Personalized adaptive e-learning application based on learning styles
Year: 2025
Type: article
Abstract: This study presents the development of an adaptive e-learning system designed to deliver personalized content according to students’ learning styles. The system analyzes individual learner profiles through a profiling module, structures learning resources via a content management module, and supports the process with instant feedback mechanisms. By dynamically adapting the flow of content, the system creates distinct learning journeys for students. The study presents the system’s architecture, design-based research methodology, and its intended contributions to learner-centered education. It is anticipated that the developed framework will support future research in adaptive e-learning. Thus, the study is expected to provide useful insights into personalized learning processes at both the national and international level.
DOI: 10.51271/jceees-0030
Authors: Ali Karay, Erdal Erdal, Atilla Ergüzen
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W4414845671
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