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Andrew P. Jaciw – American Journal of Evaluation, 2025
By design, randomized experiments (XPs) rule out bias from confounded selection of participants into conditions. Quasi-experiments (QEs) are often considered second-best because they do not share this benefit. However, when results from XPs are used to generalize causal impacts, the benefit from unconfounded selection into conditions may be offset…
Descriptors: Elementary School Students, Elementary School Teachers, Generalization, Test Bias
Elaine Chiu – Society for Research on Educational Effectiveness, 2024
Background: Observation Studies, Unmeasured Confounding, and Sensitivity Analysis: An important part of educational research is identifying important, potentially causal, factors that influence children's learning from observational studies. However, it is well-known that discovering such factors from observational studies can be biased due to…
Descriptors: Educational Research, Research Methodology, Attribution Theory, Learning Processes
Erdener, Mehmet Akif – Universal Journal of Educational Research, 2016
Parent involvement has an influence on children's educational engagement for all school levels. The objective of this study was to examine public school principals' and teachers' practices for improving parent involvement in schooling. This study used a mixed method to identify the school administrators' and teachers' perceptions about parent…
Descriptors: Principals, Parent Participation, Foreign Countries, Mixed Methods Research
Wong, Manyee; Cook, Thomas D.; Steiner, Peter M. – Journal of Research on Educational Effectiveness, 2015
Some form of a short interrupted time series (ITS) is often used to evaluate state and national programs. An ITS design with a single treatment group assumes that the pretest functional form can be validly estimated and extrapolated into the postintervention period where it provides a valid counterfactual. This assumption is problematic. Ambiguous…
Descriptors: Evaluation Methods, Time, Federal Legislation, Educational Legislation
Cooper, Harris – National Council of Teachers of Mathematics, 2008
Opinions vary on whether or not homework has positive effects on achievement. In the literature, the author found six studies conducted between 1987 and 2003 that compared homeworkers with no-homeworkers, and equated students by using either: (1) random assignments of students to conditions; or (2) statistical controls or by matching a student in…
Descriptors: Homework, Academic Achievement, Scores, Educational Research
Schochet, Peter Z. – National Center for Education Evaluation and Regional Assistance, 2009
This paper examines the estimation of two-stage clustered RCT designs in education research using the Neyman causal inference framework that underlies experiments. The key distinction between the considered causal models is whether potential treatment and control group outcomes are considered to be fixed for the study population (the…
Descriptors: Control Groups, Causal Models, Statistical Significance, Computation
Jo, Booil – Journal of Educational and Behavioral Statistics, 2008
An analytical approach was employed to compare sensitivity of causal effect estimates with different assumptions on treatment noncompliance and non-response behaviors. The core of this approach is to fully clarify bias mechanisms of considered models and to connect these models based on common parameters. Focusing on intention-to-treat analysis,…
Descriptors: Evaluation Methods, Intention, Research Methodology, Causal Models
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection