UNBOXING UNDERSTANDING: SELF-EXPLANATION PROMPTING AS A KEY TO UNLOCKING DEEP LEARNING IN CALCULUS
Sufyani Marethi , Faculty of Education, University of Sultan Ageng Tirtayasa, Indonesia Hadi Firdos Prabawanto , Mathematical Education and Natural Science Indonesia University of Education, IndonesiaAbstract
Deep learning in calculus often poses challenges for students, requiring a nuanced approach to foster comprehension. This study explores the efficacy of self-explanation prompting as a key strategy for enhancing deep learning in calculus. The research investigates the impact of guided self-explanation prompts on students' understanding and retention of calculus concepts. By employing a carefully designed intervention, we aim to uncover the mechanisms through which self-explanation facilitates meaningful learning in calculus. The results highlight the potential of self-explanation as a powerful tool in the educational toolkit, shedding light on how it can unlock a deeper understanding of calculus concepts and improve overall learning outcomes.
Keywords
Deep learning, Calculus education, Self-explanation prompting
References
Baddeley, A. (1992). Working Memory. Science, 255, 556 – 559.
Baddeley, A. (2003). Worki ng memory: looking back and looking forward. Nature Reviews. Neurosci ence, 4(10), 829–39.
Baddeley, A. (2010, March 23). Working memory. Current Biology, 20(4), 136–140.
Baddeley, A. (2012). Working memory: theories, models, and controversies. Annual Review of Psychology, 63, 1–29.
Berthold, K., Röder, H., Knörzer, D., Kessler, W., & Renkl, A. (2011). The double-edged effects of explanation prompts. Computers in Human Behavior, 27(1), 69–75.
Bokosmaty, S., Sweller, J., & Kalyuga, S. (2015). Learning Geometry Problem Solving by Studying Worked Examples: Effects of Learner Guidance and Expertise. American Educational Research Journal, 52(2), 307–333.
Booth, J. L., Lange, K. E., Koedinger, K. R., & Newton, K. J. (2013). Using example problems to improve student learning in algebra: Differentiating between correct and incorrect examples. Learning and Instruction,25, 24–34.
Clark, R. C., Nguyen, F., & Sweller, J. (2011). Efficiency in Learning; Evidence-Based Guidlines to Manage Cognitive Load. New York: John Wileyand Son Ltd.
Debue, N., & Leemput, C. van de. (2014). What does germane load mean? An empirical contribution to the cognitive load theory. Frontiers in Psychology, 5(October), 1–12.
Fraenkel, J. R., Wallen, N. E., &Hyun, H. H. (2012). How to Design and Evaluate Research in Education(8th ed.). New York: McGraw-Hill
Article Statistics
Copyright License
Copyright (c) 2024 Sufyani Marethi, Hadi Firdos Prabawanto

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors retain the copyright of their manuscripts, and all Open Access articles are disseminated under the terms of the Creative Commons Attribution License 4.0 (CC-BY), which licenses unrestricted use, distribution, and reproduction in any medium, provided that the original work is appropriately cited. The use of general descriptive names, trade names, trademarks, and so forth in this publication, even if not specifically identified, does not imply that these names are not protected by the relevant laws and regulations.