Integration of AI in STEM Education: A Systematic Review

Abstract

This systematic literature review examines the integration of Artificial Intelligence into STEM education, motivated by the need to understand how AI tools and methods are transforming educational landscapes. As AI technologies evolve rapidly, their potential to enhance teaching and learning within STEM disciplines warrants thorough investigation. This review delves into the applications of machine learning, deep learning, natural language processing, and reinforcement learning across various educational levels, drawing on 19 relevant studies identified through comprehensive database searches. The analysis reveals that AI significantly enriches teaching methods and student outcomes by offering innovative tools and methods for content generation, recognition, prediction, skill assistance, and evaluation, with a strong focus on enhancing mathematics education at the primary level. However, the limited number of studies included, and the absence of a meta-analysis highlight the need for ongoing research. Future studies are encouraged to expand the scope of literature searches and employ quantitative synthesis techniques to assess the impact of AI more robustly in STEM education. This review sets the stage for future explorations that could profoundly influence educational strategies and policies.