AI-TPACK in Formal Education: A Qualitative Systematic Review
TL;DR
This qualitative systematic review synthesizes empirical research that uses the TPACK framework to examine AI integration in formal education and indicates substantial variation in AI-TPACK operationalization, emphasizing the need for practice-proximal evidence and context-sensitive support.
Abstract
This qualitative systematic review synthesizes empirical research that uses the TPACK framework to examine AI integration in formal education. PRISMA-guided procedures were applied to Scopus-indexed, peer-reviewed journal articles published in English between 2021 and 2026. The search yielded 278 records; after eligibility checks and manual screening, 116 empirical studies were included for full-text analysis. Deductive coding, aligned with TPACK components, was combined with inductive reflexive thematic analysis to identify patterns in conceptualization and enactment. Results indicate substantial variation in AI-TPACK operationalization, ranging from psychometric self-report measures and predictive models to professional learning accounts, practice-oriented design tasks, and critiques of traditional instruments. Reported challenges extend beyond technical proficiency to pedagogical alignment, ethical judgment and accountability, assessment and feedback validity, and institutional policy constraints. A recurring theme is divergence between perceived competence and enacted classroom use, emphasizing the need for practice-proximal evidence and context-sensitive support. These insights guide future research priorities.