Work

Designing an Intelligent Learning System Based on the Knowledge Tracing Model to Enhance Self-Efficacy, Academic Passion, and Achievement Among Educational Technology Students

Year: 2026

Type: article

Abstract: Knowledge tracing is a methodological framework focused on modeling and predicting learners’ future performance on tasks involving related concepts, while also tracking the dynamic evolution of their knowledge over time. The current study aims to assess the effectiveness of an intelligent learning system (ILS) based on the Knowledge Tracing Model in improving academic passion, self-efficacy, and achievement among 100 students enrolled in a Special Care course. A quasi-experimental design was employed via a single experimental group without a control group. Three instruments—achievement test, self-efficacy, and academic passion—were administered pre- and post-intervention. A statistically significant improvement was observed across all three domains. The findings suggest a positive association between the use of the ILS and gains in academic achievement, self-efficacy, and academic passion. In conclusion, the results support the use of knowledge-tracing-based learning systems for academic performance enhancement and university students’ motivation.

Source: Computers

DOI: 10.3390/computers15020090

Authors: Mohamed Ramadan Attia, Shaimaa Youssef Soufy, Riham Moustafa Kamaleldin, Gomaa Said Mohamed Abdelhamid

Institutions: Fayoum University, Rustaq College of Education, University of Technology and Applied Sciences

Language: English

Topic: Intelligent Tutoring Systems and Adaptive Learning

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: gold

Estimated APC paid: $2,172