Welcome to the Learning Analytics & Psychology in Education Lab (LAPeL)!
Our aim is to help ensure that digital technologies can be used to promote equitable outcomes for underserved populations.
We use big data generated in digital learning environments to help design, build, and evaluate technologies that support learning in various educational contexts.
Educational Data Science
Data science techniques, such as natural language processing (NLP), enable us to study various phenomena that potentially impact learning and/or learners at scale.
Visualizing Learning Data
Data driven educational insights are often communicated through visualizations. Our lab studies how visualizations can impact learning and motivation.
Keeping to our roots in psychology, we also design studies focused on refuting various misconceptions that may impact on policy, teaching, and learning.
Learn more about the members of the Learning Analytics and Psychology Lab
Urban Education Policy