CHALKBOARDS TO CHATBOTS EVOLUTION OF EQUITABLE EDUCATION IN THE AGE OF AI
DOI:
https://doi.org/10.29121/shodhai.v3.i1.2026.68Keywords:
Education Equity, Ai-Enhanced Learning, Monte Carlo Simulation, Adaptive Learning, Ai In EducationAbstract
Educational inequality is still one of the hardest problems schools face. This is especially evident in places with limited access to good teachers or learning support. This study looks at the use of artificial intelligence within education for a more balanced and fair access to quality of learning. Using a Monte Carlo simulation, we modeled thousands of classroom situations for teacher skill, student readiness, and AI-based support to shape learning outcomes. Teacher quality changed with socioeconomic conditions, while AI worked as an extra layer of help in teaching. Across 10,000 simulated classrooms, students were improved when AI tools were part of the process. Average scores rose by about 40%, and the biggest improvements came from students in low-income settings. Most notable changes were observed with AI closing the gap between high- and low socioeconomic groups. In most extreme cases the learning gap shrank by more than 40%. This is an important result that demonstrates the feasibility of AI to close the learning gap where resources are thin. Results varied when the use of AI wasn’t steady, which demonstrates that persistence and proper use of the tools is required. This study demonstrates that AI can amplify but not fully replace the teacher and close the learning gaps between high and low socioeconomic layers of society.
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Copyright (c) 2026 Andre Slonopas, Adam Beatty, Edward Olbrych, Harry Cooper, Elliott Lynn
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