CLUSTERING STUDENTS TO HELP EVALUATE LEARNING

摘要

In this paper we show how clustering techniques can be applied to student answers generated from a web-based tutoring tool. In particular we are interested in extracting clusters of students based on the mistakes they made using the tool, with the aim of obtaining pedagogically relevant information and providing this feedback to the teacher. The data we used comes from the Logic-ITA, a web-based tutoring tool to practice formal proofs currently in use in the School of Information Technologies at the University of Sydney.