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Showing all 11 results Save | Export
Adam C. Sales; Ethan Prihar; Johann Gagnon-Bartsch; Ashish Gurung; Neil T. Heffernan – Grantee Submission, 2022
Randomized A/B tests allow causal estimation without confounding but are often under-powered. This paper uses a new dataset, including over 250 randomized comparisons conducted in an online learning platform, to illustrate a method combining data from A/B tests with log data from users who were not in the experiment. Inference remains exact and…
Descriptors: Research Methodology, Educational Experiments, Causal Models, Computation
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Singer, Judith D. – Journal of Research on Educational Effectiveness, 2019
The arc of quantitative educational research should not be etched in stone but should adapt and change over time. In this article, I argue that it is time for a reshaping by offering my personal view of the past, present and future of our field. Educational research--and research in the social and life sciences--is at a crossroads. There are many…
Descriptors: Educational Research, Research Methodology, Longitudinal Studies, Evaluation
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Cook, Thomas D.; Steiner, Peter M. – Psychological Methods, 2010
In this article, we note the many ontological, epistemological, and methodological similarities between how Campbell and Rubin conceptualize causation. We then explore 3 differences in their written emphases about individual case matching in observational studies. We contend that (a) Campbell places greater emphasis than Rubin on the special role…
Descriptors: Research Methodology, Pretests Posttests, Data Analysis, Evaluation Methods
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Onwuegbuzie, Anthony J.; Leech, Nancy L. – Qualitative Report, 2006
The purpose of this paper is to discuss the development of research questions in mixed methods studies. First, we discuss the ways that the goal of the study, the research objective(s), and the research purpose shape the formation of research questions. Second, we compare and contrast quantitative research questions and qualitative research…
Descriptors: Qualitative Research, Methods Research, Research Methodology, Statistical Analysis
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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
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Schumacker, Randall E. – Mid-Western Educational Researcher, 1993
Structural equation models merge multiple regression, path analysis, and factor analysis techniques into a single data analytic framework. Measurement models are developed to define latent variables, and structural equations are then established among the latent variables. Explains the development of these models. (KS)
Descriptors: Causal Models, Data Analysis, Error of Measurement, Factor Analysis
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Attewell, Paul A.; Lavin, David E.; Domina, Thurston; Levey, Tania – Journal of Higher Education, 2006
Using college transcripts, we separate the effects of remedial coursework from high school preparation. For two-year colleges, taking remedial classes was "not" associated with less academic success. In four-year colleges, there "are" negative effects of remedial coursework, but many minority students who complete a bachelor's…
Descriptors: Minority Groups, Remedial Instruction, Inferences, Literature Reviews
Helberg, Clay – 1996
Abuses and misuses of statistics are frequent. This digest attempts to warn against these in three broad classes of pitfalls: sources of bias, errors of methodology, and misinterpretation of results. Sources of bias are conditions or circumstances that affect the external validity of statistical results. In order for a researcher to make…
Descriptors: Causal Models, Comparative Analysis, Data Analysis, Error of Measurement
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Keith, Timothy Z. – Remedial and Special Education (RASE), 1993
This overview of nonexperimental causal research methods focuses on latent variable structural equation modeling using the LISREL computer program. An extended example in special education is used to present LISREL as an extension of structural equations analysis (path analysis) and as a method of reducing the effects of error in research.…
Descriptors: Causal Models, Computer Oriented Programs, Computer Software, Data Analysis
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
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