Efficacy of an Intensive Generative AI Professional Development Program on Pedagogical Content Knowledge (AI-PCK) and the Comparative Analysis of Learning Gain between Experienced and Pre-service Teachers

Synthesis: This quasi-experimental study of an intensive 8-hour generative-AI professional development program with 163 teachers and pre-service teachers found significant gains across all five AI-PCK components (overall d = 2.36), with pre-service teachers showing statistically higher learning gains than experienced teachers (p = 0.033).

Key Findings

1. Intensive 8-hour PD, 163 participants. A quasi-experimental pretest-posttest design assessed an intensive 8-hour GenAI professional development program on five core AI-PCK components.

2. Large significant effects. The PD program was significantly effective across all five AI-PCK components (p < 0.001), with the highest effect size in the Rubric Assessment component (d = 2.19) and an overall effect size of d = 2.36.

3. Pre-service teachers gained more. Pre-service teachers demonstrated a statistically higher overall PCK learning gain than experienced teachers (p = 0.033).

4. Design implications. The intensive model is highly efficacious for rapid AI-PCK enhancement, but the differential learning gain highlights the need to integrate AI-PCK components into core teacher-training curricula and to design specialized support.

Implications

This study provides strong evidence that intensive, focused professional development can rapidly build Teacher AI Competency in Generative AI-related pedagogical content knowledge. The very large effect sizes (d = 2.36 overall) support the Research Methods AIED case for structured, short-format training programs in a fast-moving area where teachers urgently need updated skills.

The differential gain favoring Professional Training candidates suggests that embedding AI-PCK into pre-service curricula may be particularly efficient, while experienced teachers may need tailored, specialized support rather than one-size-fits-all PD. This connects directly to Professional Training, Faculty Development, and Professional Training debates about how to upskill educators for AI-integrated teaching.

For Professional Training and institutional Educational Policy AI, the findings argue for systematic rather than ad-hoc AI teacher preparation, and for attention to differentiated learning needs across the teacher-career spectrum.

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Citation

Talebzadeh, H. (2026). Efficacy of an Intensive Generative AI Professional Development Program on Pedagogical Content Knowledge (AI-PCK) and the Comparative Analysis of Learning Gain between Experienced and Pre-service Teachers. EdArXiv preprint.