Mapping Preservice Teachers’ AI Competence in Higher Education: A Critical Scoping Review (2015–2025)

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Authors: Ruslina Irianty
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Abstract

This registration documents a critical scoping review of empirical research on preservice teachers’ AI-related competence in higher education and initial teacher education (ITE) programmes between 2015 and 2025. The project follows the PRISMA Extension for Scoping Reviews (PRISMA-ScR) to systematically identify, screen, and synthesise studies from Scopus and Web of Science that examine how preservice teachers’ AI literacy, AI readiness, AI‑TPACK/Intelligent‑TPACK, and Generative AI practices are conceptualised and assessed. ​ The review has three main aims: to map the contextual and methodological landscape of this literature (countries, disciplines, research designs); to identify and compare the dominant competence constructs and reported levels of preservice teachers’ AI competence; and to analyse the instruments and assessment approaches used, including their psychometric and methodological strengths and limitations. ​ Beyond cataloguing existing work, the review adopts a critical stance on current reliance on self-report measures, the paradox between high perceived readiness and limited technical/pedagogical integration skills, and the implications of infrastructure inequalities and Global South contexts for defining and measuring AI competence. The expected outcomes include: ​ a structured map of 2023–2025 empirical studies on preservice teachers’ AI competence; a set of four thematic clusters (AI literacy foundations, readiness/intention/anxiety, Intelligent‑TPACK, and GenAI-based interventions); and a set of design principles for future AI competence frameworks and assessment tools in teacher education (e.g., integrating performance-based tasks, learning analytics, and context-sensitive indicators). ​ The registration covers the search strategy, eligibility criteria, screening decisions, data extraction schema, and planned analytic approach, and will be linked to anonymised extraction matrices and, when available, a preprint of the full manuscript.

Fields of Study & Subjects

Artificial Intelligence in Education Digital literacy in education Teacher Education and Leadership Studies

Publication details

Journal / source
Open Science Framework
Publication date
1 January 2026