AI-Driven Assessment of Brain Dominance: Classifying CBSE Students as Left-, Right-, or Whole-Brain Learner

Abstract

Introduction: The concept of brain dominance (left, right, or whole) is a significant factor in understanding individual learning styles and academic achievement. Traditional assessment methods, such as self-report questionnaires, are limited by subjectivity and an inability to capture dynamic cognitive processes. This study addresses the need for an objective, scalable tool to classify brain dominance, specifically within the diverse CBSE student population in India, by leveraging the power of Artificial Intelligence (AI). The primary objective was to develop and validate an AI-driven model to classify CBSE students as left-, right, or whole-brain learners. Specific objectives included: To determine whether a student from a CBSE school population is left-, right-, or whole-brained dominant. To develop a model for categorizing students as left-, right-, or whole-brained dominant and to recommend activities according to their brain dominance to enhance their dominant brain. A sample of 400 CBSE students (Grades 6 to 8) completed a digital cognitive task battery and standardized questionnaires. The Cognitive Dominance Classification Pipeline (CDCP), a machine learning model based on a Gradient Boosting Classifier , was developed. It was trained on engineered features from task performance (e.g., analytical-to-creative time ratio, logical sequence score) using a consensus ground truth label derived from task performance, self-reports, and teacher assessments. The AI model achieved a high classification accuracy of 91.7%. The distribution of brain dominance in the sample was 42.5% left brain, 35.0% right brain, and 22.5% whole brain. A significant correlation was found with gender, with male students having a greater tendency towards left hemisphere dominance and female students having a greater tendency towards right hemisphere dominance. No significant correlation was found with education level. The study successfully demonstrates that AI can objectively and accurately assess brain dominance, overcoming the limitations of traditional tools. The findings reveal a distinct cognitive landscape among CBSE students and highlight the potential of AI-based diagnostics to inform personalized, equitable and effective pedagogical strategies tailored to individual learning styles.