Integrating AI into Inquiry-Based Learning and Argumentation in Elementary Science Education
Integrating AI into Inquiry-Based Learning and Argumentation in Elementary Science Education
Sustainable Development Goals
Abstract/Objectives
This project aims to integrate Generative Artificial Intelligence (GenAI) into elementary school science inquiry and argumentation to enhance students’ scientific literacy and critical thinking skills. By designing AI-supported, baseball-themed game-based learning activities, students will use AI to generate questions, analyze data, construct hypotheses, and revise their arguments while deepening conceptual understanding and knowledge construction through situated tasks. The project focuses on cultivating problem-solving abilities, strengthening the structured expression of scientific argumentation, and constructing an AI-supported learning environment that examines the pedagogical potential and implementation model of game-based learning and baseball contexts in science inquiry.
Results/Contributions
This project successfully developed an instructional model that integrates Generative Artificial Intelligence (GenAI) with a baseball-themed context to support inquiry and argumentation in elementary school science. A comprehensive set of teaching materials, AI-supported learning procedures, and assessment mechanisms was established. Through game-based learning scenarios situated in authentic and motivating contexts, students engaged in question generation, hypothesis construction, evidence collection, and argument revision, leading to noticeable improvements in their scientific inquiry skills and the structural quality of their arguments.
Keywords
Artificial intelligence Scientific argumentation, scientific inquiry, curriculum and pedagogy
References
Contact Information
林裕仁
linyuren@mx.nthu.edu.tw