Utilizing Artificial Intelligence Applications in the Professional Development of Basic Education Teachers
The present study aims to propose a conceptual framework for utilizing artificial intelligence (AI) applications in teaching and learning processes, with the goal of supporting basic education teachers—specifically those teaching core subjects—in enhancing their instructional performance within the classroom. This is achieved by providing diverse examples and models of AI-supported educational activities, assessment tools, and methods for analyzing student performance data and utilizing it in classroom practice. To explore the current status of AI integration, a survey was used to investigate the teachers’ views on their use of AI applications in teaching and the challenges they encounter in implementing these technologies. The study sample comprised 285 teachers from the primary and preparatory stages. Findings revealed that 69% of the participating teachers had not received any training related to digital applications in general, nor AI applications in particular. This highlights the urgent need for a proposed professional development model grounded in AI applications, aimed at enhancing teachers’ pedagogical practices and integrating various digital tools and AI programs into lesson planning for use across different subjects and classroom contexts. Based on the results, the study recommends organizing targeted training programs for teachers and other school staff on the effective integration of AI applications into educational settings. Such training program is essential to ensure the effective use of AI tools and, consequently, the development of teaching practices and the overall educational process.
Authors
- A. Saad
- Shaimaa Hamouda Elharon
Institutions
- National Institute for Education (SK)
- Methodist Hospital (US)
Publication Details
- Journal
- International Journal of Recent Education Research.
- Published
- 2025-12-01
- DOI
- https://doi.org/10.21608/ijrer.2025.393502.1023
- Primary Topic
- Online Learning and Analytics
- Type
- article
- Field-Weighted Citation Impact
- 0.00