learning.understanding.cognition.intelligence.data science

Matt Borman

Credentials: Ph.D. Student, Psychology

Research Interests: Semantics in Word Learning

Research mentor: Mark Seidenberg

I’m interested in using computational and behavioral methods to estimate language experience and semantic knowledge, with the goal of exploring how different states of prior knowledge impact learning of new words and concepts. I’m focused on the interaction between one’s background knowledge and the context of a given learning environment. By better understanding this interaction, I hope to contribute insight on questions like:

– When is it most advantageous to focus on learning related concepts and when is it more efficient branch out into new sets of concepts?

– When does contextual variability or contextual consistency greater benefit a learner?

– Why do some learners benefit more from contextual variability?

– How much experience with a word or concept does a learner need in order to generalize their knowledge?

– How can we use our knowledge on these topics to support language and vocabulary growth in development?