Enhancing Digital Education: A Study on Intelligent Tutoring System(ITS)
Abstract
Intelligent Tutoring Systems (ITS) are widely used to manage, deliver, and evaluate educational content; however, most lack adaptive capabilities to meet individual learner needs. This study integrates three key components—student activity tracking, performance prediction, and data visualization—to enable early identification of at-risk learners and support targeted interventions. Leveraging deep learning techniques enhances prediction accuracy, demonstrating the potential of advanced analytics to improve instructional decision-making, personalized feedback, and overall learning outcomes.
Fields of Study & Subjects
Intelligent Tutoring Systems and Adaptive Learning
Online Learning and Analytics
Artificial Intelligence in Education
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 27 January 2026