Optimizing STEM instructional strategies using AI and deep learning: A study of elementary school students

With the rapid development of artificial intelligence and deep learning technology, its application potential in the field of education has gradually attracted attention. Especially in STEM education, there are a lot of opportunities for optimization and innovation. This study aims to explore how these advanced technologies can be used to optimize STEM instructional strategies at the elementary school level. To this end, we constructed a data set containing 1,000 pieces of virtual data, involving students’ basic information, learning style, learning process, interactive behavior, feedback and evaluation, etc. Through in-depth data analysis and application of deep learning models, we identified a series of key factors that played a decisive role in optimizing STEM teaching strategies. This study provides not only new insights for academics, but also practical teaching strategies and recommendations for educators. Copyright © 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG.