Research at the lab asks:

  • How do we use technologies in learning to do new things, and not just old things better? 
  • How do we capture the process of learning across multiple modalities, rather than relying on one-time measures?  
  • How do we make sure that AI is designed in a way to benefit all learners? 

Research Focus

Focus 1: AI in Education

We are particularly interested in using AI to practice new, less explicitly supported types of skills, such as disagreeing well, active listening, or multiple source-based reasoning.

Focus 2: ADHD learners

Research investigates the daily experiences of ADHD learners from a learning sciences perspective, gathering multiple sources of data across modalities and temporal scales, to inform support and tool designs. 

Focus 3: Multimodal learning analytics

The lab uses and develops tools and methods for multimodal learning analytics, where multiple sources of data such as eye-trackers, wearables, cameras, transcripts, or digital logs are used to paint a richer picture of the learning process. 

Focus 4: STEM education 

Of particular interest are the emotional and motivational challenges to engagement, or "pain points" of learning that frequently occur for novice Science, Technology, Engineering and Math (STEM) learners. The lab seeks ways to understand and support them. 

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For a list of ongoing projects, please see the projects page.