Kimberly Colvin

Kimberly F. Colvin

Psychometric Methods

The World Within Reach
Kimberly F. Colvin, Ed.D.
Assistant Professor

School of Education
Department: Educational and Counseling Psychology

Division of Educational Psychology and Methodology
ED 244



Dr. Colvin joined UAlbany’s Educational Psychology and Methodology faculty in 2014. She received her doctorate in psychometrics from the University of Massachusetts Amherst and completed a post-doctoral research fellowship at the Massachusetts Institute of Technology (MIT). She holds a bachelor’s and a master’s degree in statistics and a master’s in mathematics curriculum and instruction. For ten years she was a high school math teacher in central New York. Dr. Colvin's research focuses on computer-based assessments as well as the use of item response theory in the development and analysis of educational and psychological instruments.

Additional Information


EPSY 640 – Educational & Psychological Measurement (Fall 2014, Fall 2015, Fall 2016)

EPSY 687 – Item Response Theory (Fall 2015)

EPSY 751 – Multivariate Methods for Applied Researchers (Spring 2015, Spring 2016)

EPSY 441 - Social Issues in Testing (Spring 2016)


Colvin, K. F., & Keller, L. A. (in press). Markov Chain Monte Carlo Item Response Theory Estimation. In Wiley StatsRef-Statistics Reference Online (WSR), John Wiley & Sons.

Keller, L. A., Keller, R., Cook, R., & Colvin, K. F. (2016). Impact of accumulated error on item response theory pre-equating with mixed format tests. Applied Measurement in Education, 29(1), 65-82.

Keller, L. A., Colvin, K. F. & Garcia, A. (2016). Growth: Measurement, meaning, and misuse. In C.S. Wells & M. Faulkner-Bond (Eds.), Educational Measurement: From Foundations to Future (pp. 318-334). New York, NY: Guilford Press.

Mariani, M., Villares, E., Sink, C., Colvin, K. F., & Kuba, S. P. (in press). Confirming the structural validity of the [Student] My Class Inventory – Short Form Revised. Professional School Counseling.

Rayyan, S., Fredericks, C., Colvin, K. F., Liu, A.*, Teodorescu, R., Barrantes, A., Pawl, A., Seaton, D. T., & Pritchard, D. E. (2016). A MOOC based on blended pedagogy. Journal of Computer Assisted Learning, doi: 10.1111/jcal.12126.

Villares, E., Mariani, M., Sink, C., & Colvin, K. F. (in press). Multilevel confirmatory factor analysis of the Teacher My Class Inventory – Short Form. Measurement and Evaluation in Counseling and Development.

Balint, T. A., Teodorescu, R., Colvin, K. F., Choi, Y-J., & Pritchard, D. E. (2015). Comparing measures of student performance in hybrid and MOOC physics courses. European Journal of Physics Education 6(3), 32-43.

Colvin, K. F., & Keller, L. A. (2015). Bias in testing: What does it mean? In S. Thompson (Ed.), Encyclopedia of Diversity and Social Justice (pp. 715-717). Lanham, MD: Rowman & Littlefield Publishers.

Colvin, K. F., Champaign, J., Liu, A.*, Zhou, Q., Fredericks, C., & Pritchard, D. E. (2014). Learning in an introductory physics MOOC: All cohorts learn equally, including an on-campus class. The International Review of Research in Open and Distance Learning IRRODL 15, 4.

Keller, L. A., & Colvin, K. F. (2014). Review of the book The Rise of Data in Education Systems: Collection, Visualization, and Use edited by Martin Lawn. Comparative Education Review, 58, 549-551.

Villares, E., Colvin, K. F., Carey, J., Webb, L., Brigman, G., & Harrington, K. (2014). Convergent and divergent validity of the Student Engagement in School Success Skills Survey. The Professional Counselor, 4(5), 541-552.

Colvin, K. F. (2013). Review of the book Doing Bayesian data analysis: A tutorial with R and BUGS, by J. K. Kruschke. Journal of Educational Measurement, 50, 469-471.