Generative AI as the New Frontier in Science Education: A Systematic Review of Web of Science Articles

Abstract

This systematic review study investigated the research on the use of generative artificial intelligence (GenAI) tools in science education. The Web of Science database was screened by study titles and abstracts. In total, 41 peer-reviewed articles were included. The researchers created the coding scheme in light of GenAI use in education and science education literature. Results revealed that with 12 studies, most of the research was conducted in chemistry education. The highest frequency of the intended use was to evaluate GenAI tools' performance in tasks (e.g., solving physics problems), whereas very few studies aimed at enriching science teaching (n = 1). Regarding student-centeredness, only five studies let learners use the technology without any direction, whereas in seven studies, learners' use was guided. Concerning the level of use, in 14 studies, GenAI use was at a replacement level. The assessment was primarily focused on the instructional component in 23 papers. Most of the studies conducted with GenAI tools did not include participants (n = 20). Quantitative methods (n = 17) were preferred over qualitative ones (n = 10). Based on the results, the use of GenAI tools in science education seems to be in its infancy. At this stage, interdisciplinary partnerships between technology and science educators are necessary. In future research, science educators should focus more on using GenAI tools to enrich science instruction (e.g., how to enhance learners' arguments, how GenAI tool use affects learners' argument formation, and how GenAI tools can enrich the history and nature of science instruction).