Citation

Adam, Ibrahim (2026) Design and development of personalised adaptive content for E-Learning. PhD thesis, Multimedia University.

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Abstract

The increasing demand for personalised learning has positioned adaptive elearning as a promising alternative to traditional one-size-fits-all instructional models. However, despite technological advancements, significant uncertainty remains regarding how to design and implement pedagogically effective personalised elearning environments, particularly within resource-constrained higher education contexts. Existing approaches often prioritise technological capabilities over instructional coherence, resulting in fragmented personalisation that fails to meaningfully enhance learning experiences. This study addresses this gap by developing and empirically validating a pedagogically grounded framework for adaptive e-content development to support personalised e-learning. Grounded in a pragmatic research paradigm, which supports the integration of quantitative and qualitative methods to address complex educational problems, the study employs a Design and Development Research design. The study was conducted in three phases: Analysis, Design and Development, and Evaluation, supported by a case study based mixed methods approach within the context of The Maldives National University. The Analysis Phase comprised a systematic literature review and institutional needs assessment to examine learner satisfaction and identify key limitations in the existing e-learning environment. Findings revealed that content quality and personalisation were the weakest dimensions, and multiple regression analysis confirmed them as the strongest predictors of overall learner satisfaction. These findings established the need for a structured and instructionally aligned approach to personalisation. The Design and Development Phase translated these needs into a set of design requirements, operationalised through four key design considerations. Central to this phase was the reconceptualisation of content as instructionally aligned Learning Objects integrating learning outcomes, activities, materials, and assessments. The design incorporated a hybrid learner profiling strategy and dynamic, data-driven adaptation mechanisms, implemented within a Moodle-based environment. Expert validation using the Fuzzy Delphi Method demonstrated strong consensus on the pedagogical coherence and feasibility of the proposed approach. The Evaluation Phase assessed the effectiveness of the developed Personalised Adaptive e-Learning Environment (PAeLE) through pilot implementation using a one-group pre-test/post-test design, learner satisfaction survey, and focus group discussions. The results indicated statistically significant improvements in academic performance (t(49) = −13.15, p < .001) and learner satisfaction (t(71.41) = −14.30, p < .001), with the largest gains observed in content and personalisation. Multiple regression analysis revealed that content and learning community significantly predicted perceived personalisation, while learner interface did not, highlighting the dominant role of instructional design over technological features in shaping personalised learning experiences. Qualitative findings further confirmed increased learner autonomy, engagement, and perceived relevance of learning materials. The findings culminated in the development of the Personalised Adaptive Content for e-Learning Development (PACeD) Framework, which integrates instructional design principles, learner profiling, and adaptive mechanisms within a scalable and resource-efficient model. The study contributes to theory by positioning personalisation as an instructional design process, to practice by demonstrating a feasible implementation using open-source LMS tools, and to methodology by providing a validated framework for adaptive e-content development. Overall, the study demonstrates that effective personalised e-learning can be achieved through the alignment of pedagogy and technology, offering a practical and scalable solution for higher education institutions in resource-constrained contexts.

Item Type:	Thesis (PhD)
Additional Information:	Call No.: LB1028.5 .I27 2026
Uncontrolled Keywords:	Computer-assisted instruction
Subjects:	L Education > LB Theory and practice of education > LB1025-1050.75 Teaching (Principles and practice)
Divisions:	Faculty of Creative Multimedia (FCM)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	19 Oct 2026 04:16
Last Modified:	19 Oct 2026 04:16
URII:	http://shdl.mmu.edu.my/id/eprint/16922

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