Perception vs. Performance: Unpacking Pre-Service EFL Teachers' TPACK Gaps in AI-Enhanced Learning Design

Sulastri Manurung(1), Sri Setyarini(2), Susi Septaviana Rakhmawati(3),

DOI: https://doi.org/10.46843/jpm.v4i3.505


(1) Universitas Pendidikan Indonesia, Indonesia
(2) Universitas Pendidikan Indonesia, Indonesia
(3) Universitas Pendidikan Indonesia, Indonesia

Abstract

This study investigated how?pre?service EFL teachers' perceived Pedagogical Content Knowledge (PCK), Technological Content Knowledge?(TCK), and Technological?Pedagogical Knowledge?(TPK) relate to their demonstrated TPACK performance when designing AI?enhanced lessons. It employed a correlational research design with multiple linear regression. Seventy?seven Indonesian pre?service teachers who had used AI-enhanced tools during practicum completed perceived PCK, TCK, and TPK questionnaires. Actual TPACK competence was scored with a performance rubric (lesson plans, supporting documents, and teaching observations). Descriptively, participants reported the most substantial confidence in PCK (M?=?3.61, SD?=?0.54, 5?point scale), while TCK (M?=?3.00,?SD?=?1.14) and TPK (M?=?3.02,?SD?=?0.50) were moderate. Performance data showed that, on average, teachers achieved 70?percent of the maximum TPACK score, indicating adequate yet improvable integration of technology, pedagogy, and content. Multiple?regression analysis revealed that perceived PCK, TCK, and TPK together did not significantly predict demonstrated TPACK (F?(3,73) = 1.98,?p?=.125). These findings suggest a disconnect between what teachers think they know and what they can enact. It contributes to teacher knowledge research by highlighting the gap between self-perceived and demonstrated competence, underscoring the need for practice-oriented training that explicitly links AI tool use to pedagogical and content goals.

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