Student engagement prediction: Bridging learning analytics and AI
Abstract
This project explores Under the current situation; distance education has rapidly become popular among students and teachers. This educational situation has changed the traditional way of teaching in the classroom. Under this kind of circumstance, students will be required to learn independently. But at the same time, it also brings some drawbacks, and teachers cannot obtain the feedback of students’ engagement in real-time. This thesis explores the feasibility of applying a lightweight model to recognize student engagement and the practicality of the model in a distance education environment.
Fields of Study & Subjects
Online Learning and Analytics
Intelligent Tutoring Systems and Adaptive Learning
Artificial Intelligence in Education
Publication details
- Journal / source
- CRC Press eBooks
- Pages
- 586–594
- Publication date
- 10 March 2026
- Language
- EN
- Document type
- Book chapter