Determining the Most Important Features for Designing a Smart Recommender Framework in E-Learning Systems: An Investigation Using the Delphi Study Method

Despite the advantages of online learning, many students have trouble connecting with the material since it is so generic. By customizing information to each learner’s needs, the smart recommender system is predicted to boost the effectiveness of online learning. Nevertheless, current e-learning platforms frequently struggle to identify and utilize user features for inclusion in this customisation, which has a negative impact on user engagement and retention. The article uses the Delphi study approach to determine how smart recommender system features can be prioritized. The Delphi panel’s specialists were selected from educational technologists at the Namibia University of Science and Technology with experience in instructional design and user experience design. According to the first phase of the Delphi study’s findings, the development of smart recommender systems should give priority to non-technical factors that include learner characteristics, teaching and learning support, and community building. The study also identified the necessity for a flexible system that makes use of both traditional teaching methods and technology-assisted instruction. In addition, considerations such accessibility, cost, and bandwidth speed are deemed to be very important.