Exploring Artificial Intelligence’s Role in Enhancing Mathematical Modeling for Science Education Program

This paper examines the potential integration of artificial intelligence (AI) into science education, focusing on mathematical modelling. Particularly in STEM fields, education systems are looking at creative ways to use AI tools to improve teaching and learning as AI gets more ingrained in many different fields. Along with the difficulties in its application, the study looks at how science teachers view artificial intelligence’s influence on students’ problem-solving skills, conceptual understanding, and interaction with mathematical ideas. Using a descriptive survey approach, 150 science teachers responded on carefully crafted questionnaires. Our data analysis used descriptive (mean, standard deviation) and inferential (Pearson correlation) statistical approaches. Results show that teachers mainly see AI as a useful tool for improving mathematical modelling abilities and increasing student involvement. However, obstacles such as poor teacher training, limited access to artificial intelligence technologies, and resistance to technological change hinder its successful adoption. Especially notable were strong correlations found between teaching experience and use of AI tools and between teachers’ opinions and their readiness to include artificial intelligence in their lessons. The study comes to the conclusion that, although artificial intelligence has great potential to revolutionise science education, effective integration depends on strategic investment in infrastructure improvement, teacher professional development, and supportive educational policies. Advice is given on how to enhance AI training courses, change courses to include AI competencies, and support more study on AI uses in learning environments. This study adds to the growing corpus of knowledge on artificial intelligence in education and provides practical advice for encouraging more successful integration of AI into scientific classrooms.