Technology and Trust: Psychological Determinants of Generative Artificial Intelligence Adoption in Teaching Practice

Keywords:
Generative Artificial Intelligence, Adoption Gap, Psychological Factors, Trust In AI, AI Anxiety.

Abstract:
Although generative artificial intelligence (AI) systems are now widely available in education, their actual integration into teaching practice remains uneven and largely superficial. This paper addresses the so-called adoption gap and examines the relationship between the technological features of AI systems and teachers’ psychological responses to them. Drawing on a systematic review and thematic synthesis of the recent literature, the analysis isolates three technological dimensions (transparency, reliability, ease of use) and the corresponding psychological constructs (trust, AI anxiety, self-efficacy), and on this basis proposes an integrative analytical model termed the Tech-Psych AI Adoption Framework. The findings indicate that psychological variables operate as key mediators between system characteristics and patterns of use, with the subjective experience of the technology carrying greater predictive weight than its objective performance. The paper concludes that successful AI integration calls for a psychologically informed approach, one that combines system explainability, the cultivation of AI literacy, and systemic support for teachers.

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M. Marković Blagojević, M. Čolović, D. Simonović, “Technology and Trust: Psychological Determinants of Generative Artificial Intelligence Adoption in Teaching Practice,” in Sinteza 2025 - International Scientific Conference on Information Technology, Computer Science, and Data Science, Belgrade, Singidunum University, Serbia, 2026, pp. 40-46. doi:10.15308/Sinteza-2026-40-46

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Marković Blagojević, M., Čolović, M., Simonović, D. (2026). Technology and Trust: Psychological Determinants of Generative Artificial Intelligence Adoption in Teaching Practice. Paper presented at Sinteza 2025 - International Scientific Conference on Information Technology, Computer Science, and Data Science. doi:10.15308/Sinteza-2026-40-46

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