Latent Profiles of Turkish Pre-Service Teachers’ Attitudes Toward Artificial Intelligence

Abstract

The rapid proliferation of artificial intelligence technologies in educational contexts demands a nuanced understanding of how future educators perceive and position themselves in relation to these tools. This study adopts a person-centred approach to identify latent attitudinal profiles of Turkish pre-service teachers concerning AI integration in education. Utilizing a cross-sectional survey design, data were collected from 529 participants and analysed through Latent Profile Analysis, complemented by confirmatory factor analysis, ANOVA, and chi-square tests. The results uncovered three distinct profiles: Artificial Intelligence (AI)-Confident Advocates, Balanced Readiness, and Low-Readiness Sceptics. Each profile demonstrated unique patterns of AI-related self-efficacy, pedagogical technology engagement, and attitudinal orientation, indicating substantial intra-group variation. While the majority exhibited moderate openness to AI, only a small subgroup reported the confidence and practical readiness necessary for meaningful classroom integration. Notably, demographic predictors such as gender, and programme type did not significantly influence profile membership, whereas academic seniority emerged as a differentiating factor. These findings underscore the limitations of one-size-fits-all approaches in teacher education and highlight the necessity of differentiated, profile-sensitive training models, as pre-service teachers differ in AI confidence and readiness, making uniform training unable to address their diverse learning needs. Furthermore, the study suggests that fostering AI readiness requires not only technical proficiency but also the cultivation of pedagogical confidence and reflective engagement with emerging technologies. By mapping the attitudinal landscape of pre-service teachers, this research offers critical insights for curriculum developers, educational policymakers, and teacher educators seeking to align technological innovation with human-centred pedagogical capacity.

Keywords

• Artificial Intelligence
• pre-service teachers
• latent profile analysis
• teacher readiness
• educational technology

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