There are usually limited user evaluation of resources on a recommender system, which caused an extremely sparse user rating matrix, and this greatly reduce the accuracy of personalized recommendation, especially for new users or new items. This paper presents a recommendation method based on rating prediction using causal association rules.…

This paper challenges traditional dichotomies that identify temporal and spatial restrains as relevant defining properties of learning environments. We present a critique of the current dominant computer-supported cooperative work (CSCW) taxonomy. Although we believe that the taxonomy does provide useful information, we question whether the axis…

The main aim of this study is to integrate cooperative learning strategies, mastery learning and interactive multimedia to improve students' performance in Mathematics, specifically in the topic of matrices. It involved a quasi-experimental design with gain scores and time-on-task as dependent variables. The independent variables were three…