A learning diagnosis architecture with a Bayesian network approach

In this paper, we present a knowledge learning diagnosis approach to supporting a computer-supported collaborative learning environment. Bayesian network technique is used here to diagnose the misconception about learning knowledge and to reason potential misconception for individual learners. After learners have made a test, the system using probabilistic reasoning will automatically create learning communities based on the learners´ characteristics and test results. This work is motivated by diagnosing learning performance of learners for both instructors and learners to understand concept comprehension of learners in a computer-supported collaborative learning (CSCL) environment.