Overview
Kevin (Chun-Wei) Huang is a Senior Research Associate with the Learning and Technology team. He specializes in research design, applied statistics, and psychometrics. Over the past 18 years, Huang has led, designed, and implemented rigorous randomized controlled trials and measurement projects funded by the U.S. Department of Education, the National Science Foundation, and private foundations. He contributes his knowledge and experience to these projects by following the What Works Clearinghouse guidance and applying sophisticated statistical and measurement models. He has also worked with the states or local education agencies to plan and conduct studies to evaluate the statewide or districtwide K–12 education policy.
Before joining WestEd, Huang worked as a psychometrician and research manager at CTB/McGraw-Hill (now DRC/CTB), where he led statistical and psychometric analyses on two statewide testing programs. He was also part of the TerraNova development team, designing and conducting field tests to update the assessments on a yearly basis. He has taught educational statistics at undergraduate and graduate levels while pursuing his doctoral degree at the University of Maryland, College Park.
Education
- PhD in measurement, statistics, and evaluation, University of Maryland at College Park, Graduate School of Education
- MA in psychology, University of Missouri at Kansas City, School of Humanities and Social Sciences
- BS in psychology, Kaohsiung Medical University in Taiwan
Select Publications
Flynn, K., Li, L., Huang, C-W., Patel, R., Luttgen, K., Yang, S., & Chow, E. (2024). Leveraging technology to address social–emotional learning during the pandemic: Findings from an efficacy trial. Social and Emotional Learning: Research, Practice, and Policy, 4, 100045. https://doi.org/10.1016/j.sel.2024.100045
Jordan N. C., Klein, A., & Huang, C-W. (2024). Screener for early number sense (SENS). Hammill Institute.
Feng, M., Huang, C., & Collins, K. (2023). Promising long term effects of ASSISTments online math homework support. In N. Wang, G. Rebolledo-Mendez, V. Dimitrova, N. Matsuda, & O. C. Santos (Eds.), Artificial intelligence in education: Posters and late breaking results, workshops and tutorials, industry and innovation tracks, practitioners, doctoral consortium and Blue Sky. AIED 2023. Communications in Computer and Information Science, vol. 1831. Springer. https://doi.org/10.1007/978-3-031-36336-8_32
Huang, C-W., Li, L., & Flynn K. (2023). Psychometric properties of SELweb and its use in measuring student social–emotional learning. Paper presented at the annual meeting of the National Council on Measurement in Education, Chicago.
Li, L., Flynn K., Huang, C-W., & Luttgen K. (2023). Investigating efficacy, moderators, and implementation of a game-based social–emotional learning platform. Paper presented at the annual meeting of the American Educational Research Association, Chicago.
Bracco, K., Huang, C-W., Fong, T., & Finkelstein, N. (2021). Using multiple measures to predict success in students’ first college math course: An examination of multiple measures under Executive Order 1110 in the California State University system. WestEd.
Perry, R., & Huang, K. (2019). Spotlight on student achievement: Analyses of statewide assessment data in Math in Common districts. WestEd. http://sdbjrfoundation.org/education/stem/advancing-teaching-and-learning/math-in-common/
Barnes, M. A., Klein, A., Swank, P., Starkey, P., McCandliss, B., Flynn, K., Zucker, T., Huang, C.-W., Fall, A.-M., & Roberts, G. (2016). Effects of tutorial interventions in mathematics and attention for low-performing preschool children. Journal of Research on Educational Effectiveness, 9(4), 577–606. https://doi.org/10.1080/19345747.2016.1191575
Gallagher, C., Huang, K., & Van Matre, J. (2015). STEM Learning Opportunities Providing Equity (SLOPE): An Investing in Innovation (i3) grant [Final evaluation report, ED565472]. https://files.eric.ed.gov/fulltext/ED565472.pdf
Snipes, J., Huang, C.-W., Jaquet, K., & Finkelstein, N. (2015). The effects of the Elevate Math summer program on math achievement and algebra readiness (REL 2015–096). U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance, Regional Educational Laboratory West. https://ies.ed.gov/ncee/rel/regions/west/pdf/REL_2015096.pdf
Huang, C.-W., Snipes, J., & Finkelstein, N. (2014). Using assessment data to guide math course placement of California middle school students (REL 2014–040). U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance, Regional Educational Laboratory West. https://ies.ed.gov/ncee/rel/regions/west/pdf/REL_2014040.pdf
Quellmalz, E. S., Davenport, J. L., Timms, M. J., DeBoer, G. E., Jordan, K. A., Huang, C.-W., & Buckley, B. C. (2013). Next-generation environments for assessing and promoting complex science learning. Journal of Educational Psychology, 105(4), 1100–1114.
Finkelstein, N., Hanson, T., Huang, C.-W., Hirschman, B., & Huang, M. (2010). Effects of problem based economics on high school economics instruction [NCEE 2010–4002]. National Center for Education Evaluation and Regional Assistance, Institute of Education Sciences, U.S. Department of Education.
Huang, C.-W., & Mislevy, R. J. (2010). An application of the polytomous Rasch model to mixed strategies. In M. L. Nering & R. Ostini (Eds.), Handbook of polytomous item response theory models (pp. 211–228). Routledge Academic.
Sato, E., Rabinowitz, S., Gallagher, C., & Huang, C.-W. (2010). Accommodations for English language learner students: The effect of linguistic modification of math test item sets [NCEE 2009–4079]. National Center for Education Evaluation and Regional Assistance, Institute of Education Sciences, U.S. Department of Education.
Mislevy, R. J., & Huang, C.-W. (2007). Measurement models as narrative structures. In M. V. Davier & C. H. Carstensen (Eds.), Multivariate and mixture distribution Rasch models (pp. 15–35). Springer.
Huang, C.-W., & Mislevy, R. J. (2004, June). An application of the Andersen/Rasch Multivariate Measurement Model within the framework of evidence-centered design to explore students’ problem-solving in physics. Paper presented at the international meeting of the Psychometric Society, Monterey, CA.