2692-4048ISSN (Online)
2770-0070ISSN (Print)
Volume 21 , Issue 2 , PP: 383-295, 2026 | Cite this article as | XML | Html | PDF | Full Length Article
A. F. Elgamal 1 * , S. S. Al-Saidi 2 , S. A. Abdelsamie 3 * , A. A. A. Kamel 4 *
Doi: https://doi.org/10.54216/FPA.210224
This study proposes an Intelligent Tutoring System (ITS) to enhance hand-knitting skills among Home Economics students through AI-driven personalized learning, addressing the limitations of traditional generic methods. The system integrates computer vision, adaptive algorithms, and interactive tutorials to provide real-time feedback and track progress. A study involving 60 students (30 control, 30 experimental) showed the ITS group achieved significantly higher post-test scores, confirming improved proficiency and engagement. Results reveal that the IT IS effectively accelerates skill acquisition and deepens understanding compared to conventional instruction.
Intelligent Tutoring System (ITS) , Hand Knitting , Home Economics , Adaptive Learning , Computer Vision , AI in Education
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