Generative Artificial Intelligence Studies and Research Trends in Science Education
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Abstract
This study aims to provide a comprehensive analysis of the application areas and research trends of generative artificial intelligence (GAI) in science education. The objective is to explore how GAI is utilized to enhance educational processes such as knowledge exploration, material production, and student assessment, while also addressing teachers' perceptions and challenges related to its use. A literature review was conducted on 27 articles published between 2021 and 2024 in the Web of Science database. These articles were analyzed descriptively based on their research topics, GAI methods/tools utilized, research contexts, and suggested areas for future studies. The study found that GAI is employed in STEM education to enhance student achievement, support scientific process skills, and aid in understanding complex concepts. Teachers' perceptions of GAI are influenced by knowledge gaps, ethical concerns, and misunderstandings. While educators recognize the benefits of GAI, such as improving instructional practices and engaging students, they also express concerns about information accuracy, risks of plagiarism, and ethical responsibilities. The findings emphasize the importance of teacher guidance in using GAI tools like ChatGPT effectively in educational settings. Additionally, the study highlights the need for adapting GAI tools to instructional contexts to ensure reliable and ethical classroom applications. Future research is recommended to develop strategies for more dependable and ethical use of GAI, as well as to provide comprehensive guidance for educators to maximize its potential in science education.
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