Title: A hybrid recommendation system for e-learning based on the design social science research process model

Authors: Chandrakant Mallick; Syamalendu Pati; Bijay Kumar Paikaray; Jayanta Mondal

Addresses: Department of Computer Science and Information Technology, Gandhi Institute of Technological Advancement (GITA) Autonomous College, Odisha, India ' Department of Computer Science and Engineering, Trident Academy of Technology, Bhubaneswar, Odisha, India ' Centre for Data Science, Department of Computer Science and Engineering, Siksha 'O' Anusandhan (Deemed to be) University, Bhubaneswar, Odisha, India ' School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, Odisha, India

Abstract: Existing e-learning systems have the potential for improvement in terms of real-time scalability and personalised adaptation, which could improve the learning experiences of individual users. The study uses the design science research (DSR) process to explore potential enhancements to e-learning systems through collaborative filtering recommendation systems (CFRS). It expands on earlier theories and proposes a DSRP-based hybrid recommendation system to improve the user experience in e-learning. The proposed technique incorporates key prototype modelling approaches like collaborative filtering, machine learning, and clustering. Specialists seeking new approaches to improve online education, such as information system researchers and e-learning practitioners, are the intended audience for this method. It has practical applications in addition to its theoretical merits.

Keywords: e-learning; recommendation system; design science research; DSR; information system; collaborative filtering; CF.

DOI: 10.1504/IJLT.2025.151033

International Journal of Learning Technology, 2025 Vol.20 No.4, pp.400 - 420

Received: 29 Aug 2023
Accepted: 18 Mar 2024
Published online: 12 Jan 2026 *

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