Identifying and Incorporating Affective States and Learning Styles in Web-based Learning Management Systems

Abstract

Learning styles and affective states influence students' learning. The purpose of this study is to develop a conceptual framework for identifying and integrating learning styles and affective states of a learner into web-based learning management systems and therefore provide learners with adaptive courses and additional individualized pedagogical guidance that is tailored to their learning styles and affective states. The study was carried out in three phases, the first of which was the investigation and determination of learning styles and affective states which are important for learning. Phase two consisted of the development of an approach for the identification of learning styles and affective states as well as the development of a mechanism to calculate them from the students' learning interactions within web-based learning management systems. The third phase was to develop a learning strategy that is more personalized and adaptive in nature and tailored to learners' needs and current situation through considering learners' learning styles and affective states, aiming to lead to better learning outcomes and progress.