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IES Grant

Title: Carnegie Mellon and RAND Traineeships (CMART) in Methodology and Interdisciplinary Research
Center: NCER Year: 2010
Principal Investigator: Junker, Brian Awardee: Carnegie Mellon University
Program: Postdoctoral Research Training Program in the Education Sciences      [Program Details]
Award Period: 5 years Award Amount: $654,619
Goal: Training Award Number: R305B100012

The Postdoctoral Training in Children's Mathematics Learning at Carnegie Mellon University provides opportunities for fellows to focus on contemporary theories and methods of cognitive development, and participate in experimental studies to test interventions designed to improve learning. The program is carried out in collaboration with RAND Corporation, whose team adds quantitative and methodological training for scientifically rigorous education research. Postdoctoral fellows have the opportunity to work on several projects led by researchers including: the development of an online tutoring system for middle school math; randomized trials evaluating instructional coaching, online geometry tutoring, and other interventions; a study of the consequences of broad reform efforts; educational data mining exploring the effects of online tutors; value-added and related evaluation of teacher performance; and a longitudinal analysis of promotion policies. Along with this research, the program consists of participation and trainings through seminars, colloquia, brown-bags, short courses and workshops, mentoring, and writing publications and grants proposals.


Book chapter

Casabianca, J.M. (2012). The Hierarchical Rater Model. In W.J. van der Linden, and R.K. Hambleton (Eds.), Handbook of Modern Item Response Theory. Boca Raton, FL: Chapman and Hall-CRC.

Casabianca, J.M., and Junker, B.W. (2013). Estimating the Latent Trait Distribution With Loglinear Smoothing Models. In R. Millsap (Ed.), New Developments in Quantitative Psychology (pp. 415–425). New York: Springer Science and Business Media.

Casabianca, J.M., and Junker, B.W. (2012). Discrete Distributions Relevant to Item Response Theory. In W.J. van der Linden, and R.K. Hambleton (Eds.), Handbook of Modern Item Response Theory. Boca Raton, FL: Chapman and Hall/CRC.

Casabianca, J.M., and Junker, B.W. (2012). Multivariate Normal Distributions. In W.J. van der Linden, and R.K. Hambleton (Eds.), Handbook of Modern Item Response Theory. Boca Raton, FL: Chapman and Hall-CRC.

Ream, R.K., and Ryan, S. (in press). Racial Inequality: Achievement. In J. Ainsworth (Ed.), Sociology of Education. Thousand Oaks, CA: SAGE.

Ream, R.K., Ryan, S., and Espinoza, J. (2012). Reframing the Ecology of the ";Achievement Gap";: Why ";No Excuses"; Reforms Have Failed to Narrow Student Group Differences. In T. Timar, and J. Maxwell-Jolly (Eds.), Narrowing the Achievement Gap: Perspectives and Strategies for Challenging Times (pp. 35–56). Cambridge, MA: Harvard Education Press.

Journal article, monograph, or newsletter

Casabianca, J.M., McCaffrey, D.F., Gitomer, D., Bell, C., Hamre, B.K., and Pianta, R.C. (2013). Effect of Observation Mode on Measures of Secondary Mathematics Teaching. Educational and Psychological Measurement, 73(5): 757–783.

Coburn, C.E., Russell, J.L., Kaufman, J., and Stein, M.K. (2012). How Teacher Social Capital Shapes the Implementation of Innovative Standards-Based Mathematics Curricula. American Journal of Education, 119(1): 137–182.

Grim, P., Singer, D.J., Fisher, S., Bramson, A., Berger, W.J., Reade, C., Flocken, C., and Sales, A. (2013). Scientific Networks on Data Landscapes: Question Difficulty, Epistemic Success, and Convergence. Episteme, 10(4): 441–464.

Hebert, P.L., Sisk, J.E., Tuzzio, L., Casabianca, J.M., Pogue, V.A., Wang, J.J., Chen, Y., Coles, C., and McLaughlin, M. (2012). Nurse-Led Disease Management for Hypertension Control in a Diverse Urban Community: A Randomized Trial. Journal of General Internal Medicine, 27(6): 630–636.

Kaufman, J.H., and Schunn, C.D. (2011). Students' Perceptions About Peer Assessment for Writing: Their Origin and Impact on Revision Work. Instructional Science, 39(3): 387–406.

Kaufman, J.H., Karam, R., Pane, J., and Junker, B. (2012). How Curriculum and Classroom Achievement Predict Teacher Time on Lecture- and Inquiry-Based Mathematics Activities. Journal of Mathematics Education at Teachers College, 3(2): 56–62.

Kaufman, J.H., Stein, M.K., and Junker, B. (2016). Factors Associated with Alignment between Teacher Survey Reports and Classroom Observation Ratings of Mathematics Instruction. The Elementary School Journal, 116(3): 339–364.

Knowlton, S., Sales, A. and Merriman, K. (2014). A Comparison of Faculty and Bibliometric Valuation of Serials Subscriptions at an Academic Research Library. Serials Review 40(1): 28–39.

Ryan, S.M. (2016). Ambitions in Action: Investigating College Enrollment Among Hispanic Youth Who Expect to Complete a Bachelor's Degree. Journal of Hispanic Higher Education, 15(1): 3–21.

Stein, M.K., and Kaufman, J.H. (2010). Selecting and Supporting the Use of Mathematics Curricula at Scale. American Educational Research Journal, 47(3): 663–693.

Stein, M.K., Kaufman, J.H., Sherman, M., and Hillen, A. (2011). Algebra: A Challenge at the Crossroads of Policy and Practice. Review of Educational Research, 81(4): 453–492.

Nongovernment report, issue brief, or practice guide

Iriti, J.E., Bickel, W., and Kaufman, J.H. (2012). Realizing 'The Promise': Scholar Retention and Persistence in Postsecondary Education. Pittsburgh: Evaluation for Learning Group.

Ryan, S.M., and Ream, R.K. (2012). Education is a Social Process: Repairing the P-16 Pipeline for Hispanic Youth One Relationship at a Time. Arlington, TX: The Center for K–16 Education Policy and Research.