An Emotion Oriented Topic Modeling Approach to Discover What Students are Concerned about in Course Forums

Course forums offer an interactive channel for learners to express opinions and feedback, which contain valuable emotions and topic information towards courses. In this paper, we propose an emotion oriented topic probabilistic model that can be used to calculate distributions of emotion-topic over words to discover what students are most concerned about. An experiment on real-life data indicates that students had a positive attitude for knowledge applications, a negative experience for the learning system, and expressed confusion about the final exam. We also visualize the temporal trends of emotions of the whole group and the groups with different levels of achievement. The proposed model has a potential in discovering students' emotions in their feedback, thus improving the online learning experience, and identifying at-risk students timely.