Learning Ability Clustering in Collaborative Learning

Collaborative learning promotes learning motivation which encourages the active participation and leads to good learning performance. In most cases, good grade is usually a good indicator of good learner. Teachers might classify learners into various groups according to their grade. As a result, learners with poor grades are easily depressed and self-distrust. In this paper, we integrate K-means clustering method and IRT forecasting process to solve the grouping issue in collaborative learning. With a better grouping solution, teachers then can adjust the learning materials adaptively and teach students according to the learning aptitude.