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Lortie-Forgues, Hugues; Inglis, Matthew – Educational Researcher, 2019
In this response, we first show that Simpson's proposed analysis answers a different and less interesting question than ours. We then justify the choice of prior for our Bayes factors calculations, but we also demonstrate that the substantive conclusions of our article are not substantially affected by varying this choice.
Descriptors: Randomized Controlled Trials, Bayesian Statistics, Educational Research, Program Evaluation
Vandivere, Sharon; Malm, Karin – Child Trends, 2015
This document was produced by the authors based on their research for the report, "Family Finding Evaluations: A Summary of Recent Findings. Publication #2015-01," and is an added resource for further information. The report reviews the results from 13 evaluations of Family Finding. The Family Finding model provides child welfare…
Descriptors: Foster Care, Barriers, Family Relationship, Child Welfare
Johnson, Matt; Sprowles, Amy; Overeem, Katlin; Rich, Angela – Learning Communities: Research & Practice, 2013
A place-based learning community called "Klamath Connection" was designed to improve the academic performance of freshman in Science, Technology, Engineering, and Math (STEM) majors at Humboldt State University, a midsize public institution in a location geographically and culturally unfamiliar to the majority of its students. The…
Descriptors: Place Based Education, College Freshmen, State Universities, Academic Achievement
Schochet, Peter Z. – Mathematica Policy Research, Inc., 2008
Studies that examine the impacts of education interventions on key student, teacher, and school outcomes typically collect data on large samples and on many outcomes. In analyzing these data, researchers typically conduct multiple hypothesis tests to address key impact evaluation questions. Tests are conducted to assess intervention effects for…
Descriptors: Hypothesis Testing, Guidelines, Outcomes of Education, Evaluation Methods

Posavac, E. J. – Evaluation and Program Planning, 1998
Misuses of null hypothesis significance testing are reviewed and alternative approaches are suggested for carrying out and reporting statistical tests that might be useful to program evaluators. Several themes, including the importance of respecting the magnitude of Type II errors and describing effect sizes in units stakeholders can understand,…
Descriptors: Effect Size, Evaluation Methods, Hypothesis Testing, Program Evaluation
Hanes, John C.; Hail, Michael – 1999
Many program evaluations involve some type of statistical testing to verify that the program has succeeded in accomplishing initially established goals. In many cases, this takes the form of null hypothesis significance testing (NHST) with t-tests, analysis of variance, or some form of the general linear model. This paper contends that, at least…
Descriptors: Change, Educational Indicators, Evaluation Methods, Hypothesis Testing
Kern, Sarah M.; Sherman, Sharon J.; Conte, Anthony E. – Educational Forum, The, 2004
The faculty and administration of a school of education in the mid-Atlantic region formally adopted a standards-based, conceptual framework that reflects the values articulated by the faculty and the outcomes for students as they prepare for and develop in their professions. Faculty and administrators agreed to use the framework as the basis for…
Descriptors: Program Evaluation, Professional Development, Guidelines, Cultural Pluralism

Katz, Richard S.; Eagles, Munroe – PS: Political Science and Politics, 1996
Constructs a model that explains a large fraction of the variance in political science departmental rankings. Divides the objective predictors into two sets: one reflecting faculty quality ratings of department members, the other the effects of circumstances beyond a department's control. This model works well with most social science disciplines.…
Descriptors: Achievement Rating, Analysis of Variance, Causal Models, Credentials

Jackman, Robert W.; Siverson, Randolph M. – PS: Political Science and Politics, 1996
Analyzes the National Research Council's rating of political science departments and discovers the ratings reflect two general sets of characteristics, the size and productivity of the faculty. Reveals that the quality and impact of faculty research is more important than the overall output. Includes tables of statistical data. (MJP)
Descriptors: Achievement Rating, Analysis of Variance, Credentials, Departments
Nadler, Reldan S. – 1980
In 1976 a demonstration project at the Connecticut Wilderness School integrated a Confluent Education curriculum in Outward Bound type courses, to facilitate affective learning for a more meaningful and relevant experience. A review of Outward Bound literature identified the need for affective learning as a significant program constituent. Five…
Descriptors: Adolescents, Affective Objectives, Attitude Change, Attitude Measures