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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2606.00034 |
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| _version_ | 1866918532301717504 |
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| author | Nelson, Uloma Egondu Gallegos, Gil |
| author_facet | Nelson, Uloma Egondu Gallegos, Gil |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2606_00034 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Artificial intelligence as a real game to enlighten science education for disabled students in rural New Mexico Nelson, Uloma Egondu Gallegos, Gil Computers and Society 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. |
| title | Artificial intelligence as a real game to enlighten science education for disabled students in rural New Mexico |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2606.00034 |