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Direct linkSchoen, Robert C.; Yang, Xiaotong; Tazaz, Amanda M.; Bray, Wendy S.; Farina, Kristy – Grantee Submission, 2019
The "2016 Knowledge for Teaching Early Elementary Mathematics" (2016 K-TEEM) test measures teachers' mathematical knowledge for teaching early elementary mathematics. The 2016 K-TEEM is the third version of the K-TEEM (Schoen, Bray, Wolfe, Tazaz, & Nielsen, 2017). In this report, we present results of the first large-scale field test…
Descriptors: Test Construction, Elementary School Mathematics, Elementary School Teachers, Knowledge Base for Teaching
Peer reviewedJames Cowan; Dan Goldhaber – Grantee Submission, 2015
We study a popular dual enrollment program in Washington State, "Running Start" using a new administrative database that links high school and postsecondary data. Conditional on prior high school performance, we find that students participating in Running Start are more likely to attend any college but less likely to attend four-year…
Descriptors: Dual Enrollment, College Preparation, College Bound Students, Educational Attainment
Cho, Sun-Joo; Bottge, Brian A. – Grantee Submission, 2015
In a pretest-posttest cluster-randomized trial, one of the methods commonly used to detect an intervention effect involves controlling pre-test scores and other related covariates while estimating an intervention effect at post-test. In many applications in education, the total post-test and pre-test scores that ignores measurement error in the…
Descriptors: Item Response Theory, Hierarchical Linear Modeling, Pretests Posttests, Scores
Cho, Sun-Joo; Preacher, Kristopher J.; Bottge, Brian A. – Grantee Submission, 2015
Multilevel modeling (MLM) is frequently used to detect group differences, such as an intervention effect in a pre-test--post-test cluster-randomized design. Group differences on the post-test scores are detected by controlling for pre-test scores as a proxy variable for unobserved factors that predict future attributes. The pre-test and post-test…
Descriptors: Structural Equation Models, Hierarchical Linear Modeling, Intervention, Program Effectiveness
