LITERATURE REVIEW ON GENERATIVE ARTIFICIAL INTELLIGENCE IN PHYSICS AND SCIENCE: CHALLENGES, POTENTIAL, AND IMPACTS ON THE LEARNING PROCESS

Abstract

Generative Artificial Intelligence (GenAI) has become established as an emerging technology in education, particularly in physics and science education since 2022, prompting debate about its pedagogical potential and limitations. The relevance of this topic stems from the sensitive and complex nature of incorporating GenAI into fields that require conceptual rigor, critical thinking, and strong teacher mediation. The general objective of this study is to analyze how the academic literature addresses the use of GenAI in the physics and science teaching and learning process between 2022 and 2025, considering its impacts, challenges, and possibilities. Methodologically, a Systematic Literature Review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. A search of the Scopus database resulted in the analysis of seven studies. The findings indicate that GenAI has the potential to support active learning, problem-solving, and methodological innovation, although it continues to face conceptual limitations, risks of superficial use, and technological dependence. The study concludes that the integration of GenAI requires critical pedagogical strategies, appropriate teacher training, and ethical use in order to enhance learning without compromising the quality of education.