Document Type : Original Research Paper
Authors
Department of Educational Sciences, Faculty of Human Sciences, Bu-Ali Sina University, Hamedan, 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 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 artificial intelligence in the teaching-learning process. However, the main issue is whether possessing theoretical knowledge about artificial intelligence 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 artificial intelligence 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 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 2024-2025, totaling 600 individuals. The sample size was estimated at 234 using the Krejcie and Morgan table, and sampling was conducted using the convenience method, resulting in the collection and analysis of 235 complete questionnaires. Data were collected using three standard instruments: the AI Literacy Questionnaire (Ning, 2025), a researcher-made Technology Integration Skills Questionnaire based on the SAMR model, and the Teachers' Professional Performance Questionnaire (Darandeh, 2010). The validity and reliability of the instruments were confirmed using Cronbach's alpha (0.93, 0.95, and 0.93, 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 very 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.
Conclusion: The findings of the research indicate that artificial intelligence literacy alone and without mediation is not capable of enhancing teachers' professional performance. This result suggests that theoretical knowledge about artificial intelligence leads to improved teaching quality, evaluation, and classroom management only when it passes through the channel of "practical technology integration skills." In other words, technology integration acts as a driving engine that converts cognitive potential (literacy) into actual performance. Given the low level of literacy and integration skills in the studied population, it is suggested that teacher professional development programs move beyond merely focusing on knowledge enhancement and concentrate on practical workshops regarding "how to integrate smart tools into teaching." The main limitation of this study was its conduct in a specific geographical area and the use of self-reporting tools, which warrants caution in generalizing the results.
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