Empowering Teachers in E-Learning: A Case-Based Recommender System for Effective Learning Design

Abstract

In the rapidly evolving field of e-learning over the past decade, the learning design (LD) sector has emerged as a crucial determinant of success. It plays a vital role in ensuring effective instructional design, preserving best practices, enhancing educational quality, promoting personalization, and embracing technological innovation. However, the creation of effective LDs can be challenging due to the diverse range of learning methods, strategies, resources, learner profiles, evolving technologies, and communication platforms. This paper aims to address the research question of how to efficiently leverage recommender systems (RSs) and repurpose existing LD solutions to provide valuable support for teachers in the LD process. Specifically, this paper focuses on the implementation of case-based recommender system (CBRS) and presents the initial evaluation results. CBRS, which is a RS, assists teachers in locating and reusing pre-existing LDs. The initial evaluation results validate the system’s effectiveness in supporting teachers throughout the LD process by offering reliable and useful LDs. Furthermore, additional findings pertaining to the overall user perception and the perceived value of CBRS are discussed.