Title: Context-aware recommender system for adaptive ubiquitous learning

Authors: Olutayo Boyinbode; Tunde Fatoke

Addresses: Department of Information Technology, Federal University of Technology, Akure, Ondo State, Nigeria ' Department of Computer Science, Federal University of Technology, Akure, Ondo State, Nigeria

Abstract: The use of context-aware recommender systems for adaptive ubiquitous learning has become a promising and interesting research direction in recent years, both as a result of the vast use of ubiquitous devices in our day-to-day lives and because of students' increasing desire to learn with ease anytime and anywhere without restriction. This paper implements an RFID-based context-aware technology and recommender system for adaptive ubiquitous learning that will help learners to achieve personalised learning goals and greater learning efficiency. Our context-aware recommender suggests courseware to students based on their location, surrounding noise level and time of day. Radio Frequency Identification (RFID) technology was used to acquire context awareness, and fuzzy logic was employed to develop courseware recommendations. The front end of the system was developed using Android Studio. Experimental results were obtained from selected students from different disciplines who evaluated the system.

Keywords: context-aware; recommender system; ubiquitous learning; RFID; radio frequency identification; courseware; noise level; location; time; LMS; learning management system.

DOI: 10.1504/IJMLO.2021.118437

International Journal of Mobile Learning and Organisation, 2021 Vol.15 No.4, pp.409 - 426

Received: 12 Feb 2019
Accepted: 14 Apr 2020
Published online: 26 Oct 2021 *

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