Affinity-based learning object retrieval in an e-learning environment using evolutionary learner profile

• Published in: Knowledge management & e-learning Vol. 8; no. 1; pp. 182 - 199
• Main Authors: Raghuveer, V R, Tripathy, B K
• Format: Journal Article
• Language: English
• Published: Hong Kong The University of Hong Kong - Faculty of Education 01.03.2016; Hong Kong Bao Long Accounting & Secretarial Limited
• Subjects: Affinity; College Science; Distance learning; Educational Environment; Educational Needs; Electronic Learning; Engineering Education; Information Retrieval; Instructional Development; Knowledge Management; Learning Management Systems; Learning Processes; Literature Reviews; Management Systems; Metadata; Network Analysis; Object recognition; Periodicals; Preferences; Profiles; Teaching Experience
• ISSN: 2073-7904; 2073-7904; 2309-5008
• DOI: 10.34105/j.kmel.2016.08.012

With the abundance of learning objects (LOs) available across the web, there arises a demand for retrieving the LOs that exactly suit the learners’ requirements. In order to achieve this, the learner profile (LP) should exactly mimic the subject specific requirements of the learner as well as evolve over the learning cycle. Moreover, each LO should project itself in such a way that the learning management system is able to find it as a suitable candidate for a specific learner requirement. This paper proposes a novel method that fetches appropriate LOs for the learner by mapping his/her learner profile with those of the LOs. The LOs thus retrieved are then re-ranked according to their affinity towards the particular learner’s requirements and then presented to the learner. The experimental results demonstrated the effectiveness of the proposed method in retrieving appropriate learning content for learners.