A, AI-Based Adaptive Learning Mo “AI-Based Adaptive Learning Model to Enhance Students’ Self-Directed Learning in Higher Education”

Design, Implementation, and Evaluation of a Personalized Learning Approach

Authors

  • Oktaviana Bangun Universitas Mandiri Bina Prestasi Medan

DOI:

https://doi.org/10.30983/biced.v3i1.808

Keywords:

AI-Based Adaptive Learning, Self-Directed Learning

Abstract

This study aims to develop and validate an AI-based adaptive learning model designed to enhance students’ self-directed learning (SDL) in higher education. The research employed a mixed-method design, combining qualitative needs analysis with quantitative validation and pilot testing. Findings indicate that the adaptive learning model significantly improves learner autonomy, engagement, and performance. The integration of learner profiling, adaptive content delivery, dynamic assessment, and learning analytics provides a personalized pathway that fosters SDL. This study contributes to the field of educational technology by bridging AI innovations with pedagogical frameworks, supporting the digital transformation of higher education.

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Published

2025-12-24

How to Cite

Bangun, O. (2025). A, AI-Based Adaptive Learning Mo “AI-Based Adaptive Learning Model to Enhance Students’ Self-Directed Learning in Higher Education”: Design, Implementation, and Evaluation of a Personalized Learning Approach. BiCED Proceeding, 3(1), 128–132. https://doi.org/10.30983/biced.v3i1.808