Towards a Web-Based Teaching Tool to Measure and Represent the Emotional Climate of Virtual Classrooms

This paper presents the first results of a teaching innovation project named “Emotional Thermometer for Teaching” (ETT) carried out at the Universitat Oberta de Catalunya. The ETT project intersects the scopes of eLearning and Affective Computing with the aim of collecting and managing emotional information of online students during their learning process. Such information allows lecturers to monitor the overall emotional climate of their virtual classrooms whilst detecting critical moments for timely interventions, such as assisting in certain learning tasks that generate negative emotions (anxiety, fear, etc.). To this end, an innovative teaching tool named ETT was developed as a functional indicator to measure and represent the classroom emotional climate, which is dynamically evolving as the course goes by. In this paper, the technical development of the ETT tool is described that meets the challenging requirement of correctly identifying the overall emotional climate of virtual classrooms from the posts sent by students to in-class forums. First, a machine learning approach combined with Natural Language Processing techniques is described to automatically classify posts in terms of positive, neutral and negative emotions. Then, a web-based graphical tool is presented to visualize the calculated emotional climate of the classroom and its evolution over time. Finally, the post classification approach is technically tested and the initial results are discussed.