar, V. (2014, December). Multi-dimensional sentiment classification in online learning environment. In 2014 IEEE Sixth International Conference on Technology for Education (pp. 172-175). IEEE. https://doi.org/10.1109/T4E.2014.50

Hew, K. F., Cheung, W. S., & Ng, C. S. L. (2010). Student contribution in asynchronous online discussion: a review of the research and empirical exploration. Instructional Science, 38(6), 571-606. https://doi.org/10.1007/s11251-008-9087-0

Hofer, S., Nistor, N., & Scheibenzuber, C. (2021). Online teaching and learning in higher education: lessons learned in crisis situations. Computers in Human Behavior, 121, 106789-106789. https://doi.org/10.1016/j.chb.2021.106789

Huang, C. Q., Han, Z. M., Li, M. X., Jong, M. S. Y., & Tsai, C. C. (2019). Investigating students' interaction patterns and dynamic learning sentiments in online discussions. Computers & Education, 140, 103589. https://doi.org/10.1016/j.compedu.2019.05.015

Jaggars, S. S., & Xu, D. (2016). How do online course design features influence student performance?. Computers & Education, 95, 270-284. https://doi.org/10.1016/j.compedu.2016.01.014

Janssen, J., & Kirschner, P. A. (2020). Applying collaborative cognitive load theory to computer-supported collaborative learning: Towards a research agenda. Educational Technology Research and Development, 68(2), 783-805. https://doi.org/10.1007/s11423-019-09729-5

Javed, Z. S., Nazeer, Z., & Umair, M. (2023). University Students’ Perception of MOOCs based on MOOC Instructional Design Elements. PJDOL, 9(1). https://doi.org/10.30971/pjdol.v9i1.1400

Jin, S. H., Im, K., Yoo, M., Roll, I., & Seo, K. (2023). Supporting students’ self-regulated learning in online learning using artificial intelligence applications. International Journal of Educational Technology in Higher Education, 20(1), 37. https://doi.org/10.1186/s41239-023-00406-5

Juan, S. (2021). Promoting engagement of nursing students in online learning: use of the student-generated question in a nursing leadership course. Nurse Education Today, 97(1), 104710. https://doi.org/10.1016/j.nedt.2020.104710

Konstantinidou, A., & Nisiforou, E. (2022). Assuring the quality of online learning in higher education: Adaptations in design and implementation. Australasian Journal of Educational Technology, 38(4), 127-142. https://doi.org/10.14742/ajet.7910

Kortjass, M., & Mkhize-Mthembu, N. (2023). Reflecting on teaching in the higher education context during the covid-19 era: a collaborative self-study project. Educational Research for Social Change, 12(2). https://doi.org/10.17159/2221-4070/2023/v12i2a4

Kuh, G. D. (2009). The national survey of student engagement: conceptual and empirical foundations. New Directions for Institutional Research, 2009(141), 5-20. https://doi.org/10.1002/ir.283

Lamon, S., Knowles, O., Hendy, A., Story, I., & Currey, J. (2020). Active learning to improve student learning experiences in an online postgraduate course. Frontiers in Education (Lausanne), 5, 598560. https://doi.org/10.3389/feduc.2020.598560

Lang, Y., Xie, K., Gong, S., Wang, Y., & Cao, Y. (2022). The impact of emotional feedback and elaborated feedback of a pedagogical agent on multimedia learning. Frontiers in Psychology, 13, 810194. https://doi.org/10.3389/fpsyg.2022.810194

Li, Q., & Baker, R. (2018). The different relationships between engagement and outcomes across participant subgroups in massive open online courses. Computers and Education, 127, 41-65. https://doi.org/10.1016/j.compedu.2018.08.005

Lin, CC., & Tsai, CC. (2012). Participatory learning through behavioral and cognitive engagements in an online collective information searching activity. Computer Supported Learning, 7, 543–566. https://doi.org/10.1007/s11412-012-9160-1

Liu, F. H., & Yi, X. T. (2021). Research on Construction and Application of Analysis Model of Online Learning Engagement. E-education Research, 42, 69-75. https://doi.org/10.13811/j.cnki.eer.2021.09.010

Ma, J. N., Mou, T. Y., & Cheng, L. (2023). A Study on Implementation of Sustainable Development Goals in General Education Courses: A Textual Analysis of Undergraduate General Education Courses in 20 “Double First-Class” Construction Universities. China Higher Education Research, 39(01): 101-108. https://doi.org/10.16298/j.cnki.1004-3667.2023.01.16

Manwaring, K. C., Larsen, R., Graham, C. R., Brigham, C. H., & Halverson, L. R. (2017). Investigating student engagement in blended learning settings using experience sampling and structural equation modeling. The Internet and Higher Education, 35, 21-33. https://doi.org/10.1016/j.iheduc.2017.06.002

Margaryan, A., Bianco, M., & Littlejohn, A. (2015). Instructional quality of massive open online courses (moocs). Computers & Education, 80, 77-83. https://doi.org/10.1016/j.compedu.2014.08.005

Martin, F., & Bolliger, D. U. (2023). Designing online learning in higher education. Handbook of open, distance and digital education, 1217-1236. https://doi.org/10.1007/978-981-19-2080-6_72

Men, Q., Gimbert, B., & Cristol, D. (2023). The Effect of Self-Regulated Learning in Online Professional Training. International Journal of Mobile and Blended Learning (IJMBL), 15(2), 1-17. https://doi.org/10.4018/IJMBL.318225

Michalsky, T., & Cohen, A. (2021). Prompting socially shared regulation of learning and creativity in solving STEM problems. Frontiers in psychology, 12, 722535. https://doi.org/10.3389/fpsyg.2021.722535

Monkaresi, H., Bosch, N., Calvo, R. A., & D'Mello, S. K. (2017). Automated detection of engagement using video-based estimation of facial expressions and heart rate. IEEE Transactions on Affective Computing, 8(1), 15-28. https://doi.org/10.1109/TAFFC.2016.2515084

Monzo, C., Germán Cobo, José Antonio Morán, Eugènia Santamaría, & David García-Solórzano. (2021). Remote laboratory for online engineering education: the rlab-uoc-fpga case study. Electronics, 10(9), 1072. https://doi.org/10.3390/electronics10091072

Müller, A. M., Goh, C., Lim, L. Z., & Gao, X. (2021). COVID-19 Emergency eLearning and Beyond: Experiences and Perspectives of University Educators. Education Sciences, 11(1), 19. https://doi.org/10.3390/educsci11010019

Paulsen, J., & McCormick, A. C. (2020). Reassessing disparities in online learner student engagement in highereducation. Educational Researcher, 49(1), 20–29. https://doi.org/10.3102/0013189X19898690

Pintrich, P. R. R., Smith, D., Garcia, T., & McKeachie, W. (1991). A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ). Ann Arbor. Michigan, 48109(August 2016), 1259. https://doi.org/ED338122

Prada Arias, A. Y., Trujillo Rodríguez, M. A., & Herrera Mosquera, L. (2022). Enhancing Language Learning Engagement through Critical Literacy Practices. Lenguaje, 50(1), 37-65. https://doi.org/10.25100/lenguaje.v50i1.11085

Radhika, S., Sharath, S., & Jane, W. (2008). Using self-regulatory learning to enhance e-learning-based information technology training. Information Systems Research, 19(1), 26-47. https://doi.org/10.1287/isre.1070.0141

Ravindran, B., Greene, B. A., & Debacker, T. K. (2005). Predicting preservice teachers' cognitive engagement with goals and epistemological beliefs. Journal of Educational Research, 98(4), 222-233. https://doi.org/10.3200/JOER.98.4.222-233

Redmond, P., Abawi, L. A., Brown, A., Henderson, R., & Heffernan, A. (2018). An online engagement framework for higher education. Online learning, 22(1), 183-204. https://doi.org/10.24059/olj.v22i1.1175

Renée S. Jansen, Leeuwen, A. V., Janssen, J., Conijn, R., & Kester, L. (2019). Supporting learners' self-regulated learning in massive open online courses. Computers & Education, 146, 103771. https://doi.org/10.1016/j.compedu.2019.103771

Şahin, M. (2021). A comparative analysis of dropout prediction in massive open online courses. Arabian Journal for Science and Engineering (2011), 46(2), 1845-1861. https://doi.org/10.1007/s13369-020-05127-9

Salas-Pilco, S. Z., Yang, Y., & Zhang, Z. (2022). Student engagement in online learning in latin american higher education during the covid-19 pandemic: a systematic review. British journal of educational technology : journal of the Council for Educational Technology, 53(3), 593-619. https://doi.org/10.1111/bjet.13190

Sani, A. R., & Rad, R. K. (2015). The structural model of relationship between informational style, achievement goals and cognitive engagement. European Online Journal of Natural and Social Sciences, 4(1), 219. https://european-science.com/eojnss/article/view/2659

Saqr, M., & Sonsoles López-Pernas. (2021). The longitudinal trajectories of online engagement over a full program. Computers & Education, 175(2), 104325. https://doi.org/10.1016/j.compedu.2021.104325

Şeyh, F., Şen-Akbulut, M., & Umutlu, D. (2023). The impact of role assignment on social presence in online discussions: A mixed-method study. The Internet and Higher Education, 56, 100892. https://doi.org/10.1016/j.iheduc.2022.100892

Skinner, E. A., Kindermann, T. A., & Furrer, C. J. (2009). A motivational perspective on engagement and disaffection conceptualization and assessment of children's behavioral and emotional participation in academic activities in the classroom. Educational & Psychological Measurement, 69(3), 493-525. https://doi.org/10.1177/0013164408323233

Sulla, F., Monacis, D., & Limone, P. (2023). A systematic review of the role of teachers’ support in promoting socially shared regulatory strategies for learning. Frontiers in Psychology, 14, 1208012. https://doi.org/10.3389/fpsyg.2023.1208012

Tas, Y. (2016). The contribution of perceived classroom learning environment and motivation to student engagement in science. European Journal of Psychology of Education, 31, 557-577. https://doi.org/10.1007/s10212-016-0303-z

Trust, T., & Pektas, E. (2018). Using the addie model and universal design for learning principles to develop an open online course for teacher professional development. Journal of Digital Learning in Teacher Education, 34(4), 219-233. https://doi.org/10.1080/21532974.2018.1494521

Tualaulelei, E., Burke, K. M., Fanshawe, M., & Cameron, C. (2021). Mapping pedagogical touchpoints: exploring online student engagement and course design. Active Learning in Higher Education, 23, 189-203. https://doi.org/10.1177/1469787421990847

Turk, M., Turk, S. T., Muftuoglu, A. C., Karakaya, O., & Karakaya, K. (2024). Students' Expectations and Experiences about Engagement Strategies in Online Courses: A Mixed Methods Study. Online Learning, 28(2), n2. https://doi.org/10.24059/olj.v28i2.3937

Vartiainen, H., Vuojrvi, H., Saramki, K., Eriksson, M., Ratinen, I., & Torssonen, P., et al. (2022). Cross‐boundary collaboration and knowledge creation in an online higher education course. British Journal of Educational Technology, 53(5), 1304-1320. https://doi.org/10.1111/bjet.13186

Vergara-Castañeda, A., Chávez-Miyauchi, T. E., Benítez-Rico, A., & Ogando-Justo, A. B. (2021). Implementing Project-Based Learning as an Effective Alternative Approach for Chemistry Practical Courses Online. Journal of Chemical Education, 98(11), 3502-3508. https://doi.org/10.1021/acs.jchemed.1c00379

Wang, Y., Zuo, M., He, X., & Wang, Z. (2025). Exploring Students Online Learning Behavioral Engagement in University: Factors, Academic Performance and Their Relationship. Behavioral Sciences, 15(1), 78. https://doi.org/10.3390/bs15010078

Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: the panas scales. J Pers Soc Psychol, 54(6), 1063-1070. https://doi.org/10.1037/0022-3514.54.6.1063

Xia, B. S. (2015). Benefit and cost analysis of massive open online courses: pedagogical implications on higher education. International Journal of Cyber Behavior Psychology & Learning, 5(3), 47-55. https://doi.org/10.4018/IJCBPL.2015070104

Xu, W., & Lou, Y. F. (2024). Changes in the socially shared regulation, academic emotions, and product performance in venue-based collaborative learning. Active Learning in Higher Education, 25(3), 517-535. https://doi.org/10.1177/14697874231167331

Ye, J. H., Lee, Y. S., & He, Z. (2022). The relationship among expectancy belief, course satisfaction, learning effectiveness, and continuance intention in online courses of vocational-technical teachers college students. Frontiers in Psychology, 13, 904319. https://doi.org/10.3389/fpsyg.2022.904319

Ye, J. M., & Zhou, J. (2022). Exploring the relationship between learning sentiments and cognitive processing in online collaborative learning: A network analytic approach. The Internet and Higher Education, 55, 100875. https://doi.org/10.1016/j.iheduc.2022.100875

Yildirim, D., & Usluel, Y. (2022). Interrelated analysis of interaction, sequential patterns and academic achievement in online learning. Australasian Journal of Educational Technology, 38(2), 181-200. https://doi.org/10.14742/ajet.7360

Yin, R., & Xu, H. Y. (2017). Construction of online learning engagement structural model: An empirical study based on Structural Equation Model. Open Education Research, 23(4), 101-111. https://doi.org/10.13966/j.cnki.kfjyyj.2017.04.010

You, W. (2022). Research on the relationship between learning engagement and learning completion of online learning students. International Journal of Emerging Technologies in Learning (iJET), 17(1), 102-117. https://doi.org/10.3991/ijet.v17i01.28545

Zaha, A. (2022). Analysis of the Interrelatedness of Self-Regulation, Learners‟ Engagement, and Self-Perceived Development in a Synchronous Online EFL Reading Course. World, 12(8). https://doi.org/10.5430/wjel.v12n8p39

Zheng, B., Lin, C. H., & Kwon, J. B. (2020). The impact of learner-, instructor-, and course-level factors on online learning. Computers & Education, 150, 103851. https://doi.org/10.1016/j.compedu.2020.103851

Zhou, Y., & Han, Y. F. (2018). Research on learners’ learning engagement in blended-learning activities. e-Education Research, 39, 99-105. https://doi.org/10.13811/j.cnki.eer.2018.11.013

Zhu, X., Gong, Q., Wang, Q., He, Y., Sun, Z., & Liu, F. (2023). Analysis of Students’ Online Learning Engagement during the COVID-19 Pandemic: A Case Study of a SPOC-Based Geography Education Undergraduate Course. Sustainability, 15(5), 4544. https://doi.org/10.3390/su15054544

Similar Articles

You may also start an advanced similarity search for this article.