Exploring the interplay between AI literacy of pre-service teachers and their attitudes about physics in the development of physics-based assessment objectives

The impressive capabilities of Generative Artificial Intelligence (AI) have promised a huge potential to transform classroom practices, particularly assessments. This talk investigates how pre-service elementary teachers develop and refine their practice-oriented physics assessment objectives (AO) using AI. We further investigate their approaches towards engaging with AOs with respect to their attitudes about physics and their knowledge of AI. The study employs multiple surveys to assess teachers' attitudes about physics and their current understanding of AI, exploring how these elements shape their skills and abilities in prompting AI models effectively. Furthermore, this work analyzes the capabilities and constraints teachers face when developing practice-oriented assessment objectives and their perceived differences between self-generated and AI-generated objectives. This work contributes to the existing efforts in equipping future teachers to effectively leverage emerging technologies in teaching science.