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Deke, John; Finucane, Mariel; Thal, Daniel – National Center for Education Evaluation and Regional Assistance, 2022
BASIE is a framework for interpreting impact estimates from evaluations. It is an alternative to null hypothesis significance testing. This guide walks researchers through the key steps of applying BASIE, including selecting prior evidence, reporting impact estimates, interpreting impact estimates, and conducting sensitivity analyses. The guide…
Descriptors: Bayesian Statistics, Educational Research, Data Interpretation, Hypothesis Testing
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Jones, Thomas J.; Ehlers, Todd A. – Journal of Geoscience Education, 2021
The need for geoscience students to develop a quantitative skillset is ever increasing. However, this can be difficult to implement in university-style lecture courses in a way that is both manageable for the instructor and does not involve lengthy, potentially repetitive, question sheets for the students. Here, a method for teaching dimensional…
Descriptors: Earth Science, Science Experiments, Graduate Students, College Science
Jacob M. Schauer; Kaitlyn G. Fitzgerald; Sarah Peko-Spicer; Mena C. R. Whalen; Rrita Zejnullahi; Larry V. Hedges – Grantee Submission, 2021
Several programs of research have sought to assess the replicability of scientific findings in different fields, including economics and psychology. These programs attempt to replicate several findings and use the results to say something about large-scale patterns of replicability in a field. However, little work has been done to understand the…
Descriptors: Statistical Analysis, Research Methodology, Evaluation Methods, Replication (Evaluation)
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Thompson, W. Burt – Teaching of Psychology, 2019
When a psychologist announces a new research finding, it is often based on a rejected null hypothesis. However, if that hypothesis is true, the claim is a false alarm. Many students mistakenly believe that the probability of committing a false alarm equals alpha, the criterion for statistical significance, which is typically set at 5%. Instructors…
Descriptors: Statistical Analysis, Hypothesis Testing, Misconceptions, Data Interpretation
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Jaylin Lowe; Charlotte Z. Mann; Jiaying Wang; Adam Sales; Johann A. Gagnon-Bartsch – Grantee Submission, 2024
Recent methods have sought to improve precision in randomized controlled trials (RCTs) by utilizing data from large observational datasets for covariate adjustment. For example, consider an RCT aimed at evaluating a new algebra curriculum, in which a few dozen schools are randomly assigned to treatment (new curriculum) or control (standard…
Descriptors: Randomized Controlled Trials, Middle School Mathematics, Middle School Students, Middle Schools
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Ozmen, Zeynep Medine; Guven, Bulent; Kurak, Yasin – Eurasian Journal of Educational Research, 2020
Purpose: Previous research focused on graphical skills of the students, which remains a gap that exists, and there has not been comprehensive research on students' graphical literacy abilities. The present study aims to picture graphical literacy levels of the 8th grade students concerning the "reading," "interpreting,"…
Descriptors: Middle School Students, Grade 8, Knowledge Level, Graphs
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Slayter, Elspeth M. – Journal of Social Work Education, 2017
Existing research suggests a majority of faculty include social justice content in research courses but not through the use of existing quantitative data for in-class activities that foster mastery of data analysis and interpretation and curiosity about social justice-related topics. By modeling data-driven dialogue and the deconstruction of…
Descriptors: Statistical Analysis, Social Justice, Class Activities, Social Work
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He, Lingjun; Levine, Richard A.; Fan, Juanjuan; Beemer, Joshua; Stronach, Jeanne – Practical Assessment, Research & Evaluation, 2018
In institutional research, modern data mining approaches are seldom considered to address predictive analytics problems. The goal of this paper is to highlight the advantages of tree-based machine learning algorithms over classic (logistic) regression methods for data-informed decision making in higher education problems, and stress the success of…
Descriptors: Institutional Research, Regression (Statistics), Statistical Analysis, Data Analysis
Schweig, Jonathan; McEachin, Andrew; Kuhfeld, Megan; Mariano, Louis T.; Diliberti, Melissa Kay – RAND Corporation, 2021
The novel coronavirus disease 2019 (COVID-19) pandemic has created an unprecedented set of obstacles for schools and exacerbated existing structural inequalities in public education. In spring 2020, as schools went to remote learning formats or closed completely, end-of-year assessment programs ground to a halt. As a result, schools began the…
Descriptors: Student Placement, COVID-19, Pandemics, Student Characteristics
Jonathan Schweig; Andrew McEachin; Megan Kuhfeld; Louis T. Mariano; Melissa Kay Diliberti – Grantee Submission, 2021
The novel coronavirus disease 2019 (COVID-19) pandemic has created an unprecedented set of obstacles for schools and exacerbated existing structural inequalities in public education. In spring 2020, as schools went to remote learning formats or closed completely, end-of-year assessment programs ground to a halt. As a result, schools began the…
Descriptors: Student Placement, COVID-19, Pandemics, Student Characteristics
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Swank, Jacqueline M.; Mullen, Patrick R. – Measurement and Evaluation in Counseling and Development, 2017
The article serves as a guide for researchers in developing evidence of validity using bivariate correlations, specifically construct validity. The authors outline the steps for calculating and interpreting bivariate correlations. Additionally, they provide an illustrative example and discuss the implications.
Descriptors: Correlation, Construct Validity, Guidelines, Data Interpretation
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Wang, Jue; Engelhard, George, Jr. – Measurement: Interdisciplinary Research and Perspectives, 2016
The authors of the focus article describe an important issue related to the use and interpretation of causal indicators within the context of structural equation modeling (SEM). In the focus article, the authors illustrate with simulated data the effects of omitting a causal indicator. Since SEMs are used extensively in the social and behavioral…
Descriptors: Structural Equation Models, Measurement, Causal Models, Construct Validity
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Abel, Todd; Poling, Lisa – Teaching Statistics: An International Journal for Teachers, 2015
Working with practicing teachers, this article demonstrates, through the facilitation of a statistical activity, how to introduce and investigate the unique qualities of the statistical process including: formulate a question, collect data, analyze data, and interpret data.
Descriptors: Statistical Analysis, Concept Formation, Data Collection, Data Interpretation
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Bi, Henry H. – Assessment & Evaluation in Higher Education, 2018
There are no absolute standards regarding what teaching evaluation ratings are satisfactory. It is also problematic to compare teaching evaluation ratings with the average or with a cutoff number to determine whether they are adequate. In this paper, we use average and standard deviation charts (X[overbar]-S charts), which are based on the theory…
Descriptors: Robustness (Statistics), Data Interpretation, Rating Scales, Computation
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Boedeker, Peter – Practical Assessment, Research & Evaluation, 2017
Hierarchical linear modeling (HLM) is a useful tool when analyzing data collected from groups. There are many decisions to be made when constructing and estimating a model in HLM including which estimation technique to use. Three of the estimation techniques available when analyzing data with HLM are maximum likelihood, restricted maximum…
Descriptors: Hierarchical Linear Modeling, Maximum Likelihood Statistics, Bayesian Statistics, Computation
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