Investigating science teachers’ experiences of generative AI in science teaching and learning from a GenAI-TPACK perspective

This study examines how science teachers report using generative artificial intelligence (GenAI) tools in their classrooms. It employs an interpretivist, qualitative design using semi-structured interviews with twenty secondary science teachers (1–11 years’ experience) on temporary leave while enrolled in Master’s courses at a London university, all of whom had had exposure to GenAI while teaching science to school students. Findings reveal that participants reported using GenAI tools to do such things as generate inquiry prompts, scaffold experiments, and create personalised quizzes for science lessons, all aligned with Technological Pedagogical Content Knowledge (TPACK) principles. Confidence in GenAI varied: teachers felt more secure using GenAI privately for lesson planning than when using it directly with their students. They were confident about GenAI’s future potential but less so about currently applying GenAI in their classes. Many reported becoming more confident after professional development. Most of the teachers had considerable awareness of ethical issues around GenAI, but they sought clearer guidance on handling these issues in lessons. This research contributes to understanding how teachers can navigate the complex interplay of technology, pedagogy and subject content to foster critical and ethical scientific learning with GenAI.

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Publication Details

Journal
International Journal of Science Education
Published
2026-09-18
DOI
https://doi.org/10.1080/09500693.2026.2733687
Primary Topic
Science Education and Pedagogy
Type
article
Field-Weighted Citation Impact
0.00
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article

Investigating science teachers’ experiences of generative AI in science teaching and learning from a GenAI-TPACK perspective

Michael Reiß, Xiang Zhang
International Journal of Science Education
Science Education and Pedagogy
article

Investigating science teachers’ experiences of generative AI in science teaching and learning from a GenAI-TPACK perspective

Michael Reiß, Xiang Zhang
article en

Abstract

This study examines how science teachers report using generative artificial intelligence (GenAI) tools in their classrooms. It employs an interpretivist, qualitative design using semi-structured interviews with twenty secondary science teachers (1–11 years’ experience) on temporary leave while enrolled in Master’s courses at a London university, all of whom had had exposure to GenAI while teaching science to school students. Findings reveal that participants reported using GenAI tools to do such things as generate inquiry prompts, scaffold experiments, and create personalised quizzes for science lessons, all aligned with Technological Pedagogical Content Knowledge (TPACK) principles. Confidence in GenAI varied: teachers felt more secure using GenAI privately for lesson planning than when using it directly with their students. They were confident about GenAI’s future potential but less so about currently applying GenAI in their classes. Many reported becoming more confident after professional development. Most of the teachers had considerable awareness of ethical issues around GenAI, but they sought clearer guidance on handling these issues in lessons. This research contributes to understanding how teachers can navigate the complex interplay of technology, pedagogy and subject content to foster critical and ethical scientific learning with GenAI.

International Journal of Science Education
University of Cambridge (GB), University College London (GB)
Quality Education
Openalex Percentile: Top 3%
Science Education and Pedagogy
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