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Peter Z. Schochet – Journal of Educational and Behavioral Statistics, 2025
Random encouragement designs evaluate treatments that aim to increase participation in a program or activity. These randomized controlled trials (RCTs) can also assess the mediated effects of participation itself on longer term outcomes using a complier average causal effect (CACE) estimation framework. This article considers power analysis…
Descriptors: Statistical Analysis, Computation, Causal Models, Research Design
Peter Schochet – Society for Research on Educational Effectiveness, 2024
Random encouragement designs are randomized controlled trials (RCTs) that test interventions aimed at increasing participation in a program or activity whose take up is not universal. In these RCTs, instead of randomizing individuals or clusters directly into treatment and control groups to participate in a program or activity, the randomization…
Descriptors: Statistical Analysis, Computation, Causal Models, Research Design
Cohausz, Lea – Journal of Educational Data Mining, 2022
Student success and drop-out predictions have gained increased attention in recent years, connected to the hope that by identifying struggling students, it is possible to intervene and provide early help and design programs based on patterns discovered by the models. Though by now many models exist achieving remarkable accuracy-values, models…
Descriptors: Guidelines, Academic Achievement, Dropouts, Prediction
Joyce, Kathryn E.; Cartwright, Nancy – American Educational Research Journal, 2020
This article addresses the gap between what works in research and what works in practice. Currently, research in evidence-based education policy and practice focuses on randomized controlled trials. These can support causal ascriptions ("It worked") but provide little basis for local effectiveness predictions ("It will work…
Descriptors: Theory Practice Relationship, Educational Policy, Evidence Based Practice, Educational Research
Rottman, Benjamin M.; Keil, Frank C. – Cognitive Psychology, 2012
Seven studies examined how people learn causal relationships in scenarios when the variables are temporally dependent--the states of variables are stable over time. When people intervene on X, and Y subsequently changes state compared to before the intervention, people infer that X influences Y. This strategy allows people to learn causal…
Descriptors: Reaction Time, Causal Models, Prediction, Observation
Harvill, Eleanor L.; Peck, Laura R.; Bell, Stephen H. – American Journal of Evaluation, 2013
Using exogenous characteristics to identify endogenous subgroups, the approach discussed in this method note creates symmetric subsets within treatment and control groups, allowing the analysis to take advantage of an experimental design. In order to maintain treatment--control symmetry, however, prior work has posited that it is necessary to use…
Descriptors: Experimental Groups, Control Groups, Research Design, Sampling
Voortman, Mark – ProQuest LLC, 2010
Recently, several philosophical and computational approaches to causality have used an interventionist framework to clarify the concept of causality [Spirtes et al., 2000, Pearl, 2000, Woodward, 2005]. The characteristic feature of the interventionist approach is that causal models are potentially useful in predicting the effects of manipulations.…
Descriptors: Causal Models, Mathematics, Prediction, Intervention
Moore, J. – Behavior Analyst, 2010
In this reply to Baum, I emphasize that the failure to understand the processes associated with scientific verbal behavior may result in scientific statements like the generalized matching law that do not accurately reflect cause-and-effect relations.
Descriptors: Verbal Stimuli, Behavioral Science Research, Prediction, Intervention
Metcalfe, Lindsay A.; Harvey, Elizabeth A.; Laws, Holly B. – Journal of Educational Psychology, 2013
Existing research suggests that there is a relation between academic/cognitive deficits and externalizing behavior in young children, but the direction of this relation is unclear. The present study tested competing models of the relation between academic/cognitive functioning and behavior problems during early childhood. Participants were 221…
Descriptors: Longitudinal Studies, Cognitive Ability, Academic Ability, Behavior Problems
Sloman, Steven A.; Lagnado, David A. – Cognitive Science, 2005
A normative framework for modeling causal and counterfactual reasoning has been proposed by Spirtes, Glymour, and Scheines (1993; cf. Pearl, 2000). The framework takes as fundamental that reasoning from observation and intervention differ. Intervention includes actual manipulation as well as counterfactual manipulation of a model via thought. To…
Descriptors: Observation, Intervention, Causal Models, Prediction
Jordan, Will J.; And Others – 1994
This study analyzes NELS:88 data from a dropout sample of students who were enrolled in the eighth grade in 1988 but who were not enrolled in school in 1990. The data for this analysis were collected in Spring 1990 to examine reasons for dropping out and plans for dropouts to resume their education. In both areas, differences were found on…
Descriptors: Academic Aspiration, Black Students, Causal Models, Dropout Research
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers