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Learning & Cognition/Educational Technology M.A. & Ph.D.

Make improvements in education through psychology, science, and technology

As a student in the program, you’ll study the psychological processes critical to education. Research in our program focuses on cognitive and social-emotional development, including high-level cognition and factors shaping and enhancing learning throughout the lifespan. You'll use this knowledge to develop better educational processes and procedures for schools and other educational agencies, businesses, human and social service organizations, health care providers, government agencies, and more.

How to apply


Degrees & coursework

A master's degree is not required to apply for the doctoral program.

Master's of Arts (M.A.)

M.A. curriculum (33-34 credits)

Doctor of Philosophy (Ph.D)

Ph.D. curriculum (72 credits)

What you'll study

  • Cognitive processes
  • Scientific reasoning
  • Problem solving
  • Teaching effectiveness
  • Intelligence
  • Dynamic-based simulations
  • Learning from texts
  • Software and courseware design
  • Reading and language
  • Adaptive learning systems
  • Technology-enhanced learning
  • Conceptual change
  • Mathematical cognition

  • Faculty

    Learning and cognition / educational technology

    Headshot of Willian Bart

    William M. Bart

    Email | Lab

    • Relationships among cognition, instruction, and testing
    • Gifted and talented education
    • Chess expertise
    Headshot of Panayiota Andrea Kendeou

    Panayiota Andrea Kendeou

    Email | Lab

    • Cognitive processes in reading comprehension
    • Change of pre-existing beliefs and misconceptions
    • Technology-based comprehension interventions and assessments
    Headshot of Robert D. Tennyson

    Robert D. Tennyson

    Email | Lab

    • Cognitive processes in reading comprehension
    • Change of pre-existing beliefs and misconceptions
    • Technology-based comprehension interventions and assessments

    Keisha Varma

    Email | Lab

    • Cognitive processes in science learning
    • Scientific visualizations and student learning outcomes
    • Teacher knowledge development and effective teaching practice
    Headshot of Sashank Varma

    Sashank Varma

    Email | Lab

    • Understanding of abstract mathematical concepts
    • Long-term memory and language understanding
    • Computational models of mathematical reasoning, language understanding, and spatial problem solving
    Headshot of Steve Yussen

    Steve Yussen

    Email | Lab

    • Memory and comprehension of stories
    • Narrative exchanges between children and parents (e.g., storybook reading, reminiscence)
    • The role of culture on narrative storytelling and memory


    Headshot of Reese Butterfuss

    Reese Butterfuss


    “I joined the department for the opportunity to pursue my interests and to get top-quality research training and mentorship.”

    • Interests: Knowledge revision and learning in the context of reading
    • Work: Reese's past work research on reading assessment and academic interventions. Currently, his work explores the individual differences in knowledge revision.
    • Future plans: He would love to continue with research.
    Headshot of Kelsey Will

    Kelsey Will


    • Interests: Development of reading, language and comprehension skills in children, reading comprehension and quality of explanations of autism in children
    • Work: Kelsey worked as a former general psychology lab instructor, as well as a behavior therapist for children with autism. She currently works with her advisor on examining students' quality of explanations after reading refutation and non-refutation texts.
    • Future plans: Kelsey plans to work in a role that combines teaching and research to benefit education at the elementary school level or in higher education.