Cognitive architecture lab
The Cognitive Architecture Lab takes a multidisciplinary approach to the fundamental mechanisms that support high-level cognition. We are currently addressing four research goals:
- Undertaking behavioral experiments investigating how people understand abstract mathematical concepts such as irrational numbers, and also developing mesaures of mathematical insight, mathematical intuition, and other abilities that potentially predict success in STEM disciplines in college
- Investigating the cognitive and neural mechanisms underlying language comprehension through the development of computational models of word and sentence comprehension that explain behavioral and brain imaging data in normal adults neuropsychological patients, and people with autism
- Conducting lab- and classroom-based studies of how adults and children solve problems, think spatially, and reason scientifically
- Applying findings from neuroscience and cognitive science to improve instruction in classrooms and in online environments
- Experimental studies of abstract mathematical thinking
- Neurocognitive models of sentence comprehension and spatial problem solving
- Memory mechanisms supporting learning from text
- Application of neuroscience findings to educational contexts
- Lab director
- Associate professor of educational psychology in the psychological foundations of educcation program
- Emphasis: Learning and cognition/educational technologies
Soo-hyun Im Ph.D. student, psychological foundations: learning and cognition/educational technologies
Soo-hyun is investigating how (1) pre-service teachers and (2) the general population reason about the educational relevance of neuroscience findings and how their reasoning can be improved by coursework in educational psychology. He is also developing instructional sequences to build the arithmetic fluency of elementary school children.
Erik Anderson M.A. student, psychological foundations: learning and cognition/educational technologies
Erik is developing semantic ontologies for expressing the assessment history of individual students over an entire school year.
Astrid Schmied Ph.D. student, psychological foundations: learning and cognition/educational technologies
Astrid is investigating how (1) pre-service teachers, (2) undergraduates majoring in STEM fields, and (3) the general population reason about the ethics of applying neuroscience findings to improve educational outcomes.
Purav Patel Ph.D. student, psychological foundations: learning and cognition/educational technologies
Purav is investigating the mental representation of irrational numbers (such the square root of 2). He is also developing instructional sequences for teaching algebraic properties such as associativity, identity, inverse, and commutativity.
Kasey Michel Ph.D. student, psychological foundations: learning and cognition/educational technologies
Kasey's research focuses on educational neuroscience.
Varma, S. (2014). The subjective meaning of cognitive architecture: A Marrian analysis. Frontiers in Psychology, 5, e440.
Varma, S., & Karl, S. R. (2013). Understanding decimal proportions: Discrete representations, parallel access, and privileged processing of zero. Cognitive Psychology, 66, 283-301.
Dubinsky, J. M., Roehrig, G., & Varma, S. (2013). Infusing neuroscience into teacher training. Educational Researcher, 42, 317-329. [Featured as an Editor's Choice (“When Neuroscience Guides Education”) in Science, 342, 671.]