Artificial intelligence as a real game to enlighten science education for disabled students in rural New Mexico
For disabled students in underserved rural areas, AI-driven pedagogy can significantly enhance science education outcomes.
This study applied an AI-based learning intervention to 120 disabled students in rural New Mexico, achieving a 32% improvement in science concept retention, 27% increase in lab performance, and 42% rise in engagement, with high predictive accuracy (R²=0.92).
Artificial Intelligence AI has emerged as a transformative innovation in inclusive science education for disabled learners in rural New Mexico. Using a mixed method design that combined multiple linear regression and an Artificial Neural Network ANN model, this study examined 120 students in grades 6 to 10 and 15 instructors across four rural schools. The AI-based learning intervention predicted student performance with high accuracy R2 equals 0.92, and p less than 0.05. Experimental results showed a 32 percent improvement in science concept retention, a 27 percent increase in laboratory performance, and a 42 percent rise in student engagement following the intervention. These findings demonstrate that AI-driven pedagogy can serve as a transformative equalizer, improving engagement, comprehension, and accessibility for disabled learners. The study concludes that AI is a promising tool for achieving equitable science education in underserved rural settings.