Citation

Adam, Ibrahim and Tengku Shariman, Tengku Putri Norishah and Siran, Zainudin (2026) Human-centered adaptive e-learning: leveraging learner profiling and adaptive algorithms to enhance satisfaction in digital learning environments. Frontiers in Computer Science, 8. ISSN 2624-9898

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Abstract

Introduction: The growing demand for personalized digital learning has increased interest in adaptive e-learning environments that tailor instructional experiences to individual learners. Despite these developments, many online learning implementations still rely on standardized instructional designs that limit meaningful personalization and learner engagement. This study investigates the effectiveness of an adaptive e-learning intervention developed using a human-centered design approach, where learner satisfaction was used as a key indicator of personalized learning experiences. Methods: Guided by a design-based research approach, the study integrates the Felder–Silverman Learning Style Model and the Personalized Learning Design Framework to propose an adaptive e-content development mechanism that combines instructional design principles with learning style categorization. The proposed approach conceptualizes content as modular learning objects in which learning outcomes, instructional materials, and knowledge assessments are adaptively organized to support personalized learning pathways aligned with learners’ style preferences while allowing dynamic adjustments based on evolving learning needs. Two topics within an undergraduate course module were redesigned using this approach to incorporate adaptive instructional content and personalized learning pathways. A mixed-methods intervention study was subsequently conducted with 50 undergraduate students. Learner satisfaction was measured across four human-centered constructs: learner interface, content, learning community, and personalization. Quantitative data were analyzed using descriptive statistics, correlation analysis, and multiple regression analysis, while a focus group discussion provided qualitative insights into learners’ experiences. Results: The regression model significantly predicted personalization, explaining 44.5% of the variance in learners’ perceptions. Content (β = 0.418, p = 0.016) and learning community (β = 0.467, p = 0.005) emerged as significant predictors, whereas learner interface was not significant. Focus group findings further highlighted the importance of adaptive learning materials and collaborative interaction in shaping personalized learning experiences. Discussion: These findings underscore the importance of human-centered instructional design in developing effective adaptive e-learning environments. The study demonstrates that prioritizing adaptive content organization and building collaborative community pathways significantly enhances learner satisfaction and engagement in higher education.

Item Type:	Article
Uncontrolled Keywords:	Adaptive learning, e-learning
Subjects:	L Education > LB Theory and practice of education > LB1060 Learning
Divisions:	Faculty of Creative Multimedia (FCM)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	04 Aug 2026 02:20
Last Modified:	04 Aug 2026 02:20
URII:	http://shdl.mmu.edu.my/id/eprint/16457

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