Model of Formation of Digital Competences of Future Teachers in the Conditions of Integration of E-Learning and Artificial Intelligence Technologies

Abstract

The effect of an artificial intelligence (AI) integrated instructional model in developing the digital competencies of future teachers at Ualikhanov University, Kazakhstan, is investigated in the paper. A mixed-methods approach (experimental and qualitative) was employed in the study. The study included a sample of 210 students in their 3rd and 4th years of pedagogical specialties. To evaluate an AI-integrated e-learning model with the use of tools such as DigCompEdu, an AI Literacy Scale a 12-week pre-test/post-test control group design was implemented in the study as well as an EdTech Self-Efficacy Questionnaire. Data were analysed using t-tests, ANCOVA, effect size measures, correlation analyses, and regression models. The results demonstrated that the difference in mean scores between the experimental group (M = 4.14, SD = 0.40) and the control group (M = 3.08, SD = 0.44) was statistically significant (P< 0.05), indicating that the AI-integrated model intervention had a substantial positive impact on students’ overall digital competencies. Thus, AI literacy is the strongest predictor of digital competence (β =0.43, p <.01). The qualitative data resulted in six themes: autonomy, critical thinking, ethics, and creativity, which confirmed that competence development extended beyond technical skill. The study concluded that an AI-integrated e-learning model significantly improved students’ (future teachers) digital competence. Policymakers and institutions should incorporate AI literacy, given its strong predictive power, into teacher education and training programs.