Enhancing Online Learning: Integrating Social Interaction Dimension into The Felder Silverman Learning Style Model
https://doi.org/10.26594/register.v12i2.3922
Keywords:
Felder Silverman Learning Styles Model, Online Learning, Learning Performance, Social InteractionAbstract
This study aims to investigate the impact of enhancing Felder Silverman Learning Style Model (FSLSM) by integrating social interaction on student learning per-formance. A mixed methods was performed to analyze the usage to 400 data col-lected in Indonesia. The findings show that social interaction play significant roles on the enhancing FSLSM. Interestingly, the social interaction dimension that are not considered in the FSLSM, does act as the influencer. This study high-lights the combination of FSLSM and social interaction dimension can create a comprehensive description of students learning styles which has an impact on student’s learning performance which increased by 4.5%. The study suggested that online learning platform should have features that can retain comprehensive and personalized learning experiences, which may create a better online learning platform and positively affect users’ learning performance.
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[1] E. S. Alamoudi and N. S. Alghamdi, “Sentiment classification and aspect-based sentiment analysis on Yelp reviews using deep learning and word embeddings,” Journal of Decision Systems, vol. 30, nos. 2–3, pp. 259–281, 2021, doi: 10.1080/12460125.2020.1864106.
[2] J. Valverde-Berrocoso, M. C. Garrido-Arroyo, C. Burgos-Videla, and M. B. Morales-Cevallos, “Trends in educational research about e-learning: A systematic literature review (2009–2018),” Sustainability, vol. 12, no. 12, Art. no. 5153, 2020, doi: 10.3390/su12125153.
[3] D. Turnbull, R. Chugh, and J. Luck, “Transitioning to e-learning during the COVID-19 pandemic: How have higher education institutions responded to the challenge?” Education and Information Technologies, vol. 26, no. 5, pp. 6401–6419, 2021, doi: 10.1007/s10639-021-10633-w.
[4] M. F. Contrino, M. Reyes-Millán, P. Vázquez-Villegas, and J. Membrillo-Hernández, “Using an adaptive learning tool to improve student performance and satisfaction in online and face-to-face education for a more personalized approach,” Smart Learning Environments, vol. 11, Art. no. 6, 2024, doi: 10.1186/s40561-024-00292-y.
[5] T. Kabudi, I. Pappas, and D. H. Olsen, “AI-enabled adaptive learning systems: A systematic mapping of the literature,” Computers and Education: Artificial Intelligence, vol. 2, Art. no. 100017, 2021, doi: 10.1016/j.caeai.2021.100017.
[6] H. A. El-Sabagh, “Adaptive e-learning environment based on learning styles and its impact on development students’ engagement,” International Journal of Educational Technology in Higher Education, vol. 18, Art. no. 53, 2021, doi: 10.1186/s41239-021-00289-4.
[7] I. Gligorea, M. Cioca, R. Oancea, A.-T. Gorski, H. Gorski, and P. Tudorache, “Adaptive learning using artificial intelligence in e-learning: A literature review,” Education Sciences, vol. 13, no. 12, Art. no. 1216, 2023, doi: 10.3390/educsci13121216.
[8] J. R. Hernández-Herrera, J. Ortiz-Bejar, and J. Ortiz-Bejar, “Adaptive and personalized learning in higher education: An artificial intelligence-based approach,” Education Sciences, vol. 16, no. 1, Art. no. 109, 2026, doi: 10.3390/educsci16010109.
[9] N. W. Rahayu, R. Ferdiana, and S. S. Kusumawardani, “A systematic review of ontology use in e-learning recommender systems,” Computers and Education: Artificial Intelligence, vol. 3, Art. no. 100047, 2022, doi: 10.1016/j.caeai.2022.100047.
[10] J. Cooper, S. Olsher, and M. Yerushalmy, “Didactic metadata informing teachers’ selection of learning resources: Boundary crossing in professional development,” Journal of Mathematics Teacher Education, vol. 23, no. 4, pp. 363–384, 2020, doi: 10.1007/s10857-019-09428-1.
[11] S. Tahir, Y. Hafeez, M. A. Abbas, A. Nawaz, and B. Hamid, “Smart learning objects retrieval for e-learning with contextual recommendation based on collaborative filtering,” Education and Information Technologies, vol. 27, no. 6, pp. 8631–8668, 2022, doi: 10.1007/s10639-022-10966-0.
[12] T.-T. Goh, “Learning management system log analytics: The role of persistence and consistency of engagement behaviour on academic success,” Journal of Computers in Education, vol. 13, no. 1, pp. 283–306, 2026, doi: 10.1007/s40692-025-00358-x.
[13] K. Najem, Y. Zaoui Seghroucheni, and S. Ziti, “Comparative analysis of learning style models for e-learning: Validating the Felder-Silverman framework using behavioral data,” International Journal of Interactive Mobile Technologies, vol. 19, no. 24, pp. 120–136, 2025, doi: 10.3991/ijim.v19i24.57421.
[14] F. Rasheed and A. Wahid, “Learning style detection in e-learning systems using machine learning techniques,” Expert Systems with Applications, vol. 174, Art. no. 114774, 2021, doi: 10.1016/j.eswa.2021.114774.
[15] B. A. Muhammad, C. Qi, Z. Wu, and H. K. Ahmad, “GRL-LS: A learning style detection in online education using graph representation learning,” Expert Systems with Applications, vol. 201, Art. no. 117138, 2022, doi: 10.1016/j.eswa.2022.117138.
[16] C. Troussas, A. Krouska, C. Sgouropoulou, and I. Voyiatzis, “Ensemble learning using fuzzy weights to improve learning style identification for adapted instructional routines,” Entropy, vol. 22, no. 7, Art. no. 735, 2020, doi: 10.3390/e22070735.
[17] H. Zhang et al., “A learning style classification approach based on deep belief network for large-scale online education,” Journal of Cloud Computing, vol. 9, no. 1, 2020, doi: 10.1186/s13677-020-00165-y.
[18] B. Oyarzun and F. Martin, “A systematic review of research on online learner collaboration from 2012–2021: Collaboration technologies, design, facilitation, and outcomes,” Online Learning, vol. 27, no. 1, pp. 71–106, 2023, doi: 10.24059/olj.v27i1.3407.
[19] A. Bach and F. Thiel, “Collaborative online learning in higher education—Quality of digital interaction and associations with individual and group-related factors,” Frontiers in Education, vol. 9, Art. no. 1356271, 2024, doi: 10.3389/feduc.2024.1356271.
[20] J. Hattie and T. O’Leary, “Learning styles, preferences, or strategies? An explanation for the resurgence of styles across many meta-analyses,” Educational Psychology Review, vol. 37, Art. no. 31, 2025, doi: 10.1007/s10648-025-10002-w.
[21] A. M. Aboregela, “Learning style preference and the academic achievements of medical students in an integrated curriculum,” Journal of Medicine and Life, vol. 16, no. 12, pp. 1802–1807, 2023, doi: 10.25122/jml-2023-0366.
[22] J. Miao and L. Ma, “Students’ online interaction, self-regulation, and learning engagement in higher education: The importance of social presence to online learning,” Frontiers in Psychology, vol. 13, Art. no. 815220, 2022, doi: 10.3389/fpsyg.2022.815220.
[23] Z. Zhou and Y. Zhang, “Intrinsic and extrinsic motivation in distance education: A self-determination perspective,” American Journal of Distance Education, vol. 38, no. 1, pp. 51–64, 2024, doi: 10.1080/08923647.2023.2177032.
[24] R. M. Ryan and E. L. Deci, “Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions,” Contemporary Educational Psychology, vol. 61, Art. no. 101860, 2020, doi: 10.1016/j.cedpsych.2020.101860.
[25] J. C. Moneva, J. S. Arnado, and I. N. Buot, “Students’ learning styles and self-motivation,” International Journal of Social Science Research, vol. 8, no. 2, pp. 16–29, 2020, doi: 10.5296/ijssr.v8i2.16733.
[26] M. Raleiras, A. H. Nabizadeh, and F. A. Costa, “Automatic learning styles prediction: A survey of the state of the art (2006–2021),” Journal of Computers in Education, vol. 9, no. 4, pp. 587–679, 2022, doi: 10.1007/s40692-021-00215-7.
[27] A. B. Rashid, R. R. Raja Ikram, Y. Thamilarasan, L. Salahuddin, N. F. A. Yusof, and Z. B. Rashid, “A student learning style auto-detection model in a learning management system,” Engineering, Technology & Applied Science Research, vol. 13, no. 3, pp. 11000–11005, 2023, doi: 10.48084/etasr.5751.
[28] S. Bouallegue, A. Omri, and S. Al-Naemi, “Machine learning approaches for early student performance prediction in programming education,” Information, vol. 17, no. 1, Art. no. 60, 2026, doi: 10.3390/info17010060.
[29] N. A. Ahmad, A. A. Mayouf, N. F. Elias, and H. Mohamed, “Learning management system instrument development based on Aiken’s V technique,” International Journal of Evaluation and Research in Education, vol. 13, no. 5, p. 3211, 2024, doi: 10.11591/ijere.v13i5.28925.
[30] J. Hair and A. Alamer, “Partial least squares structural equation modeling (PLS-SEM) in second language and education research: Guidelines using an applied example,” Research Methods in Applied Linguistics, vol. 1, no. 3, Art. no. 100027, 2022, doi: 10.1016/j.rmal.2022.100027.
[31] S. Demir and M. Uşak, “Analyzing the implementation of PLS-SEM in educational technology research: A review of the past 10 years,” SAGE Open, vol. 15, no. 2, Art. no. 21582440251345950, 2025, doi: 10.1177/21582440251345950.
[32] S. Maloney et al., “Using LMS log data to explore student engagement with coursework videos,” Online Learning, vol. 26, no. 4, pp. 399–423, 2022, doi: 10.24059/olj.v26i4.2998.
[33] M. Riestra-González, M. del P. Paule-Ruíz, and F. Ortin, “Massive LMS log data analysis for the early prediction of course-agnostic student performance,” Computers & Education, vol. 163, Art. no. 104108, 2021, doi: 10.1016/j.compedu.2020.104108.
[34] H. Y. Ayyoub and O. S. Al-Kadi, “Learning style identification using semi-supervised self-taught labeling,” IEEE Transactions on Learning Technologies, vol. 17, pp. 1093–1106, 2024, doi: 10.1109/TLT.2024.3358864.
[35] F. Martin, D. U. Bolliger, and C. Flowers, “Design matters: Development and validation of the Online Course Design Elements (OCDE) instrument,” International Review of Research in Open and Distributed Learning, vol. 22, no. 2, pp. 46–71, 2021, doi: 10.19173/irrodl.v22i2.5187.
[36] C. Na, S. Jeong, J. Clarke-Midura, and Y. Shin, “Linking self-regulated learning to community of inquiry in online undergraduate courses: A person-centered approach,” Educational Technology Research and Development, vol. 72, no. 6, pp. 2895–2920, 2024, doi: 10.1007/s11423-024-10380-y.
[37] D. Teodorescu, K. A. Aivaz, and A. Amalfi, “Factors affecting motivation in online courses during the COVID-19 pandemic: The experiences of students at a Romanian public university,” European Journal of Higher Education, vol. 12, no. 3, pp. 332–349, 2022, doi: 10.1080/21568235.2021.1972024.
[38] L. S. Chikileva, A. A. Chistyakov, M. V. Busygina, A. I. Prokopyev, E. V. Grib, and D. N. Tsvetkov, “A review of empirical studies examining the effects of e-learning on university students’ academic achievement,” Contemporary Educational Technology, vol. 15, no. 4, Art. no. ep449, 2023, doi: 10.30935/cedtech/13418.
[39] A. Lestari, A. Lawi, S. A. Thamrin, and N. Hidayat, “Automated detection of learning styles using online activities and model indicators,” International Journal of Advanced Computer Science and Applications, vol. 15, no. 6, pp. 594–604, 2024, doi: 10.14569/IJACSA.2024.0150661.
[40] G. W. Cheung, H. D. Cooper-Thomas, R. S. Lau, and L. C. Wang, “Reporting reliability, convergent and discriminant validity with structural equation modeling: A review and best-practice recommendations,” Asia Pacific Journal of Management, vol. 41, pp. 745–783, 2024, doi: 10.1007/s10490-023-09871-y.
[41] B. Yin and C. H. Yuan, “Precision teaching and learning performance in a blended learning environment,” Frontiers in Psychology, vol. 12, Art. no. 631125, 2021, doi: 10.3389/fpsyg.2021.631125.
[42] H. Ulum, “The effects of online education on academic success: A meta-analysis study,” Education and Information Technologies, vol. 27, no. 1, pp. 429–450, 2022, doi: 10.1007/s10639-021-10740-8.
[43] F. Afzal and L. Crawford, “Student’s perception of engagement in online project management education and its impact on performance: The mediating role of self-motivation,” Project Leadership and Society, vol. 3, Art. no. 100057, 2022, doi: 10.1016/j.plas.2022.100057.
[44] A. Rof, A. Bikfalvi, and P. Marques, “Exploring learner satisfaction and the effectiveness of microlearning in higher education,” The Internet and Higher Education, vol. 62, Art. no. 100952, 2024, doi: 10.1016/j.iheduc.2024.100952.
[45] H. C. Wei and C. Chou, “Online learning performance and satisfaction: Do perceptions and readiness matter?” Distance Education, vol. 41, no. 1, pp. 48–69, 2020, doi: 10.1080/01587919.2020.1724768.
[46] F. Martin and J. Borup, “Online learner engagement: Conceptual definitions, research themes, and supportive practices,” Educational Psychologist, vol. 57, no. 3, pp. 162–177, 2022, doi: 10.1080/00461520.2022.2089147.
[47] P. M. L. Ng, J. K. Y. Chan, and K. K. Lit, “Student learning performance in online collaborative learning,” Education and Information Technologies, vol. 27, no. 6, pp. 8129–8145, 2022, doi: 10.1007/s10639-022-10923-x.
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