William (Hank) Murrah
Associate Professor and Department Head
Office: 4038 Haley
Units: Department of Educational Foundations, Leadership, and Technology
Campus Mail: 4036 Haley Center
Phone: (334) 844-3806
Educational Research, Measurement, and Assessment
Short BioHank Murrah is the Department Head, Educational Foundations, Leadership, and Technology, and he is also an Associate Professor of Quantitative Methods at Auburn University. He teaches introductory and advanced research methods courses in the College of Education. His expertise is in cognitive development and learning. His research is focused on understanding how our early experiences, motor learning, motivation, and emotions impact how we learn and think in formal and informal educational settings. He uses large scale data sets including Early Childhood Longitudinal Studies (ECLS) and the National Longitudinal Study of Youth (NLSY), and is currently also working with the Adolescent Brain Cognitive Development (ABCD) data.
Dr. Murrah is a Co-Founder of the Quantitative Methods in Educational Research (QMER) learning community, and is a co-director of the SCALES Lab.
Prior to joining Auburn University Dr. Murrah earned his Ph.D. in Educational Psychology from the University of Virginia where he also completed a postdoctoral fellowship and worked as a research scientist.
M.Ed. in Counseling, 1997, University of Montevallo
B.S. in Psychology, 1994, University of Montevallo
Ph.D. in Educational Psychology, University of Virginia
2023 - present
Associate Professor and Department Head, Auburn University
2021 - 2023
Associate Professor, Auburn University
2016 - 2021
Assistant Professor, Auburn University
2013 - 2016
Research Scientist, University of Virginia
2010 - 2013
Postdoctoral Fellow, University of Virginia
Research InterestsDr. Murrah' research interests focus on two primary areas: experimental design and
secondary data analysis. He has worked as a primary methodologist on four randomized
controlled trials evaluating interventions aimed at promoting STEM related cognitive skills, student motivation, reading skills and socioemotional skills. His work with secondary data analysis focuses on using large-scale nationally representative data sets to understand the development of academic skills in disadvantaged and at-risk students.