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Hughes, Katherine L.; Miller, Trey; Reese, Kelly – Grantee Submission, 2021
This report from the Career and Technical Education (CTE) Research Network Lead team provides final results from an evaluability assessment of CTE programs that feasibly could be evaluated using a rigorous experimental design. Evaluability assessments (also called feasibility studies) are used in education and other fields, such as international…
Descriptors: Program Evaluation, Vocational Education, Evaluation Methods, Educational Research
Wing, Coady; Bello-Gomez, Ricardo A. – American Journal of Evaluation, 2018
Treatment effect estimates from a "regression discontinuity design" (RDD) have high internal validity. However, the arguments that support the design apply to a subpopulation that is narrower and usually different from the population of substantive interest in evaluation research. The disconnect between RDD population and the…
Descriptors: Regression (Statistics), Research Design, Validity, Evaluation Methods
Warne, Russell T. – Journal of Advanced Academics, 2016
Card and Giuliano conducted a regression discontinuity study in a large Florida school district to investigate the magnitude of academic benefits of the district's gifted program. They found that for children identified as gifted through an intelligence test, the program provided few or no benefits. But children who were admitted to the gifted…
Descriptors: Special Education, Gifted, Program Evaluation, Educational Research
Adelson, Jill L.; Kelcey, Benjamin – Journal of Advanced Academics, 2016
In this commentary of "Evaluating the Gifted Program of an Urban School District Using a Modified Regression Discontinuity Design" by Davis, Engberg, Epple, Sieg, and Zimmer, we examine the background of the study, critique the methods used, and discuss the results and implications. The study used a fuzzy regression discontinuity design…
Descriptors: Special Education, Gifted, Program Evaluation, Regression (Statistics)
Conklin, Jonathan E.; Burstein, Leigh – 1979
Educational outcomes are affected by student level, classroom level, and school level characteristics. The fact that educational data are multilevel in nature poses serious analysis questions. Though strong arguments can be made for focusing on a single level of analysis, such studies have several basic limitations: the choice of analytic level…
Descriptors: Analysis of Covariance, Correlation, Data Analysis, Mathematical Models
Peer reviewedTrochim, William M.K. – Evaluation Review, 1982
Meta-analysis of Title I program evaluations shows the norm-referenced model overestimates positive effectiveness; while the regression-discontinuity design underestimates it. Potential biases include residual regression artifacts, attrition and time-of-testing problems in the norm-referenced design, and assignment, measurement, and data…
Descriptors: Compensatory Education, Data Collection, Elementary Secondary Education, Evaluation Methods
Peer reviewedHennessy, Michael; Saltz, Robert F. – Evaluation Review, 1989
A beverage-server intervention project at two West Coast Navy bases that attempted to reduce levels of alcoholic intoxication via policy changes and server training is described. Data obtained via interviews and structured observations of 1,511 club customers indicate methodological bias and self-selection effects. Bias adjustments were performed…
Descriptors: Alcohol Abuse, Clubs, Dining Facilities, Enlisted Personnel
Juan Carlos Calcagno; Bridget Terry Long – National Center for Postsecondary Research, 2008
Remedial or developmental courses are the most common policy instruments used to assist underprepared postsecondary students who are not ready for college-level coursework. However, despite its important role in higher education and its substantial costs, there is little rigorous evidence on the effectiveness of college remediation on the outcomes…
Descriptors: Educational Objectives, Academic Persistence, Outcomes of Education, Academic Achievement
Echternacht, Gary; Swinton, Spencer – 1979
Title I evaluations using the RMC Model C design depend for their interpretation on the assumption that the regression of posttest on pretest is linear across the cut score level when there is no treatment; but there are many instances where nonlinearities may occur. If one applies the analysis of covariance, or model C analysis, large errors may…
Descriptors: Achievement Gains, Analysis of Covariance, Educational Assessment, Elementary Secondary Education

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