Analysis and prediction of students emotions while doing programmign exercises
The modeling of student emotions has recently considerable interest in the field of intelligent tutoring systems. However, most approaches are applied in typical interaction models characterized by frequent communication or dialogue between the student and the tutoring model. In this paper, we analy...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | text |
| Published: |
Animo Repository
2019
|
| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/13068 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | De La Salle University |
| Summary: | The modeling of student emotions has recently considerable interest in the field of intelligent tutoring systems. However, most approaches are applied in typical interaction models characterized by frequent communication or dialogue between the student and the tutoring model. In this paper, we analyze emotions while students are writing computer programs without any human or agent communication to induce displays of affect. We use a combination of features derived from typing logs, compilation logs, and a video of the students’ face while solving coding exercises and determine how they can be used to predict affect. We find that combining pose-based, face-based, and log- based features can train models that predict affect with good accuracy above chance levels and that certain features are discriminative in this task. |
|---|