Personalization of Adaptive Learning Modules: Differential Impact Analysis Based on Students' Prior Knowledge Profiles and Self-Regulated Learning Levels

Authors

  • Sudi Dul Aji Universitas PGRI Kanjuruhan Malang, Indonesia
  • Nurul Ain Universitas PGRI Kanjuruhan Malang, Indonesia
  • Akhmad Zaini Universitas PGRI Kanjuruhan Malang, Indonesia
  • Hestiningtyas Yuli Pratiwi Universitas PGRI Kanjuruhan Malang, Indonesia
  • Kadek Dwi Hendratma Gunawan Universitas Sebelas Maret, Indonesia
  • Salsabila Kholifahtun Nisa’ Universitas Sebelas Maret, Indonesia
  • Muhammad Nur Hudha Universitas Sebelas Maret, Indonesia

DOI:

https://doi.org/10.33394/jk.v12i1.17755

Keywords:

Adaptive Learning Module, Self-Regulated Learning, Learner Profile

Abstract

This study aims to identify student learner profiles based on a combination of prior knowledge and Self-Regulated Learning (SRL) levels and to analyze the differential impact of an adaptive learning module on knowledge and SRL improvement in each profile. Using a mixed-methods explanatory sequential design, 92 undergraduate physics education students were selected through purposive sampling. K-Means cluster analysis was applied to form learner profiles, followed by a six-week pre–post intervention and qualitative interviews. The results identified three learner profiles (Proficient-Autonomous Learner, Resilient-Developing Learner, and Proficient-Fragile Achiever). The result showed that the adaptive module significantly improved Results showed significant knowledge gains across profiles, while SRL improvements differed significantly. The Proficient–Fragile Achiever group demonstrated the largest SRL gain (p < .001; large effect size, d > 0.80), associated with more frequent scaffolding support. In conclusion, the effectiveness of adaptive modules is highly dependent on learner profiles, with the most significant benefits in their ability to provide external support for building self-regulation skills. These findings imply that learning technology design should incorporate SRL as a key variable for personalization, and institutions can utilize these platforms as intervention tools for students with weak learning independence.

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Published

2026-03-14

How to Cite

Aji, S. D., Ain, N., Zaini, A., Pratiwi, H. Y., Gunawan, K. D. H., Nisa’, S. K., & Hudha, M. N. (2026). Personalization of Adaptive Learning Modules: Differential Impact Analysis Based on Students’ Prior Knowledge Profiles and Self-Regulated Learning Levels. Jurnal Kependidikan : Jurnal Hasil Penelitian Dan Kajian Kepustakaan Di Bidang Pendidikan, Pengajaran, Dan Pembelajaran, 12(1), 251–258. https://doi.org/10.33394/jk.v12i1.17755

Issue

Vol. 12 No. 1 (2026): March

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Articles

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