Document Type : Original Research Paper
Authors
Department of Educational Sciences, Faculty of Humanities, Bu-Ali Sina University, Hamadan, Iran
Abstract
Background and Objectives: In the digital age, teachers, as the pillars of the educational system, face emerging challenges in integrating modern technologies into teaching practices. Despite the emphasis of upstream documents and global standards on the necessity of improving teachers’ professional performance, evidence suggests that many are still unable to effectively utilize smart tools. The emergence of Artificial Intelligence (AI) as a transformative technology necessitates the formation of a new type of literacy among teachers; a literacy that goes beyond simple technical skills and includes the ability to understand, evaluate, and creatively use AI in the teaching-learning process. However, the main issue is whether possessing theoretical knowledge about AI alone can directly lead to improved professional performance, or if this effect requires executive mediators. Previous studies have indicated a gap between theoretical knowledge and educational practice, which might be bridged by the variable of 'technology integration.' Accordingly, the main objective of this study is to investigate the relationship between AI literacy and the professional performance of primary school teachers, emphasizing the mediating role of technology integration skills (based on the SAMR model), to provide a model for enhancing the quality of education in schools.
Methods: The present study is applied in terms of purpose and quantitative, descriptive-correlational, based on structural equation modeling in terms of nature. The statistical population included all teachers working in primary schools of Kabudarahang County in the academic year 2025-2026, totaling 600 individuals. The sample size was estimated at 234 using the Krejcie and Morgan table, and sampling was conducted using the convenience method; 280 questionnaires were distributed and, after preliminary screening, 235 complete questionnaires were collected and analyzed. Data were collected using three instruments: the AI Literacy Questionnaire, the Teachers’ Professional Performance Questionnaire, and a researcher-made Technology Integration Skills Questionnaire based on the SAMR model. Content validity was confirmed by subject-matter experts and further supported by confirmatory factor analysis, while reliability was established using Cronbach’s alpha (0.93, 0.93, and 0.95 for AI literacy, professional performance, and technology integration, respectively). Data analysis was performed using SPSS and SmartPLS statistical software through one-sample t-tests, Pearson correlation coefficient, and structural equation modeling.
Findings: Descriptive results showed that the mean scores of AI literacy (2.65) and technology integration skills (2.83) were lower than the average, while the mean of professional performance (3.76) was higher than the average. In the inferential findings section, the results of structural equation modeling indicated that the direct relationship between AI literacy and teachers’ professional performance was not significant (path coefficient 0.102, t-statistic 1.381). However, AI literacy had a strong positive direct effect on technology integration skills (path coefficient 0.489, t-statistic 9.778). Also, technology integration skills showed a significant direct effect on teachers’ professional performance (path coefficient 0.402, t-statistic 7.014). The most important finding of the research was the confirmation of the full mediating role of the 'technology integration skills' variable in the relationship between AI literacy and professional performance (indirect path coefficient 0.197, t-statistic 5.658). The coefficient of determination of the model also showed that approximately 21% of the changes in professional performance are explained by the model variables.
Background and Objectives: In the digital age, teachers, as the pillars of the educational system, face emerging challenges in integrating modern technologies into teaching practices. Despite the emphasis of upstream documents and global standards on the necessity of improving teachers’ professional performance, evidence suggests that many are still unable to effectively utilize smart tools. The emergence of Artificial Intelligence (AI) as a transformative technology necessitates the formation of a new type of literacy among teachers; a literacy that goes beyond simple technical skills and includes the ability to understand, evaluate, and creatively use AI in the teaching-learning process. However, the main issue is whether possessing theoretical knowledge about AI alone can directly lead to improved professional performance, or if this effect requires executive mediators. Previous studies have indicated a gap between theoretical knowledge and educational practice, which might be bridged by the variable of 'technology integration.' Accordingly, the main objective of this study is to investigate the relationship between AI literacy and the professional performance of primary school teachers, emphasizing the mediating role of technology integration skills (based on the SAMR model), to provide a model for enhancing the quality of education in schools.
Methods: The present study is applied in terms of purpose and quantitative, descriptive-correlational, based on structural equation modeling in terms of nature. The statistical population included all teachers working in primary schools of Kabudarahang County in the academic year 2025-2026, totaling 600 individuals. The sample size was estimated at 234 using the Krejcie and Morgan table, and sampling was conducted using the convenience method; 280 questionnaires were distributed and, after preliminary screening, 235 complete questionnaires were collected and analyzed. Data were collected using three instruments: the AI Literacy Questionnaire, the Teachers’ Professional Performance Questionnaire, and a researcher-made Technology Integration Skills Questionnaire based on the SAMR model. Content validity was confirmed by subject-matter experts and further supported by confirmatory factor analysis, while reliability was established using Cronbach’s alpha (0.93, 0.93, and 0.95 for AI literacy, professional performance, and technology integration, respectively). Data analysis was performed using SPSS and SmartPLS statistical software through one-sample t-tests, Pearson correlation coefficient, and structural equation modeling.
Findings: Descriptive results showed that the mean scores of AI literacy (2.65) and technology integration skills (2.83) were lower than the average, while the mean of professional performance (3.76) was higher than the average. In the inferential findings section, the results of structural equation modeling indicated that the direct relationship between AI literacy and teachers’ professional performance was not significant (path coefficient 0.102, t-statistic 1.381). However, AI literacy had a strong positive direct effect on technology integration skills (path coefficient 0.489, t-statistic 9.778). Also, technology integration skills showed a significant direct effect on teachers’ professional performance (path coefficient 0.402, t-statistic 7.014). The most important finding of the research was the confirmation of the full mediating role of the 'technology integration skills' variable in the relationship between AI literacy and professional performance (indirect path coefficient 0.197, t-statistic 5.658). The coefficient of determination of the model also showed that approximately 21% of the changes in professional performance are explained by the model variables.
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© 2026 The Author(s). This is an open-access article distributed under the terms and conditions of the Creative Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/)
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