Scaffold learners´ qualitative browsing of major topics in learning forum

After the system database contains an accumulation of discussion messages with date tagged from different classes within a course, an instructor may want to have an overview of learners´ discussions, such as the top ten hot topics, without reading every message in the learning forum. Hence, it is necessary to model the relationships between discussion messages during a specific time interval for showing the major discussion topics. Consequently, an instructor can use the information to refine his/her teaching strategies in the classroom or virtual classroom. We propose a statistical model of word usage, which originates from information retrieval technology, to group learners´ discussion messages by concept similarity into time dependent topics. Consequently, the methodology can generate comprehensible topics for an instructor to sketch out what learners were discussing by concept-based message groups and when the important messages were posted by a temporal interface.