Adaptive Learning at Scale: A Framework for Personalized Education
Journal of Educational Technology
Research
Advancing the Science of Learning
Our research team explores the intersection of artificial intelligence, cognitive science, and education to create more effective learning experiences.
Research Areas
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Adaptive Learning Systems
Developing AI algorithms that dynamically adjust content difficulty and presentation based on real-time learner performance.
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Learning Analytics
Using data science to understand learning patterns and predict student outcomes for early intervention.
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Personalization Engines
Creating models that match learning content to individual cognitive styles and preferences.
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Natural Language Processing
Building conversational AI tutors that can engage students in natural, educational dialogue.
Recent Publications
Neural Networks for Student Performance Prediction
International Conference on AI in Education
Conversational AI Tutors: Engagement and Effectiveness
Educational Research Review