Abstract
This chapter explores the integration of Artificial Intelligence (AI) into science education, emphasizing its theoretical foundations and pedagogical potential. It highlights the importance of interdisciplinarity in fostering a more dynamic and personalized learning experience. Furthermore, it examines the ethical and epistemological challenges associated with this transformation in the educational context. The research adopted a qualitative approach, essential for an in-depth exploration of the relationship between Artificial Intelligence (AI) and science education. The methodology involved a literature review, drawing from sources categorized into three groups: (1) sources on AI, (2) sources on science education, and (3) sources discussing the intersection of AI and science education. This approach enabled a detailed analysis of the pedagogical, epistemological, and ethical implications of this integration. The overarching aim of this study is to explore the foundations and possibilities of integrating Artificial Intelligence (AI) into science education, with a focus on promoting interdisciplinarity while addressing the ethical and epistemological challenges inherent in this pedagogical process. The findings reveal that AI can serve as a powerful tool to transform science education, particularly by fostering more personalized and interactive learning environments that enhance interdisciplinarity and critical skill development among students. However, the study also underscores significant challenges in implementing AI in science education, including ensuring equity, transparency, and data privacy, as well as addressing epistemological issues related to the redefinition of knowledge and the educator's role.
DOI:https://doi.org/10.56238/sevened2024.037-027