Scaffolding student online discussions using past discussions: PedaBot studies

摘要

We are developing instructional tools that will help students and instructors use discussion boards more effectively, with an emphasis on automatically assessing discussion activities and promoting student discussion participation and learning. In this paper, we present a discussion scaffolding tool that exploits natural language processing and information retrieval techniques. The PedaBot tool is designed to aid student knowledge acquisition, promote reflection about course topics and encourage student participation in discussions. It dynamically processes student discussions and presents related discussions and document from a knowledge base of past discussions and course materials. This paper describes the system and presents a comparative analysis of the information retrieval techniques used to respond to free-form student discussions, including a combination of topic profiling, term frequency-inverse document frequency, and latent semantic analysis. Responses are presented as annotated links that students can follow and rate for usefulness. The tool has been integrated into a live discussion board and has been used by an undergraduate computer science course for three semesters. We report current studies of PedaBot from its usages based on student viewings, student ratings, and a small survey. Initial results indicate that there is a high level of student interest in the feature and that its responses are moderately relevant to student discussions. We are exploring more opportunities to exposing the tool to students.