Are They Ready to Teach? Generative AI as a Means to Uncover Pre-Service Science Teachers’ PCK and Enhance Their Preparation Program

Ron Blonder*, Yael Feldman-Maggor, Shelley Rap

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Integrating generative artificial intelligence (GenAI) in pre-service teachers’ education programs offers a transformative opportunity to enhance the pedagogical development of future science educators. This conceptual paper suggests applying the GenAI tool to evaluate pedagogical content knowledge (PCK) among pre-service science teachers. By holding interactive dialogues with GenAI, pre-service teachers engage in lesson planning in a way that reveals their understanding of content, pedagogy, and PCK while facilitating the practical application of theoretical knowledge. Interpretation of these interactions provides insights into teachers-to-be knowledge and skills, enabling personalized learning experiences and targeted program adjustments. The paper underscores the need to equip pre-service teachers with the necessary competencies to utilize GenAI effectively in their future teaching practices. It contributes to the ongoing discourse on technology’s role in teacher preparation programs, highlighting the potential of addressing existing challenges in evaluating and developing teacher knowledge via GenAI. The suggested future research directions aim to further investigate the GenAI usage implications in educational contexts.

Original languageEnglish
JournalJournal of Science Education and Technology
DOIs
Publication statusPublished - 18 Nov 2024

Funding

Open access funding provided by Weizmann Institute of Science

All Science Journal Classification (ASJC) codes

  • Education
  • General Engineering

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