The Effectiveness of the Deep Learning Learning Model in Enhancing Students' Conceptual Understanding and Mathematics Learning Retention during the Implementation of the Merdeka Curriculum at SMP Negeri 1 Plampang
DOI:
https://doi.org/10.58258/p3f0zz51Abstract
Mathematics learning at the junior high school level still faces challenges related to students’ low conceptual understanding and learning retention, including at State Junior High School 1 Plampang. Students tend to memorize formulas without deeply understanding the underlying concepts, causing the knowledge they acquire to be easily forgotten. This condition requires the implementation of meaningful and student-centered learning models, such as deep learning. Therefore, this study aims to analyze the effectiveness of the deep learning model in improving students’ conceptual understanding and learning retention in mathematics, as well as to compare its outcomes with those of conventional learning at State Junior High School 1 Plampang. This study employed a quantitative approach using a quasi-experimental method with a Nonequivalent Control Group Design. The research sample consisted of 49 eighth-grade students divided into two groups: Class VIII-A as the experimental group with 25 students and Class VIII-B as the control group with 24 students. Data were collected through classroom observations, conceptual understanding tests, and learning retention tests. Data analysis was conducted using descriptive and inferential statistics, including the Shapiro–Wilk normality test, Levene’s homogeneity test, N-Gain analysis, and the Independent Sample ttest. The results showed that the average posttest score of the experimental group was 84.16, which was higher than that of the control group at 73.08. The average retention test score of the experimental group was 81.48, while the control group obtained 68.25. The N-Gain analysis indicated that the improvement in students’ conceptual understanding in the experimental group was categorized as high (0.71), whereas the control group was categorized as moderate (0.38). The hypothesis testing results revealed a significance value of 0.001 < 0.05 for conceptual understanding, learning retention, and differences in learning outcomes, indicating that the alternative hypotheses were accepted. Based on the findings, it can be concluded that the deep learning model is effective in improving students’ conceptual understanding and mathematics learning retention. Furthermore, there are significant differences in learning outcomes between students who learn through the deep learning model and those who receive conventional instruction. Therefore, the deep learning model can be considered an innovative learning alternative that supports the implementation of the Merdeka Curriculum in mathematics education.References
Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes. In K. W. Spence & J. T. Spence (Eds.), The psychology of learning and motivation: Advances in research and theory (Vol. 2, pp. 89–195). New York, NY: Academic Press.
Creswell, J. W. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Thousand Oaks, CA: SAGE Publications.
Deterding, S., Dixon, D., Khaled, R., & Nacke, L. (2011). From game design elements to gamefulness: Defining “gamification.” In Proceedings of the 15th International Academic MindTrek Conference: Envisioning Future Media Environments (pp. 9–15). New York, NY: Association for Computing Machinery.
Gee, J. P. (2013). The anti-education era: Creating smarter students through digital learning. New York, NY: Palgrave Macmillan.
Hake, R. R. (1999). Analyzing change/gain scores. Bloomington, IN: Indiana University Physics Department.
Hamari, J., Koivisto, J., & Sarsa, H. (2014). Does gamification work? A literature review of empirical studies on gamification. In Proceedings of the 47th Hawaii International Conference on System Sciences (pp. 3025–3034). Los Alamitos, CA: IEEE Computer Society.
Hasratuddin. (2023). Mengapa harus belajar matematika?. Medan, Indonesia: Perdana Publishing.
Johnson, L., & Adams, S. (2011). Challenge-based learning: The report from the implementation project. Austin, TX: The New Media Consortium.
Kapp, K. M. (2012). The gamification of learning and instruction: Game-based methods and strategies for training and education. San Francisco, CA: Pfeiffer.
Keller, J. M. (2010). Motivational design for learning and performance: The ARCS model approach. New York, NY: Springer.
National Council of Teachers of Mathematics. (2000). Principles and standards for school mathematics. Reston, VA: National Council of Teachers of Mathematics.
Piaget, J. (1972). The psychology of the child. New York, NY: Basic Books.
Sardiman, A. M. (2018). Interaksi dan motivasi belajar mengajar. Jakarta, Indonesia: Rajawali Pers.
Schraw, G. (1998). Promoting general metacognitive awareness. Instructional Science, 26, 113–125. Dordrecht, Netherlands: Springer.
Skinner, B. F. (1953). Science and human behavior. New York, NY: Macmillan.
Sugiyono. (2022). Metode penelitian kuantitatif. Bandung, Indonesia: Alfabeta.
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Hermanto Hermanto, Suparman Suparman
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Copyright Notice
Authors who publish with JISIP (Jurnal Ilmu Sosial dan Pendidikan) agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.Â
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
