On linking problem-based learning activities and students’ learning styles in personalised learning

Abstract

The paper is aimed to present an original method of identifying students preferring to actively use Problem-Based Learning (PBL) activities in personalised learning process. In the paper, the authors use an original learning personalisation approach based on identifying students’ learning needs (namely, learning styles), suitability of learning components (e.g. learning activities) to learning styles, probabilistic indexes of learning components’ suitability to particular students, and on applying intelligent technologies. Proposed method is aimed to personalise learning by applying Felder-Silverman learning styles model and intelligent technologies i.e. expert evaluation, ontologies and recommender system and thus to improve learning quality and effectiveness. Literature review presented in the paper revealed that PBL is a popular student-centred pedagogy in which students learn about a subject through the experience of solving open-ended problems found in trigger material. The PBL process does not focus on problem solving with a defined solution, but it allows for the development of other desirable skills and attributes. This includes knowledge acquisition, enhanced group collaboration and communication. The method of identifying students preferring to actively use PBL activities is based on identifying those activities’ indexes of probabilistic suitability to particular students according to their learning styles. Proposed method includes expert evaluation techniques and the method of identifying probabilistic suitability indexes to particular students. Thus, we could easily identify which students prefer to use PBL in their learning process mostly. After that, corresponding ontologies and recommender system should be created to propose the most suitable learning activities to particular students. These new elements make the given work distinct from all the other earlier works in the area.