The Model for Identifying the Dimensions and Components of AI-Based Tailored Physical Education for Students with Special Needs: A Meta-Synthesis Approach

Subject Areas : Computer Engineering and IT

homeyra kave ¹ , aliakbar ajam ^{2 *} , hosien momenimahmouei ³ , hosien soltani ⁴

1 -
2 - Department of Educational Sciences, Islamic Azad University, Torbat Heydariyeh, Iran
3 - Associate Professor of Curriculum , Islamic Azad University, Torbat Heydariyeh Branch, Torbat Heydariyeh, Iran
4 - Department of Physical Education and Sport Sciences, Torbat Heydariyeh Branch, Islamic Azad University, Torbat Heydariyeh, Iran

Received: 2025-03-09 Accepted : 2025-09-12 Published : 2025-10-13

Keywords: Adapted physical education, artificial intelligence, students with special needs.,

Abstract :

The present study was conducted with the aim of identifying the dimensions and components of artificial intelligence-based physical education adapted for students with special needs. For this purpose, a qualitative meta-synthesis method was used. Research data were searched and collected using Roberts' six-stage model in the period of interest (internal 1400-1404 and external 2020-2024). The scope of the study was all articles (97 articles) that were presented on the research topic and related fields in specialized and scientific databases. The research sample was 27 articles, which were selected purposefully and based on thematic, content, and theoretical saturation monitoring of the data. The research data were analyzed at this stage using thematic content analysis. In order to examine the validity and reliability of the findings, the criteria of the researcher's self-review and the peer review method (rater agreement coefficient) were also used. By analyzing the data, the dimensions and components of AI-based tailored physical education were organized into five dimensions, 17 axes, and 78 categories, including specific physiological assessment (identifying the physical characteristics of students with special needs, psychological analysis of students with special needs, using AI data for prediction, adapting to global standards); adaptive exercise design (designing individual physical exercises, managing diversity in programs, intelligent tracking and monitoring); smart training environment (simulating the sports environment, using environmental sensors, intelligent adaptation of the training environment); data-driven educational strategies (designing motivational programs based on data, creating interaction and participation in different groups, using positive feedback), and multi-domain evaluation (performance evaluation, cognitive and motivational evaluation, social and communication evaluation, adaptive and personalized evaluation).

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