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Computational Learning Technologies & Sciences

CLeaTS

CLeaTS studies and designs computational and AI-enabled technologies for human learning, thinking, and collaboration.

Mission Statement

CLeaTS advances the science and design of computational systems for learning by integrating learning sciences, artificial intelligence, human-computer interaction, data science, and participatory design to understand human learning, build effective and responsible technologies, and expand access to high-quality learning and training opportunities. Our research investigates how computation, AI, and digital technologies interact with human learning, cognition, collaboration, and performance, and how these interactions inform the design of systems to support learning across educational and workplace contexts.

Pillars of Research

CLeaTS brings together research on how people learn with technology, how learning technologies are designed, and where they are used. Our work spans three interconnected areas.

  • Understanding and Designing for Learning

    Computational and theoretical foundations of human-AI learning

    Human-centered design of learning technologies

    Learning analytics, educational data science, and assessment

  • Building Technologies to Support Learning

    Adaptive learning, personalization, and feedback

    Technologies for self-regulated and collaborative learning

  • Learning Across Educational and Workplace Settings
    AI, computing, and STEM education across K-12, higher education, and online learning
     
    AI-supported workplace training, professional development, and upskilling

Leadership

Affiliated Faculty

Associated Centers

CLeaTS is connected to Vanderbilt’s LIVE Learning Innovation Incubator, which brings together researchers, educators, and partners to design, develop, and study innovative technologies and approaches to learning.