INTEGRATING GENERATIVE AI IN LESSON PLANNING: FUTURE EDUCATORS’ INTELLIGENT TPACK DEVELOPMENT AND ETHICAL PERCEPTIONS

Preservice teachers (PSTs) are entering a profession increasingly shaped by generative artificial intelligence (GenAI), yet teacher education programs have been slow to develop structured, pedagogically grounded frameworks for GenAI integration. Without intentional preparation, PSTs risk either over-reliance on or avoidance of these tools, both of which undermine the effective and ethical use of GenAI tools. This study examined PSTs’ use of GenAI tools in lesson planning, their intention to align GenAI-generated outputs with pedagogical goals, and their critical evaluation of the reliability and ethics of such output. Within this process, the study explored how PSTs develop intelligent technological, pedagogical, and content knowledge (iTPACK) through structured engagement with a TPACK-aligned CustomGPT tool during lesson planning activities. The study employed a convergent parallel mixed-method design. Participants were 37 PSTs enrolled in a technology integration in instruction course in the Spring 2025 semester. Data were collected through pre- and post-intervention surveys, Lesson plans, CustomGPT interaction prompts, written reflections, and focus group discussions. The iTPACK and the Critical Media Literacy frameworks provided the theoretical foundation. Quantitative data from pre- and post-intervention iTPACK surveys were analyzed using paired-sample t-tests and Wilcoxon signed-rank tests alongside Technology Integration Assessment Rubric (TIAR) scores across two lesson plan iterations. Qualitative data included content analysis of interaction prompts, thematic analysis of written reflections, and focus group discussions. Quantitative findings revealed statistically significant gains across all five iTPACK subscales. Rubric scores for lesson plans showed modest changes, suggesting self-perceived knowledge gains outpaced demonstrated changes in lesson plan quality. These results were supported by the qualitative analysis of lesson plans, which showed a limited shift in the selection of content-specific technological tools. GenAI helped PSTs manage the logistics of technology integration, but not a solution to real classroom challenges. Qualitative analysis of written reflections and focus group discussions identified that PSTs demonstrated neither uncritical acceptance nor whole rejection, but rather a critically engaged stance characterized by conditional trust, selective adoption, ethical lens, and emerging professional agency. Results from this study shed light on the process of GenAI integration in teacher education, on contexts for its effective use, and on research on AI-related TPACK.