TRANSFORMING DENTAL EDUCATION IN INDIA: AI-DRIVEN PERSONALIZED LEARNING TO ENHANCE COGNITIVE SKILLS AND OVERCOME LANGUAGE BARRIERS

Abstract

Objective: Indian dental education offers challenges in developing cognitive skills and overcoming language barriers with linguistic diversity and unequal resources. Artificial intelligence (AI) based personalized learning, which tailors content to one's needs, has the potential to enhance results. Its efficacy within this context is untested, mostly. This research sought to assess the effectiveness of an AI-based personalized learning intervention on the improvement in cognitive abilities and language skills of undergraduate dental students in India, and also to look into student and faculty attitudes. Materials and Methods: A 12-month mixed-methods randomized controlled trial was carried out in three Indian dental colleges (urban, semi-urban, rural). 200 BDS (Bachelor of Dental Surgery) students (2nd–4th year) were randomized into intervention (n = 100) and control (n = 100) groups; 20 faculty members gave qualitative input. The intervention group employed an AI platform with adaptive, multilingual modules (English, Hindi, regional language) for 6 months, whereas controls were given conventional teaching. Cognitive ability (max 100) and language skills (max 50) were measured pre- and post-intervention with standardized tests. Interviews and focus groups provided thematic qualitative data. Paired/independent t-tests and effect sizes were computed. Results: The intervention group improved markedly compared to controls: cognitive skill scores rose by 15.8 points (vs. 3.6, p < 0.001, Cohen's d = 1.32) and language skills by 9.4 points (vs. 2.4, p < 0.001, Cohen's d = 1.08). Time on task averaged 4.2 hours/week with an 88% task completion rate. Qualitative findings emphasized greater learning and motivation, balanced against technical difficulties (e.g., rural connectivity). Rural students showed slightly smaller gains (cognitive: +13.2, language: +7.8) compared to urban counterparts (+17.5, +10.5). Conclusion: Artificial intelligence-based individualized learning enormously improves cognitive and language skills in Indian dental training, with large acceptability notwithstanding implementation challenges. Personalized interventions can rectify educational inequalities, although rural infrastructural constraints are a cause of concern.