Designing an Artificial Intelligence Model for School Management in Iraq

Abstract

Objective: This study aimed to design an artificial intelligence model for school management in Iraq.

Methodology: This qualitative study employed grounded theory as its research method. Data was collected through semi-structured interviews with 15 experts. The research validity was confirmed by both the interviewees and expert faculty. The research reliability was obtained using the intra-rater agreement method with a coefficient of 66%. For data analysis, the constant comparative method was used in three stages: open coding, axial coding, and selective coding.

Findings: The analysis of the interviews yielded 116 key concepts, categorized into 32 categories, and 16 main classes under six dimensions. The main classes included technology infrastructure, human resources, creation of intelligent educational content (causal conditions), advanced technology in education, cybersecurity (core phenomenon), policies and regulations, organizational factors (contextual conditions), technological challenges, and security and cultural barriers (intervening conditions), improving communication infrastructure, enhancing educational skills and reducing skill gaps (strategies), improving educational quality, efficiency of school management, data-driven feedback for students, and integration of educational assessment (consequences).

Conclusion: The application of artificial intelligence in school management in Iraq requires the development of technological infrastructure and the enhancement of educational skills. Despite technological challenges and security and cultural barriers, the effective use of artificial intelligence can improve the quality of education and the efficiency of school management.