A Framework to Provide Personalization in Learning Management Systems through a Recommender System Approach

Abstract

Abstract. Personalization in learning management systems (LMS) occurs when such systems tailor the learning experience of learners such that it fits to their profiles, which helps in increasing their performance within the course and the quality of learning. A learner's profile can, for example, consist of his/her learning styles, goals, existing knowledge, ability and interests. Generally, traditional LMSs do not take into account the learners' profile and present the course content in a static way to every learner. To support personalization in LMS, recommender systems can be used to recommend appropriate learning objects to learners, not only based on their individual profile but also based on what worked well for learners with a similar profile. In this paper, we propose a framework to integrate a recommender system approach into LMS. The proposed framework is designed with the goal of presenting a flexible integration model which can provide personalization by automatically suggesting learning objects to learners based on their current situation as well as successful learning experiences of learners with similar profiles in a similar situation. Such advanced personalization can help learners in many ways such as reducing the learning time without negative impact on their marks, improving learning performance as well as increasing the level of satisfaction.

Recommender Systems: Algorithms, Evaluation and Limitations

“…Several studies discuss personalization through recommender systems. Imran [9] personalized learning management system LMS by integrating a recommender system in already developed learning management proposed a framework that is designed with the goal of providing personalization by automatically suggesting learning objects to learners with the aim of improving learning experience.…”

Learning Management System with Prediction Model and Course-content Recommendation Module

“…A general proposal structure of RS by Imatzi and Megias (2008), shown in Figure 2, and the framework architecture proposed by Imran, Hoang, Chang, and Graf (2014) in Figure 3 serve as the guiding paradigms for this study. Both of the frameworks have their own strengths; however, there are underlying limitations which exist either in the types of the objects that can be recommended by the LMS or in the process and results of its integrated RS.…”

A Framework of Semantic Recommender System for e-Learning

“…The proposed system helps the learners to search course content and get more personalized and contextual recommendation. Imran et al [1] developed a framework to incorporate a recommender system approach into LMS. The developed framework can provide personalization by recommending LOs to learners based on their existing situation and learners with similar profiles who have successful learning experiences in a similar situation.…”

“…Learning management systems (LMSs) are typically employed in large-scale educational institutions to facilitate the delivery and organization of e-learning [1]. LMS can be defined as "the infrastructure that delivers and manages instructional content, identifies and assesses individual and organizational learning or training goals, tracks the progress towards meeting those goals, and collects and presents data for supervising the learning process of an organization as a whole" [2].…”

“…LO can be a text document, an audio file, a video, a picture, or a complete website [3]. Commonly, LMSs are considered as one-size-fits-all systems as they deliver the same kind of course structure and LOs to each learner [1], [4]. However, each learner has different characteristics such as levels of expertise, learning styles, prior knowledge, cognitive abilities and interests, and therefore, a one-size-fits-all systems do not support most learners.…”