A Study On Ai In Education: Unveiling Student Insights Through Data Analytics

23 May

Authors: Dr Kowsalya.G, Sathya Narayanan B

Abstract: The rapid integration of Artificial Intelligence (AI) tools into academic environments has transformed how students learn and engage with knowledge. This study investigates student perceptions, usage patterns, and concerns regarding AI in education, focusing on the South Zone of Coimbatore District, Tamil Nadu, India. Primary data were collected from 120 students across school, undergraduate, postgraduate, and research scholar levels through a structured self-administered questionnaire and analysed using Percentage Analysis, Weighted Average Mean (WAM), Chi-Square Test, Pearson Correlation, and Simple Ranking Method. Findings reveal that 73.3% of students regularly use AI tools, primarily for assignment preparation (43.3%), with ChatGPT, Grammarly, and YouTube as dominant platforms. WAM analysis confirms positive student attitudes across all attitudinal dimensions, with AI's time-saving ability scoring highest (WM = 4.10). Chi-Square tests confirm significant differences in AI usage across academic levels (χ² = 18.47, p = 0.030) and disciplines (χ² = 21.34, p = 0.006), while a strong positive correlation (r = 0.712) between AI usage and academic performance underscores the value of purposeful AI engagement. Critically, 56.7% of students have never received institutional guidance on AI use, highlighting an urgent policy gap. The study offers evidence-based insights for educators and policymakers to develop balanced, equitable AI integration frameworks for the Indian educational context.

DOI: https://doi.org/10.5281/zenodo.20354394