The Contribution That Utilizing Generative AI for Problem Posing Makes to Pre-Service High School Mathematics Teachers' TPACK

Abstract

Fifteen pre-service mathematics teachers studying in a teachers college participated in a unique program entitled "From high-tech to teaching" as part of a specialization program for teaching advanced secondary school mathematics. During the course, they solved various mathematical problems and then were asked to pose additional problems and upgrade them to meet precise educational goals by furnishing "prompts" to a generative AI environment (ChatGPT) and refining them as necessary according to predefined steps. To understand how this process contributed to the pre-service teachers' body of technological, pedagogical, and content knowledge (TPACK), they were asked to respond to a questionnaire (ten Likert-type statements; six open-ended questions).The findings indicate that posing problems in an AI environment increased their technological knowledge vis-à-vis the advantages of the environment itself and how to generate effective prompts to obtain relevant responses. They also became aware of some disadvantages. With respect to their technological-pedagogical knowledge, integrating AI at challenging pedagogical junctures (e.g., tailoring problems to students' individual needs) provided diverse pedagogical ideas. Although AI involves some challenges (e.g., all suggestions must be critically examined), overall they expressed satisfaction with the concept and indicated they would use it in the future.