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Showing 1 to 15 of 58 results Save | Export
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Alexander von Eye; Wolfgang Wiedermann – Merrill-Palmer Quarterly: A Peer Relations Journal, 2024
In this article, we pursue two points of discussion. First, a new illustration is presented of the person-oriented tenet according to which it can be hazardous to generalize to the individual results that are based on the analysis of aggregated data. Second, it is illustrated that taking into account serial dependence information can result in not…
Descriptors: Research Methodology, Generalizability Theory, Generalization, Multivariate Analysis
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Abdulrazaq A. Imam – International Society for Technology, Education, and Science, 2023
Research in psychology and education tend to use large-N group designs that necessitate reporting of mean measures analyzed mostly with null hypothesis statistical testing (NHST), but sometimes with Bayesian, or the estimation approaches in inferential statistics. These approaches all render the average person or student as the the putative…
Descriptors: Students, Student Characteristics, Generalizability Theory, Research Methodology
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Amanda Davis Simpfenderfer; Romeo Jackson; Danielle Aguilar; C. V. Dolan; Jason C. Garvey – Educational Studies: Journal of the American Educational Studies Association, 2024
This paper aims to unsettle assumptions of generalizability and representativeness in quantitative research using queer framings and positionalities. We argue that generalizability and representativeness are tools of supremacist dominance that reinforce harmful and essentialist categories of identities for the false purpose of statistical…
Descriptors: Homosexuality, Statistical Analysis, Generalizability Theory, Research Methodology
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Jane E. Miller – Numeracy, 2023
Students often believe that statistical significance is the only determinant of whether a quantitative result is "important." In this paper, I review traditional null hypothesis statistical testing to identify what questions inferential statistics can and cannot answer, including statistical significance, effect size and direction,…
Descriptors: Statistical Significance, Holistic Approach, Statistical Inference, Effect Size
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Teker, Gülsen Tasdelen – International Journal of Assessment Tools in Education, 2019
The aim of this paper is to introduce a software that is appropriate for the generalizability theory for not only balanced but also unbalanced data sets. Because it is possible to have unbalanced data sets while conducting a study, the researchers have devised an easy solution, other than deleting data, to balance the design to cope with this…
Descriptors: Generalizability Theory, Research Design, Computer Software, Data
Petscher, Y.; Pentimonti, J.; Stanley, C. – National Center on Improving Literacy, 2019
Validity is broadly defined as how well something measures what it's supposed to measure. The reliability and validity of scores from assessments are two concepts that are closely knit together and feed into each other.
Descriptors: Screening Tests, Scores, Test Validity, Test Reliability
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Schumacker, Randall – Measurement: Interdisciplinary Research and Perspectives, 2019
The R software provides packages and functions that provide data analysis in classical true score, generalizability theory, item response theory, and Rasch measurement theories. A brief list of notable articles in each measurement theory and the first measurement journals is followed by a list of R psychometric software packages. Each psychometric…
Descriptors: Psychometrics, Computer Software, Measurement, Item Response Theory
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Huebner, Alan; Lucht, Marissa – Practical Assessment, Research & Evaluation, 2019
Generalizability theory is a modern, powerful, and broad framework used to assess the reliability, or dependability, of measurements. While there exist classic works that explain the basic concepts and mathematical foundations of the method, there is currently a lack of resources addressing computational resources for those researchers wishing to…
Descriptors: Generalizability Theory, Test Reliability, Computer Software, Statistical Analysis
Stuart, Elizabeth A.; Ackerman, Benjamin; Westreich, Daniel – Research on Social Work Practice, 2018
Randomized trials play an important role in estimating the effect of a policy or social work program in a given population. While most trial designs benefit from strong internal validity, they often lack external validity, or generalizability, to the target population of interest. In other words, one can obtain an unbiased estimate of the study…
Descriptors: Randomized Controlled Trials, Research Design, Validity, Generalizability Theory
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Rupp, André A. – Applied Measurement in Education, 2018
This article discusses critical methodological design decisions for collecting, interpreting, and synthesizing empirical evidence during the design, deployment, and operational quality-control phases for automated scoring systems. The discussion is inspired by work on operational large-scale systems for automated essay scoring but many of the…
Descriptors: Design, Automation, Scoring, Test Scoring Machines
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Uto, Masaki; Ueno, Maomi – IEEE Transactions on Learning Technologies, 2016
As an assessment method based on a constructivist approach, peer assessment has become popular in recent years. However, in peer assessment, a problem remains that reliability depends on the rater characteristics. For this reason, some item response models that incorporate rater parameters have been proposed. Those models are expected to improve…
Descriptors: Item Response Theory, Peer Evaluation, Bayesian Statistics, Simulation
Jen, Enyi; Moon, Sidney; Samarapungavan, Ala – Gifted Child Quarterly, 2015
Design-based research (DBR) is a new methodological framework that was developed in the context of the learning sciences; however, it has not been used very often in the field of gifted education. Compared with other methodologies, DBR is more process-oriented and context-sensitive. In this methodological brief, the authors introduce DBR and…
Descriptors: Academically Gifted, Educational Research, Research Design, Cues
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Shavelson, Richard J. – Educational Psychologist, 2013
E. L. Thorndike contributed significantly to the field of educational and psychological testing as well as more broadly to psychological studies in education. This article follows in his testing legacy. I address the escalating demand, across societal sectors, to measure individual and group competencies. In formulating an approach to measuring…
Descriptors: Competence, Psychology, Psychological Testing, Psychological Studies
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Fan, Xitao; Sun, Shaojing – Journal of Early Adolescence, 2014
In adolescence research, the treatment of measurement reliability is often fragmented, and it is not always clear how different reliability coefficients are related. We show that generalizability theory (G-theory) is a comprehensive framework of measurement reliability, encompassing all other reliability methods (e.g., Pearson "r,"…
Descriptors: Generalizability Theory, Measurement, Reliability, Correlation
Jacob, Robin; Zhu, Pei; Somers, Marie-Andrée; Bloom, Howard – MDRC, 2012
Regression discontinuity (RD) analysis is a rigorous nonexperimental approach that can be used to estimate program impacts in situations in which candidates are selected for treatment based on whether their value for a numeric rating exceeds a designated threshold or cut-point. Over the last two decades, the regression discontinuity approach has…
Descriptors: Regression (Statistics), Research Design, Graphs, Computation
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