|Title:||Berkeley Research Experience and Methodology (BREM) Program|
|Principal Investigator:||Wilson, Mark||Awardee:||University of California, Berkeley|
|Program:||Postdoctoral Research Training Program in the Education Sciences [Program Details]|
|Award Period:||3 years||Award Amount:||$659,375|
Co-Principal Investigator: Rabe-Hesketh, Sophia
This postdoctoral program trained 6 postdoctoral fellows for 2 years each. A major methodological focus of the training program was multilevel and hierarchical modeling and the design and analysis of both randomized and observational studies in the presence of clustering. A second methodological focus was measurement models and the design and analysis of educational assessments. Researchers worked with the postdoctoral fellows to view the different types of approaches and models in these methodological areas from within a unified statistical modeling framework. This supported the postdoctoral fellows in extending the models to tackle specific problems in educational research.
The fellows were engaged in projects based in the Berkeley Evaluation and Assessment Research (BEAR) Center Fellows also worked with faculty associated with the Berkeley Research and Methodology Program (BREM). BREM is comprised of three components: (a) intensive study of methodological topics, (b) supervised engagement in one or more research projects, and (c) the design and implementation of a major study within the educational focus of the program.
As of 2020, Dr. Ayers-Wright was a psychometrician/statistician for the American Institutes for Research, Dr. Castellano was a psychometrician with Educational Testing Service, Dr. Feuerstahler was an assistant professor of psychology at Fordham University, Dr. Park was an education research analyst at the Department of Defense Education Activity, Dr. Roos was an associate professor of sociology at Virginia Polytechnic Institute and State University, and Dr. Stephenson was a senior research data scientist at BrightBytes.
Lehrer, R., Kim, M.J., Ayers, E., and Wilson, M. (2013). Toward Establishing a Learning Progression to Support the Development of Statistical Reasoning. In J. Confrey and A. Maloney (Eds.), Learning Over Time: Learning Trajectories in Mathematics Education. Charlotte, NC: Information Age Publishers.
Journal article, monograph, or newsletter
Ayers, E., Rabe-Hesketh, S., and Nugent, R. (2013). Incorporating Student Covariates in Cognitive Diagnosis Models. Journal of Classification, 30(2): 195–224. doi:10.1007/s00357–013–9130–y
Bates, M., Castellano, K.E., Rabe-Hesketh, S., and Skrondal, A. (2014). Handling Correlations Between Covariates and Random Slopes in Multilevel Models. Journal of Educational and Behavioral Statistics, 39(6): 524–549. doi:10.3102/1076998614559420
Castellano, K.E., and Ho, A.D. (2013). Contrasting OLS and Quantile Regression Approaches to Student "Growth" Percentiles. Journal of Educational and Behavioral Statistics, 38(2): 190–215. doi:10.3102/1076998611435413
Castellano, K.E., and Ho, A.D. (2015). Practical Differences Among Aggregate-Level Conditional Status Metrics: From Median Student Growth Percentiles to Value-Added Models. Journal of Educational and Behavioral Statistics, 40(1): 35–68. doi:10.3102/1076998614548485
Castellano, K.E., Duckor, B., Tellez, K., Wihardini, D., and Wilson, M. (in press). A Validity Study of the Elementary Mathematics Teaching Event for the Performance Assessment for California Teachers.
Castellano, K. E., Duckor, B., Wihardini, D., Telléz, K., and Wilson, M. (2016). Assessing Academic Language in an Elementary Mathematics Teacher Licensure Exam. Teacher Education Quarterly, 43(1), 3–27. Full text
Castellano, K.E., Rabe-Hesketh, S., and Skrondal, A. (2014). Composition, Context, and Endogeneity in School and Teacher Comparisons. Journal of Educational and Behavioral Statistics, 39(5): 333–367. doi:10.3102/1076998614547576
Duckor, B. Castellano, K.E., Tellez, K., and Wilson, M. (2014). Examining the Internal Structure Evidence for the Performance Assessment for California Teachers: A Validation Study of the Elementary Literacy Teaching Event for Tier I Teacher Licensure. Journal of Teacher Education, 65(5): 402–420. doi:10.1177/0022487114542517
Feuerstahler, L. M. (2017). Sources of Error in IRT Trait Estimation. Applied Psychological Measurement, 42(5), 359–375. Doi.10.1177/0146621617733955
Holloway, S.D., and Park, S. (2014). Broken Compass or Broken System? Questioning the Role of Parent Involvement in Promoting Student Achievement. Human Development, 57(6): 360–363. doi:10.1159/000369766
Holloway, S.D., Park, S., Jonas, M., Bempechat, J., and Li, J. (2014). "My Mom Tells Me I Should Follow the Rules, That's Why They Have Those Rules": Perceptions of Parental Advice Giving Among Mexican-Heritage Adolescents. The Journal of Latino and Education, 13(4): 262–277. doi:10.1080/15348431.2014.887468
Nielsen, F., and Roos, J.M. (2015). Genetics of Educational Attainment and the Persistence of Privilege at the Turn of the 21st Century. Social Forces, 94(2): 535–561. doi:10.1093/sf/sov080
Nielsen, F., Roos, J.M., and Combs, R.M. (2015). Clues of Subjective Social Status Among Young Adults. Social Science Research, 52: 370–388. doi:10.1016/j.ssresearch.2015.02.006
Park, S., and Holloway, S. D. (2017). The Effects of Parental School-Based Involvement on Academic Achievement at the Child and Elementary School Level: A Longitudinal Study. The Journal of Educational Research, 110(1), 1–16.
Park, S., and Holloway, S. (2018). Parental Involvement in Adolescents' Education: An Examination of the Interplay Among School Factors, Parental Role Construction, and Family Income. School Community Journal, 28(1), 9–36. Full text
Park, S., Stone, S. I., and Holloway, S. D. (2017). School-Based Parental Involvement as a Predictor of Achievement and School Learning Environment: An Elementary School-Level Analysis. Children and Youth Services Review, 82, 195–206.
Perrin, A.J., Roos, J.M., and Gauchat, G. (2014). From Coalition to Constraint: Modes of Thought in Contemporary American Conservatism. Sociological Forum, 29(2): 285–300. doi:10.1111/socf.12084
Roos, J M. (2016). Alternately Contested: A Measurement Analysis of Alternately Worded Items in the NSF Science Literacy Scale. Socius 2, 2378023116671143.
Roos, J M. (2017). Contested Knowledge and Spillover. Social Currents 4(4), 360–379.
Roos, J.M. (2014). The Vanishing Tetrad Test: Another Test of Model Misspecification. Measurement: Interdisciplinary Research and Perspectives, 12(3): 109–114. doi:10.1080/15366367.2014.943595
Roos. J. M. (2014). Measuring Science or Religion? A measurement analysis of the NSF sponsored science literacy scale 2006–2010.Public Understanding of Science 23(7):797– 813.
Roos, J. M. (2017). Contested Knowledge and Spillover. Social Currents, 4(4), 360–379.
Waller, N. G., and Feuerstahler, L. M. (2017). Bayesian Modal Estimation of the Four-Parameter Item Response Model in Real, Realistic, and Idealized Data Sets. Multivariate Behavioral Research, 52, 350–370.
Nongovernment report, issue brief, or practice guide
Castellano, K.E., and Ho, A.D. (2013). A Practitioner's Guide to Growth Models. Washington DC: Council of Chief State School Officers.
Nugent, R., Dean, N., and Ayers, E. (2010). Skill Set Profile Clustering: The Empty K-Means Algorithm With Automatic Specification of Starting Cluster Centers. In Proceedings of the 3rd International Conference on Educational Data Mining (pp. 151–160). Pittsburgh, PA.