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Wendy Chan – Asia Pacific Education Review, 2024
As evidence from evaluation and experimental studies continue to influence decision and policymaking, applied researchers and practitioners require tools to derive valid and credible inferences. Over the past several decades, research in causal inference has progressed with the development and application of propensity scores. Since their…
Descriptors: Probability, Scores, Causal Models, Statistical Inference
Reichardt, Charles S. – American Journal of Evaluation, 2022
Evaluators are often called upon to assess the effects of programs. To assess a program effect, evaluators need a clear understanding of how a program effect is defined. Arguably, the most widely used definition of a program effect is the counterfactual one. According to the counterfactual definition, a program effect is the difference between…
Descriptors: Program Evaluation, Definitions, Causal Models, Evaluation Methods
Weidlich, Joshua; Gaševic, Dragan; Drachsler, Hendrik – Journal of Learning Analytics, 2022
As a research field geared toward understanding and improving learning, Learning Analytics (LA) must be able to provide empirical support for causal claims. However, as a highly applied field, tightly controlled randomized experiments are not always feasible nor desirable. Instead, researchers often rely on observational data, based on which they…
Descriptors: Causal Models, Inferences, Learning Analytics, Comparative Analysis
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
Kim, Yongnam; Steiner, Peter – Educational Psychologist, 2016
When randomized experiments are infeasible, quasi-experimental designs can be exploited to evaluate causal treatment effects. The strongest quasi-experimental designs for causal inference are regression discontinuity designs, instrumental variable designs, matching and propensity score designs, and comparative interrupted time series designs. This…
Descriptors: Quasiexperimental Design, Causal Models, Statistical Inference, Randomized Controlled Trials
Lei, Wu; Qing, Fang; Zhou, Jin – International Journal of Distance Education Technologies, 2016
There are usually limited user evaluation of resources on a recommender system, which caused an extremely sparse user rating matrix, and this greatly reduce the accuracy of personalized recommendation, especially for new users or new items. This paper presents a recommendation method based on rating prediction using causal association rules.…
Descriptors: Causal Models, Attribution Theory, Correlation, Evaluation Methods
Marcus, Sue M.; Stuart, Elizabeth A.; Wang, Pei; Shadish, William R.; Steiner, Peter M. – Psychological Methods, 2012
Although randomized studies have high internal validity, generalizability of the estimated causal effect from randomized clinical trials to real-world clinical or educational practice may be limited. We consider the implication of randomized assignment to treatment, as compared with choice of preferred treatment as it occurs in real-world…
Descriptors: Educational Practices, Program Effectiveness, Validity, Causal Models
Schochet, Peter Z.; Puma, Mike; Deke, John – National Center for Education Evaluation and Regional Assistance, 2014
This report summarizes the complex research literature on quantitative methods for assessing how impacts of educational interventions on instructional practices and student learning differ across students, educators, and schools. It also provides technical guidance about the use and interpretation of these methods. The research topics addressed…
Descriptors: Statistical Analysis, Evaluation Methods, Educational Research, Intervention
Leviton, Laura C.; Lipsey, Mark W. – New Directions for Evaluation, 2007
"Theory as Method: Small Theories of Treatments," by Mark W. Lipsey, is one of the most influential and highly cited articles to appear in "New Directions for Evaluation." It articulated an approach in which methods for studying causation depend, in large part, on what is known about the theory underlying the program. Lipsey discussed the benefits…
Descriptors: Attribution Theory, Research Design, Program Effectiveness, Causal Models
Garcia, GNA – Online Submission, 2008
A rich narrative-style bibliography of concept mapping (reviewing six articles published between 1992-2005). Articles reviewed include: (1) Cognitive mapping: A qualitative research method for social work (C. Bitoni); (2) Collaborative concept mapping: Provoking and supporting meaningful discourse (C. Boxtel, J. Linden, E. Roelofs, and G. Erkens);…
Descriptors: Concept Mapping, Qualitative Research, Maps, Cognitive Mapping
Riches, Vivienne Catherine – Journal of Intellectual & Developmental Disability, 2003
A supports classification and assessment system is required in residential settings that enables accurate classification and resource allocation in the context of limited resources. In developing such a system, the American Association on Mental Retardation intensities of supports framework was used and consultation with all stakeholders resulted…
Descriptors: Resource Allocation, Classification, Mental Retardation, Evaluation Methods

Tate, Richard L. – Florida Journal of Educational Research, 1986
Regression-based adjustment of student outcomes for the assessment of the merit of schools is considered. First, the basics of causal modeling and multiple regression are briefly reviewed. Then, two common regression-based adjustment procedures are described, pointing out that the validity of the final assessments depends on: (1) the degree to…
Descriptors: Causal Models, Educational Assessment, Elementary Secondary Education, Evaluation Methods