Group Studying Versus Personalized Approach : A Comparative Analysis of Learning Effectiveness and Student Satisfaction
Keywords:
Group Studying, Personalised Approach, Comparative Analysis, Learning Effectiveness, Student SatisfactionAbstract
The present study delves into the ongoing debate of Group Studying versus Personalized Learning approaches in educational settings, aiming to compare their impact on learning effectiveness and student satisfaction. An empirical investigation was conducted involving undergraduate students from diverse academic disciplines. The research design included a mixed-method approach, incorporating quantitative data through pre- and post-tests, as well as qualitative insights gathered from interviews and surveys. The study found that both approaches had unique strengths and limitations, with personalized learning demonstrating higher effectiveness in certain aspects. The findings offer valuable insights for educators and policymakers to make informed decisions on optimizing learning strategies to meet individual student needs.
References
- Z. Jiang Abel, M., & Bäuml, K. H. T. (2020). Would you like to learn more? Retrieval practice plus feedback can increase motivation to keep on studying. Cognition, 201, 104316.
- Aiken, E. G., Thomas, G. S., & Shennum, W. A. (1975). Memory for a lecture: Effects of notes, lecture rate, and informational density. Journal of Educational Psychology, 67(3), 439.
- Barnett, S. M., & Ceci, S. J. (2002). When and where do we apply what we learn? A taxonomy for far transfer. Psychological Bulletin, 128, 612–637. https://doi.org/10.1037/0033-2909.128.4.612
- Bergdahl, N., Nouri, J., & Fors, U. (2020a). Disengagement, engagement and digital skills in technology-enhanced learning. Education and Information Technologies, 25(2), 957–983.
- Bergdahl, N., Nouri, J., Fors, U., & Knutsson, O. (2020b). Engagement, disengagement and performance when learning with technologies in upper secondary school. Computers & Education, 149, 103783.
- Chen, C. M., & Li, Y. L. (2010). Personalised context-aware ubiquitous learning system for supporting effective English vocabulary learning. Interactive Learning Environments, 18(4), 341–364.
- Chen, X., Zou, D., Xie, H., & Cheng, G. (2021). Twenty years of personalized language learning. Educational Technology & Society, 24(1), 205–222.
- Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Earlbaum Associates.
- Cortina, J. M. (1993). What is coefficient alpha? An examination of theory and applications. Journal of Applied Psychology, 78(1), 98.
- Du, M. C. (2004). Personalized annotation management for web based learning service (Unpublished master thesis). National Central University, Chungli, Taiwan.
- Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students’ learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14(1), 4–58.
- Finn, J. D., & Zimmer, K. S. (2012). Student engagement: What is it? Why does it matter? Handbook of research on student engagement (pp. 97–131). Springer.
- Fredricks, J. A., Reschly, A. L., & Christenson, S. L. (Eds.). (2019). Handbook of student engagement interventions: working with disengaged students. Academic Press.
- Kuder, G. F., & Richardson, M. W. (1937). The theory of the estimation of test reliability. Psychometrika, 2(3), 151–160.
- Lian, A. P., & Sangarun, P. (2017). Precision Language Education: A Glimpse Into a Possible Future. GEMA Online Journal of Language Studies, 17(4).
- Lin, C. F., Yeh, Y. C., Hung, Y. H., & Chang, R. I. (2013). Data mining for providing a personalized learning path in creativity: An application of decision trees. Computers & Education, 68, 199–210.
- Lindsey, R. V., Shroyer, J. D., Pashler, H., & Mozer, M. C. (2014). Improving students’ long-term knowledge retention through personalized review. Psychological Science, 25(3), 639–647.
- Ma, J., Cheng, J., & Han, X. (2017, December). Initial development process of a student engagement scale in blended learning environment. In 2017 International Conference of Educational Innovation through Technology (EITT) (pp. 234–237). Osaka, Japan: IEEE. https://doi.org/10.1109/EITT.2017.63.
- McDaniel, M. A., Thomas, R. C., Agarwal, P. K., McDermott, K. B., & Roediger, H. L. (2013). Quizzing in middle-school science: Successful transfer performance on classroom exams. Applied Cognitive Psychology, 27, 360–372. https://doi.org/10.1002/acp.2914
- Mercer, S. (2019). Language learner engagement: Setting the scene. Second handbook of English language teaching, 643–660.
- Murphy, M., Redding, S., & Twyman, J. (Eds.). (2016). Handbook on personalized learning for states, districts, and schools. IAP.
- Namaziandost, E., & Çakmak, F. (2020). An account of EFL learners’ self-efficacy and gender in the Flipped Classroom Model. Education and Information Technologies, 25(5), 4041–4055.
Downloads
Published
Issue
Section
License
Copyright (c) IJSRSET

This work is licensed under a Creative Commons Attribution 4.0 International License.