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Rebeckah K. Fussell; Emily M. Stump; N. G. Holmes – Physical Review Physics Education Research, 2024
Physics education researchers are interested in using the tools of machine learning and natural language processing to make quantitative claims from natural language and text data, such as open-ended responses to survey questions. The aspiration is that this form of machine coding may be more efficient and consistent than human coding, allowing…
Descriptors: Physics, Educational Researchers, Artificial Intelligence, Natural Language Processing
Jennifer Wine; Beth Hustedt; Jennifer Cooney; Erin Thomsen – National Center for Education Statistics, 2023
This report describes the design, methods, and results of the 2016/20 Baccalaureate and Beyond Longitudinal Study (B&B:16/20) conducted by the U.S. Department of Education's National Center for Education Statistics (NCES). It is the second follow-up with a cohort of bachelor's degree recipients originally identified during the 2015-16 National…
Descriptors: Longitudinal Studies, College Graduates, Bachelors Degrees, College Students
Valliant, Richard; Dever, Jill A.; Kreuter, Frauke – Springer, 2013
Survey sampling is fundamentally an applied field. The goal in this book is to put an array of tools at the fingertips of practitioners by explaining approaches long used by survey statisticians, illustrating how existing software can be used to solve survey problems, and developing some specialized software where needed. This book serves at least…
Descriptors: Sampling, Surveys, Computer Software, College Students
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
University of Chicago Consortium on Chicago School Research, 2014
Districts now have access to a wealth of new information that can help target students with appropriate supports and bring focus and coherence to college readiness efforts. However, the abundance of data has brought its own challenges. Schools and school systems are often overwhelmed with the amount of data available. The capacity of districts to…
Descriptors: College Readiness, Educational Indicators, College Preparation, School Districts
Ludtke, Oliver; Marsh, Herbert W.; Robitzsch, Alexander; Trautwein, Ulrich; Asparouhov, Tihomir; Muthen, Bengt – Psychological Methods, 2008
In multilevel modeling (MLM), group-level (L2) characteristics are often measured by aggregating individual-level (L1) characteristics within each group so as to assess contextual effects (e.g., group-average effects of socioeconomic status, achievement, climate). Most previous applications have used a multilevel manifest covariate (MMC) approach,…
Descriptors: Statistical Analysis, Sampling, Context Effect, Simulation
Boller, Kimberly; Kisker, Ellen Eliason – Regional Educational Laboratory, 2014
This guide is designed to help researchers make sure that their research reports include enough information about study measures so that readers can assess the quality of the study's methods and results. The guide also provides examples of write-ups about measures and suggests resources for learning more about these topics. The guide assumes…
Descriptors: Research Reports, Research Methodology, Educational Research, Check Lists
Yoshikawa, Hirokazu; Weisner, Thomas S.; Kalil, Ariel; Way, Niobe – Developmental Psychology, 2008
Multiple methods are vital to understanding development as a dynamic, transactional process. This article focuses on the ways in which quantitative and qualitative methodologies can be combined to enrich developmental science and the study of human development, focusing on the practical questions of "when" and "how." Research situations that may…
Descriptors: Research Methodology, Statistical Analysis, Qualitative Research, Individual Development
Onwuegbuzie, Anthony J.; Leech, Nancy L. – Qualitative Report, 2007
The purpose of this paper is to provide a typology of sampling designs for qualitative researchers. We introduce the following sampling strategies: (a) parallel sampling designs, which represent a body of sampling strategies that facilitate credible comparisons of two or more different subgroups that are extracted from the same levels of study;…
Descriptors: Qualitative Research, Sampling, Comparative Analysis, Generalization
Brese, Falk, Ed.; Carstens, Ralph, Ed. – International Association for the Evaluation of Educational Achievement, 2009
To support and promote secondary analyses, the International Association for the Evaluation of Educational Achievement (IEA) is making the SITES 2006 international database and accompanying User Guide available to researchers, analysts, and public users. The database comprises national contexts and school- and teacher-level data from 23 education…
Descriptors: Academic Achievement, Questionnaires, Information Technology, Educational Technology
Collins, Kathleen M. T.; Onwuegbuzie, Anthony J.; Jiao, Qun G. – Journal of Mixed Methods Research, 2007
A sequential design utilizing identical samples was used to classify mixed methods studies via a two-dimensional model, wherein sampling designs were grouped according to the time orientation of each study's components and the relationship of the qualitative and quantitative samples. A quantitative analysis of 121 studies representing nine fields…
Descriptors: Sampling, Sample Size, Generalization, Qualitative Research
Teddlie, Charles; Yu, Fen – Journal of Mixed Methods Research, 2007
This article presents a discussion of mixed methods (MM) sampling techniques. MM sampling involves combining well-established qualitative and quantitative techniques in creative ways to answer research questions posed by MM research designs. Several issues germane to MM sampling are presented including the differences between probability and…
Descriptors: Sampling, Probability, Research Methodology, Research Design
Shaver, James P. – Phi Delta Kappan, 1985
A dialog between two fictional teachers provides some basic examples of how research that uses approved methodology may provide results that are significant statistically but not significant practically. (PGD)
Descriptors: Educational Research, Research Methodology, Research Problems, Sampling
Shaver, James P. – Phi Delta Kappan, 1985
The second half of a dialogue between two fictional teachers examines the significance of statistical significance in research and considers the factors affecting the extent to which research results provide important or useful information. (PGD)
Descriptors: Educational Research, Research Methodology, Research Problems, Sampling
Suskie, Linda A. – 1988
A guide to survey research is presented for both novice and experienced researchers. Steps of the survey research process are covered: (1) planning the survey to determine the purpose of the study, collecting background information, designing the sample, and making a time line for completing the project; (2) questionnaire design, including the…
Descriptors: Higher Education, Institutional Research, Measurement Techniques, Questionnaires