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Showing 1 to 15 of 33 results Save | Export
Elizabeth Talbott; Andres De Los Reyes; Devin M. Kearns; Jeannette Mancilla-Martinez; Mo Wang – Exceptional Children, 2023
Evidence-based assessment (EBA) requires that investigators employ scientific theories and research findings to guide decisions about what domains to measure, how and when to measure them, and how to make decisions and interpret results. To implement EBA, investigators need high-quality assessment tools along with evidence-based processes. We…
Descriptors: Evidence Based Practice, Evaluation Methods, Special Education, Educational Research
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Peugh, James; Feldon, David F. – CBE - Life Sciences Education, 2020
Structural equation modeling is an ideal data analytical tool for testing complex relationships among many analytical variables. It can simultaneously test multiple mediating and moderating relationships, estimate latent variables on the basis of related measures, and address practical issues such as nonnormality and missing data. To test the…
Descriptors: Structural Equation Models, Goodness of Fit, Statistical Analysis, Computation
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Makel, Matthew C.; Smith, Kendal N.; McBee, Matthew T.; Peters, Scott J.; Miller, Erin M. – AERA Open, 2019
Concerns about the replication crisis and unreliable findings have spread through several fields, including education and psychological research. In some areas of education, researchers have begun to adopt reforms that have proven useful in other fields. These include preregistration, open materials and data, and registered reports. These reforms…
Descriptors: Credibility, Cooperation, Educational Research, Replication (Evaluation)
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Lortie-Forgues, Hugues; Inglis, Matthew – Educational Researcher, 2019
In this response, we first show that Simpson's proposed analysis answers a different and less interesting question than ours. We then justify the choice of prior for our Bayes factors calculations, but we also demonstrate that the substantive conclusions of our article are not substantially affected by varying this choice.
Descriptors: Randomized Controlled Trials, Bayesian Statistics, Educational Research, Program Evaluation
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Cook, Bryan G.; Therrien, William J. – Behavioral Disorders, 2017
Researchers sometimes conduct a study and find that the predicted relation between variables did not exist or that the intervention did not have a positive impact on student outcomes; these are referred to as null findings because they fail to disconfirm the null hypothesis. Rather than consider such studies as failures and disregard the null…
Descriptors: Publications, Bias, Special Education, Educational Research
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Goodboy, Alan K. – Communication Education, 2017
For decades, instructional communication scholars have relied predominantly on cross-sectional survey methods to generate empirical associations between effective teaching and student learning. These studies typically correlate students' perceptions of their instructor's teaching behaviors with subjective self-report assessments of their own…
Descriptors: Educational Research, Communication Strategies, Teaching Methods, Learning Processes
McBee, Matthew T.; Makel, Matthew C.; Peters, Scott J.; Matthews, Michael S. – Gifted Child Quarterly, 2018
Current practices in study design and data analysis have led to low reproducibility and replicability of findings in fields such as psychology, medicine, biology, and economics. Because gifted education research relies on the same underlying statistical and sociological paradigms, it is likely that it too suffers from these problems. This article…
Descriptors: Academically Gifted, Research Methodology, Social Psychology, Research
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Haegele, Justin A.; Hodge, Samuel R. – Physical Educator, 2015
Emerging professionals, particularly senior-level undergraduate and graduate students in kinesiology who have an interest in physical education for individuals with and without disabilities, should understand the basic assumptions of the quantitative research paradigm. Knowledge of basic assumptions is critical for conducting, analyzing, and…
Descriptors: Statistical Analysis, Educational Research, Physical Education, Adapted Physical Education
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Peng, Chao-Ying Joanne; Long, Haiying; Abaci, Serdar – Journal of Experimental Education, 2012
Given the importance of statistical power analysis in quantitative research and the repeated emphasis on it by American Educational Research Association/American Psychological Association journals, the authors examined the reporting practice of power analysis by the quantitative studies published in 12 education/psychology journals between 2005…
Descriptors: Educational Research, Computer Software, Hypothesis Testing, Statistical Analysis
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Demetrion, George – Journal of Research and Practice for Adult Literacy, Secondary, and Basic Education, 2012
The purpose of this essay is to draw out key insights from Dewey's important text "Logic: The Theory of Inquiry" to provide theoretical and practical support for the emergent field of teacher research. The specific focal point is the argument in Cochran-Smith and Lytle's "Inside/Outside: Teacher Research and Knowledge" on the significance of…
Descriptors: Educational Research, Teacher Researchers, Research Methodology, Inquiry
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Draxler, Clemens – Educational Research and Evaluation, 2011
This article discusses the application of logit models for the analyses of 2-way categorical observations. The models described are generalized linear models using the logit link function. One of the models is the Rasch model (Rasch, 1960). The objective is to test hypotheses of marginal and conditional independence between explanatory quantities…
Descriptors: Models, Item Response Theory, Educational Research, Hypothesis Testing
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Bahr, Peter Riley – Research in Higher Education, 2009
Variables that address student enrollment patterns (e.g., persistence, enrollment inconsistency, completed credit hours, course credit load, course completion rate, procrastination) constitute a longstanding fixture of analytical strategies in educational research, particularly research that focuses on explaining variation in academic outcomes.…
Descriptors: Institutional Research, Educational Research, Academic Persistence, Educational Attainment
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Eisenhauer, Joseph G. – Teaching Statistics: An International Journal for Teachers, 2009
Very little explanatory power is required in order for regressions to exhibit statistical significance. This article discusses some of the causes and implications. (Contains 2 tables.)
Descriptors: Statistical Significance, Educational Research, Sample Size, Probability
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Lawson, Anton E. – Science Education Review, 2008
We should dispense with use of the confusing term "null hypothesis" in educational research reports. To explain why the term should be dropped, the nature of, and relationship between, scientific and statistical hypothesis testing is clarified by explication of (a) the scientific reasoning used by Gregor Mendel in testing specific…
Descriptors: Hypothesis Testing, Educational Research, Statistical Analysis, Prediction
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DiStefano, Christine; Zhu, Min; Mindrila, Diana – Practical Assessment, Research & Evaluation, 2009
Following an exploratory factor analysis, factor scores may be computed and used in subsequent analyses. Factor scores are composite variables which provide information about an individual's placement on the factor(s). This article discusses popular methods to create factor scores under two different classes: refined and non-refined. Strengths and…
Descriptors: Factor Structure, Factor Analysis, Researchers, Scores
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