Detecting Students' Affective States in Industry-focused Projects

Veronica Liesaputra, Claudia Ott

Abstract: In industry-focused projects, students feel overwhelmed by the fast-paced nature of the group projects and the involvement of actual industry clients. To be able to provide timely feedback and support in challenging learning situations, we have experimented with the use of an emotion detection tool, in our case the IBM Watson™ Tone Analyzer, to automatically recognize the students’ emotional states and the potential issues they might have during their projects. Preliminary results show that the objectively recognised emotional tones moderately to strongly correlate with students’ issues as observed by the academic coordinators and also with students’ final marks for the project work.