An analysis of science teachers’ use of artificial intelligence in education from a Technological Pedagogical Content Knowledge perspective

Gasangusein I. Ibragimov 1 * , Elena N. Kolomoets 2, Alla A. Filippova 3, Elmira R. Khairullina 4, Natalya Y. Garnova 3, Julia V. Torkunova 5 6
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1 Kazan (Volga region) Federal University, Kazan, RUSSIA
2 Moscow Aviation Institute (National Research University), Moscow, RUSSIA
3 Sechenov First Moscow State Medical University (Sechenov University), Moscow, RUSSIA
4 Kazan National Research Technological University, Kazan, RUSSIA
5 Kazan State Power Engineering University, Kazan, RUSSIA
6 Sochi State University, Sochi, RUSSIA
* Corresponding Author
Online Journal of Communication and Media Technologies, Volume 15, Issue 3, Article No: e202523. https://doi.org/10.30935/ojcmt/16594
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ABSTRACT

The aim of the study is to evaluate science teachers’ use of artificial intelligence (AI) within the context of Technological Pedagogical Content Knowledge (TPACK). The study examines teachers’ AI Competence Self-Efficacy and their TPACK according to demographic variables, investigates the relationship between these two variables, and determines the predictive effect of AI competence self-efficacy on TPACK. Quantitative research method was used at research and relational survey model used. The sample of the study consists of 296 science teachers in 13 different middle schools during the February–March 2025 period. Data were collected by Teacher AI Competency Self-Efficacy Scale (TAICS) and the AI Technological Pedagogical Content Knowledge (AI-TPACK) Scale. For data analysis, Independent Samples t-test, ANOVA, Pearson Correlation Analysis, and Structural Equation Modeling (SEM) were used. According to the results, the overall mean scores of both AI-TPACK and TAICS were found to be medium level. According to gender analysis, female teachers scored higher than male teachers in the sub-dimensions of both AI-TPACK and TAICS. Teachers with fewer years of experience had higher scores in the technology-related components of AI-TPACK, whereas those with more teaching experience had higher averages in dimensions such as Pedagogical Knowledge (PK), Content Knowledge (CK), and Pedagogical Content Knowledge (PCK). In terms of TAICS, teachers with lower experience also had higher average scores. Overall, there were positive and significant correlations between the dimensions of TAICS and AI-TPACK. Finally, the TAICS construct significantly predicted AI-TPACK. Based on these findings, recommendations were given for future research to focus on the active use of AI within the TPACK framework and to include qualitative research designs aimed at exploring the challenges encountered in the process of AI integration.
Keywords: artificial intelligence in education, science teachers, technological pedagogical content knowledge, AI pedagogy, technology integration

CITATION

Ibragimov, G. I., Kolomoets, E. N., Filippova, A. A., Khairullina, E. R., Garnova, N. Y., & Torkunova, J. V. (2025). An analysis of science teachers’ use of artificial intelligence in education from a Technological Pedagogical Content Knowledge perspective. Online Journal of Communication and Media Technologies, 15(3), e202523. https://doi.org/10.30935/ojcmt/16594

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