A recommendation system based on an adaptive learning cognitive map model and its effects

Abstract

ABSTRACT Most online learning researchers use resource recommendation and retrieve based on learning performance and learning style to provide accurate learning resources, but it is a closed and passive adaptive way. Learners always do not know the recommendation rationale and just receive the result-oriented recommended resources without having a chance to make a procedural reflection and self-directed adjustment. This study proposed an adaptive learning cognitive map model and developed an online learning system based on this model. The proposed system could represent learners’ knowledge structure and cognitive state that allow learning contents, learning activities, learning paths and learning partners to be adjusted continuously, thus providing learners with appropriate learning resources and initiative reflection opportunities during the whole learning procedure. This study conducted a contrast experiment to evaluate the effectiveness of the proposed system. Students in the experimental group received learning interventions according to their adaptive learning cognitive maps. The result demonstrated that the proposed system with the learning cognitive map improved students’ learning achievement, learning satisfied, user acceptance of information technology and learning interaction while did not reduce or increase cognitive load.