Analysis and prediction of students emotions while doing programmign exercises

College

College of Computer Studies

Department/Unit

Software Technology

Document Type

Conference Proceeding

Source Title

Intelligent Tutoring Systems 2019

Publication Date

2019

Abstract

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.

html

Disciplines

Computer Engineering | Computer Sciences

Series Title

Lecture notes in computer science ; volume 11528

Keywords

Emotion recognition; Intelligent tutoring systems; Face perception

Upload File

wf_no

This document is currently not available here.

Share

COinS