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Webb, Kevin C.; Zingaro, Daniel; Liao, Soohyun Nam; Taylor, Cynthia; Lee, Cynthia; Clancy, Michael; Porter, Leo – ACM Transactions on Computing Education, 2022
A Concept Inventory (CI) is an assessment to measure student conceptual understanding of a particular topic. This article presents the results of a CI for basic data structures (BDSI) that has been previously shown to have strong evidence for validity. The goal of this work is to help researchers or instructors who administer the BDSI in their own…
Descriptors: Measures (Individuals), Concept Formation, Computer Science Education, Test Results
de Ruiter, Laura E.; Bers, Marina U. – Computer Science Education, 2022
Background and Context: Despite the increasing implementation of coding in early curricula, there are few valid and reliable assessments of coding abilities for young children. This impedes studying learning outcomes and the development and evaluation of curricula. Objective: Developing and validating a new instrument for assessing young…
Descriptors: Programming Languages, Computer Software, Coding, Computer Science Education
Ames, Allison; Myers, Aaron – Educational Measurement: Issues and Practice, 2019
Drawing valid inferences from modern measurement models is contingent upon a good fit of the data to the model. Violations of model-data fit have numerous consequences, limiting the usefulness and applicability of the model. As Bayesian estimation is becoming more common, understanding the Bayesian approaches for evaluating model-data fit models…
Descriptors: Bayesian Statistics, Psychometrics, Models, Predictive Measurement
Dimitrov, Dimiter M. – Measurement and Evaluation in Counseling and Development, 2017
This article offers an approach to examining differential item functioning (DIF) under its item response theory (IRT) treatment in the framework of confirmatory factor analysis (CFA). The approach is based on integrating IRT- and CFA-based testing of DIF and using bias-corrected bootstrap confidence intervals with a syntax code in Mplus.
Descriptors: Test Bias, Item Response Theory, Factor Analysis, Evaluation Methods
Weinberg, Paul J. – Journal of Pre-College Engineering Education Research, 2017
Mechanistic reasoning is an epistemic practice central within science, technology, engineering, and mathematics disciplines. Although there has been some work on mechanistic reasoning in the research literature and standards documents, much of this work targets domain-general characterizations of mechanistic reasoning; this study provides…
Descriptors: Thinking Skills, STEM Education, Item Response Theory, Scientific Concepts
Weirich, Sebastian; Haag, Nicole; Hecht, Martin; Böhme, Katrin; Siegle, Thilo; Lüdtke, Oliver – Large-scale Assessments in Education, 2014
Background: In order to measure the proficiency of person populations in various domains, large-scale assessments often use marginal maximum likelihood IRT models where person proficiency is modelled as a random variable. Thus, the model does not provide proficiency estimates for any single person. A popular approach to derive these proficiency…
Descriptors: Measurement, Item Response Theory, Measurement Techniques, Evaluation Methods
Kulesz, Paulina A.; Francis, David J.; Barnes, Marcia A.; Fletcher, Jack M. – Journal of Educational Psychology, 2016
Component skills and discourse frameworks of reading have identified characteristics of readers and texts that influence comprehension. However, these 2 frameworks have not previously been integrated in a comprehensive and systematic way to explain performance on any standardized assessment of reading comprehension that is in widespread use across…
Descriptors: Reading Comprehension, Reading Tests, Middle School Students, High School Students
Deygers, Bart; Van Gorp, Koen – Language Testing, 2015
Considering scoring validity as encompassing both reliable rating scale use and valid descriptor interpretation, this study reports on the validation of a CEFR-based scale that was co-constructed and used by novice raters. The research questions this paper wishes to answer are (a) whether it is possible to construct a CEFR-based rating scale with…
Descriptors: Rating Scales, Scoring, Validity, Interrater Reliability
Tourangeau, Karen; Nord, Christine; Lê, Thanh; Wallner-Allen, Kathleen; Vaden-Kiernan, Nancy; Blaker, Lisa; Najarian, Michelle – National Center for Education Statistics, 2018
This manual provides guidance and documentation for users of the longitudinal kindergarten-fourth grade (K-4) data file of the Early Childhood Longitudinal Study, Kindergarten Class of 2010-11 (ECLS-K:2011). It mainly provides information specific to the fourth-grade round of data collection. The first chapter provides an overview of the…
Descriptors: Children, Longitudinal Studies, Surveys, Kindergarten
Goldhaber, Dan; Lavery, Lesley; Theobald, Roddy; D'Entremont, Dylan; Fang, Yangru – Center for Education Data & Research, 2012
Recent research (Strunk and Reardon forthcoming) applies Partial Independence Item Response (PIIR) models to teacher bargaining agreements in California to calculate the latent restrictiveness of these contracts. Further research (Strunk and Grissom 2010; Strunk forthcoming) tests the external validity of these estimates. Given that much research…
Descriptors: Profiles, Unions, Collective Bargaining, Inferences
Maydeu-Olivares, Alberto; Brown, Anna – Multivariate Behavioral Research, 2010
The comparative format used in ranking and paired comparisons tasks can significantly reduce the impact of uniform response biases typically associated with rating scales. Thurstone's (1927, 1931) model provides a powerful framework for modeling comparative data such as paired comparisons and rankings. Although Thurstonian models are generally…
Descriptors: Item Response Theory, Rating Scales, Models, Comparative Analysis
Shin, Seon-Hi – Practical Assessment, Research & Evaluation, 2009
This study investigated the impact of the coding scheme on IRT-based true score equating under a common-item nonequivalent groups design. Two different coding schemes under investigation were carried out by assigning either a zero or a blank to a missing item response in the equating data. The investigation involved a comparison study using actual…
Descriptors: True Scores, Equated Scores, Item Response Theory, Coding
Tracy, Allison J.; Erkut, Sumru; Porche, Michelle V.; Kim, Jo; Charmaraman, Linda; Grossman, Jennifer M.; Ceder, Ineke; Garcia, Heidie Vazquez – Structural Equation Modeling: A Multidisciplinary Journal, 2010
In this article, we operationalize identification of mixed racial and ethnic ancestry among adolescents as a latent variable to (a) account for measurement uncertainty, and (b) compare alternative wording formats for racial and ethnic self-categorization in surveys. Two latent variable models were fit to multiple mixed-ancestry indicator data from…
Descriptors: Ethnicity, Racial Identification, Adolescents, Item Response Theory
Tourangeau, Karen; Nord, Christine; Lê, Thanh; Wallner-Allen, Kathleen; Vaden-Kiernan, Nancy; Blaker, Lisa; Najarian, Michelle – National Center for Education Statistics, 2018
This manual provides guidance and documentation for users of the longitudinal kindergarten-fourth grade (K-4) public-use data file of the Early Childhood Longitudinal Study, Kindergarten Class of 2010-11 (ECLS-K:2011), which includes the first release of the public version of the third-grade data. This manual mainly provides information specific…
Descriptors: Longitudinal Studies, Children, Surveys, Kindergarten
Fox, Connie; Zhu, Weimo; Park, Youngsik; Fisette, Jennifer L.; Graber, Kim C.; Dyson, Ben; Avery, Marybell; Franck, Marian; Placek, Judith H.; Rink, Judy; Raynes, De – Measurement in Physical Education and Exercise Science, 2011
In addition to validity and reliability evidence, other psychometric qualities of the PE Metrics assessments needed to be examined. This article describes how those critical psychometric issues were addressed during the PE Metrics assessment bank construction. Specifically, issues included (a) number of items or assessments needed, (b) training…
Descriptors: Measures (Individuals), Psychometrics, Interrater Reliability, Training
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