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<p>This study aims to examine the determinants of pre-service teachers’ perception of competences and Intelligent Ethical Technological Pedagogical Content Knowledge (IETPACK) in the context of artificial intelligence (AI) adoption in education. It explores how various factors known to influence the acceptance of AI technology, such as perceived usefulness, perceived ease of use, social influence, AI for social good, AI anxiety, and AI literacy, are linked to and affect competences, as well as the perceptions of IETPACK. Data were collected from 228 Serbian pre-service teachers using self-report questionnaires to test the developed model. Structural equation modeling revealed that the proposed model had a good fit to the data, and significantly explained pre-service teachers’ competences and IETPACK, accounting for 55.3% and 55.5% of the variance, respectively. Perceived usefulness, perceived ease of use, IETPACK, AI for social good, and AI literacy were identified as key factors directly influencing pre-service teachers’ perceptions of their AI competency. On the other hand, AI literacy and subjective norms have a strong direct influence on IETPACK. The study delves into the teaching implications aimed at augmenting competences and IETPACK.</p>

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Unpacking the relationship between AI competences, intelligent ethical TPACK, and factors influencing AI adoption in pre-service teachers: A comprehensive model

  • 期刊论文

  • 发表日期：

    2025年10月8日

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  • Verica Milutinović

摘要

This study aims to examine the determinants of pre-service teachers’ perception of competences and Intelligent Ethical Technological Pedagogical Content Knowledge (IETPACK) in the context of artificial intelligence (AI) adoption in education. It explores how various factors known to influence the acceptance of AI technology, such as perceived usefulness, perceived ease of use, social influence, AI for social good, AI anxiety, and AI literacy, are linked to and affect competences, as well as the perceptions of IETPACK. Data were collected from 228 Serbian pre-service teachers using self-report questionnaires to test the developed model. Structural equation modeling revealed that the proposed model had a good fit to the data, and significantly explained pre-service teachers’ competences and IETPACK, accounting for 55.3% and 55.5% of the variance, respectively. Perceived usefulness, perceived ease of use, IETPACK, AI for social good, and AI literacy were identified as key factors directly influencing pre-service teachers’ perceptions of their AI competency. On the other hand, AI literacy and subjective norms have a strong direct influence on IETPACK. The study delves into the teaching implications aimed at augmenting competences and IETPACK.