Enhancing learning attitudes and performance of students in physics with a mastery learning mechanism-based personalized learning support system

Abstract

© 2016 IEEE. Most existing personalized learning support systems facilitate students' learning by providing learning suggestions or learning content to individual students based on their background or profiles. It is difficult to adapt learning activities to respond to students' ongoing learning performances and status, leading to the limitation in enhancing online personal learning performance and learning attitudes. To address this issue, a mastery learning mechanism was proposed to monitor individual students ongoing learning situations; moreover, students' conceptual learning problems, learning styles and current understanding status were considered for providing effective personalized learning activities. An online personalized learning support system was developed basing on the novel mastery learning mechanism. The experimental results show that the students who learned with our proposed system had better learning attitudes toward the learning activities, better understanding and higher perception of the usefulness of the learning system, and better learning performance of Simple Electricity on Physics course than those who learned with the conventional system.