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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
Tajmel, Tanja – Cultural Studies of Science Education, 2019
With the present forum contribution, I respond to the paper "Discerning contextual complexities in STEM career pathways--Insights from successful Latinas" by Alejandro Gallard MartÃnez, Wesley Pitts, Silvia Lizette Ramos de Robles, Katie L. Milton Brkich, Belinda Flores Bustos, and Lorena Claeys. I aim to augment the thoughts of Gallard…
Descriptors: STEM Education, Science Careers, Educational Research, Figurative Language
Arnold, Lydia; Norton, Lin – Higher Education Academy, 2018
This resource has been written specifically for higher education practitioners who are interested in improving students' learning experiences through the process of researching their own practice. We use the term 'higher education practitioners' to describe all who work in universities and who have a stake in students' learning experiences.…
Descriptors: Higher Education, Educational Research, Action Research, Definitions
Beaujean, A. Alexander; Morgan, Grant B. – Practical Assessment, Research & Evaluation, 2016
Education researchers often study count variables, such as times a student reached a goal, discipline referrals, and absences. Most researchers that study these variables use typical regression methods (i.e., ordinary least-squares) either with or without transforming the count variables. In either case, using typical regression for count data can…
Descriptors: Multiple Regression Analysis, Educational Research, Least Squares Statistics, Models
Wise, Alyssa Friend; Shaffer, David Williamson – Journal of Learning Analytics, 2015
It is an exhilarating and important time for conducting research on learning, with unprecedented quantities of data available. There is a danger, however, in thinking that with enough data, the numbers speak for themselves. In fact, with larger amounts of data, theory plays an ever-more critical role in analysis. In this introduction to the…
Descriptors: Learning Theories, Predictor Variables, Data, Data Analysis
Diakow, Ronli Phyllis – ProQuest LLC, 2013
This dissertation comprises three papers that propose, discuss, and illustrate models to make improved inferences about research questions regarding student achievement in education. Addressing the types of questions common in educational research today requires three different "extensions" to traditional educational assessment: (1)…
Descriptors: Inferences, Educational Assessment, Academic Achievement, Educational Research
Ding, Lin; Beichner, Robert – Physical Review Special Topics - Physics Education Research, 2009
This paper introduces five commonly used approaches to analyzing multiple-choice test data. They are classical test theory, factor analysis, cluster analysis, item response theory, and model analysis. Brief descriptions of the goals and algorithms of these approaches are provided, together with examples illustrating their applications in physics…
Descriptors: Multiple Choice Tests, Factor Analysis, Data Interpretation, Item Response Theory

Peshkin, Alan – Educational Researcher, 1993
Dismissing research that is not theory driven, hypothesis testing, or generalization producing does injustice to the variety of contributions that qualitative research can make. Studies conducted through qualitative approaches are reviewed to summarize the desirable outcomes that can result. No research model has a monopoly on quality. (SLD)
Descriptors: Data Interpretation, Educational Research, Evaluation Methods, Generalization

Mitchell, Douglas E.; And Others – Peabody Journal of Education, 1989
Article reanalyzes and expands upon data from Tennessee's Project STAR which examined the effects of class size reduction on student achievement in the primary grades. It describes six competing theories of class size impact on achievement and test performance, settling on the student group/modeling interpretation of study data. (SM)
Descriptors: Academic Achievement, Achievement Gains, Class Size, Data Interpretation
Herrington, David E. – Online Submission, 2005
This study highlights the value of leveraging department resources in principal preparation program resources to achieve multiple teaching and program review goals. In this study, masters degree candidates participated in all aspects of the evaluation of the Department of Educational Administration and Counseling. As consumers they already had a…
Descriptors: Program Evaluation, Instructional Leadership, Evaluators, Data Interpretation