Computational Psychometrics: AI-Driven Insights into Learner Behavior
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Abstract
This paper introduces a novel approach to computational psychometrics, leveraging AI and machine learning to analyze educational behavior in learners. By integrating behavioral data with psychometric models, the study identifies patterns that correlate with learning outcomes. The paper presents a comprehensive analysis of datasets, comparing traditional psychometric methods with AI-enhanced approaches. Results demonstrate significant improvements in predictive accuracy and insights into cognitive and emotional aspects of learning. The findings have implications for personalized education and adaptive learning systems.
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References
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