Artificial Intelligence in Science Education Research: Current States and Challenges
Gyeong-Geon Lee, Minji Yun, Xiaoming Zhaı, Kent J. Crippen
Abstract
Abstract The recent surge of artificial intelligence (AI) in science education has heightened interest among the NARST community—a curiosity about how technology can transform education that has lasted for decades. Founded in 1928, NARST is an international organization of thousands of members focused on improving science education through research. This growing interest is evidenced by the launch of the Research in Artificial Intelligence-Involved Science Education (RAISE) Research Interest Group in 2022 and the increasing number of AI-related studies presented at NARST conferences. Despite the growth, limited studies have shed light on how the community members integrate AI into science education and the challenges. We systematically reviewed 36 AI-related papers presented at the 2024 NARST conference to address this gap. We found that AI (1) is widely integrated into science education research with ethical considerations, (2) serves to continue the paradigm of science education rather than redefining it, and (3) evolves into a multipurpose, multimodal, and generative tool for research and teaching. The analysis also revealed five major challenges: (1) changes in educational goals, (2) renovating science learning content, (3) complexity of assessment for individualized feedback, (4) teachers’ preparedness and professional development, and (5) bias and equity in STEM education. Consequently, the role of NARST and RAISE RIG members that respond to those challenges is readdressed.