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Sangbaek Park – ProQuest LLC, 2024
This dissertation used synthetic datasets, semi-synthetic datasets, and a real-world dataset from an educational intervention to compare the performance of 15 machine learning and multiple imputation methods to estimate the individual treatment effect (ITE). In addition, it examined the performance of five evaluation metrics that can be used to…
Descriptors: Artificial Intelligence, Computation, Evaluation Methods, Bayesian Statistics
Manolov, Rumen; Tanious, René; Fernández-Castilla, Belén – Journal of Applied Behavior Analysis, 2022
In science in general and in the context of single-case experimental designs, replication of the effects of the intervention within and/or across participants or experiments is crucial for establishing causality and for assessing the generality of the intervention effect. Specific developments and proposals for assessing whether an effect has been…
Descriptors: Intervention, Behavioral Science Research, Replication (Evaluation), Research Design
What Works Clearinghouse, 2022
Education decisionmakers need access to the best evidence about the effectiveness of education interventions, including practices, products, programs, and policies. It can be difficult, time consuming, and costly to access and draw conclusions from relevant studies about the effectiveness of interventions. The What Works Clearinghouse (WWC)…
Descriptors: Program Evaluation, Program Effectiveness, Standards, Educational Research
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
Sloman, Steven A. – Cognitive Science, 2013
Judea Pearl won the 2010 Rumelhart Prize in computational cognitive science due to his seminal contributions to the development of Bayes nets and causal Bayes nets, frameworks that are central to multiple domains of the computational study of mind. At the heart of the causal Bayes nets formalism is the notion of a counterfactual, a representation…
Descriptors: Causal Models, Cognitive Psychology, Cognitive Science, Cognitive Processes
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
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
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
Stuart, Elizabeth A. – Educational Researcher, 2007
Education researchers, practitioners, and policymakers alike are committed to identifying interventions that teach students more effectively. Increased emphasis on evaluation and accountability has increased desire for sound evaluations of these interventions; and at the same time, school-level data have become increasingly available. This article…
Descriptors: Research Methodology, Computation, Causal Models, Intervention
Schweigert, Francis J. – American Journal of Evaluation, 2006
In the present climate of public accountability, there is increasing demand to show "what works" and what return is gained for the public from investments to improve communities. This increasing demand for accountability is being met with growing confidence in the field of philanthropy during the past 10 years that the impact or effectiveness of…
Descriptors: Evaluation Methods, Private Financial Support, Accountability, Philanthropic Foundations
Randolph, Justus J.; Eronen, Pasi J. – Online Submission, 2004
Background: Although there are many high-quality models for program and evaluation planning, these models are often too intensive to be used in situations when time and resources are scarce. Additionally, there is little added value in using an elaborate and expensive program and evaluation planning procedure when programs are small or are planned…
Descriptors: Sexually Transmitted Diseases, Prevention, Communicable Diseases, Logical Thinking
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