OPTIMIZING TEACHING STRATEGIES IN THE AGE OF AI A QUANTITATIVE ANALYSIS OF AI ADOPTION IN EDUCATION

Abstract

AI has disrupted traditional educational practices by introducing exciting tools that foster learning outcomes, customization of instructions, and various administrative conveniences. Though the integration of AI tools in education has been growing, questions of its practical use efficacy and constant adoption persist. This work addresses a critical gap in knowledge about how AI affects teaching practices and student outcomes. This study applies multiple linear regression to assess how AI usage, engagement scores, and privacy concerns affect academic performance. Using quantitative methods such as multiple linear regression, the study analyses data collected from teachers to ascertain the relationship between the use of AI tools, study habits, concerns about privacy, engagement, and academic performance. The analysis showed that AI tool usage is significantly correlated with academic performance (β = 15.6, R² = 0.62, p < 0.001) toward confirming that the introduction of AI tools in a thoughtful manner would energize teaching and has a positive effect on student achievement. Adoption comes with a different set of challenges. Initiatives that can agencies such as teacher professional development programs, ethical governance frameworks for AI application, and smart investment in technological infrastructure for under-resourced institutions are needed to tackle barriers.