Enhancing Digital Education: A Study on Intelligent Tutoring System(ITS)

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Authors: Nadipriya A, Muthuselvi R
Cited by: 0

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