Bayesian Psychometric Modeling (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)

A Single Cohesive Framework of Tools and Procedures for Psychometrics and Assessment\nBayesian Psychometric Modeling presents a unified Bayesian approach across traditionally separate families of psychometric models. It shows that Bayesian techniques, as alternatives to conventional approaches, offer distinct and profound advantages in achieving many goals of psychometrics.\nAdopting a Bayesian approach can aid in unifying seemingly disparate―and sometimes conflicting―ideas and activities in psychometrics. This book explains both how to perform psychometrics using Bayesian methods and why many of the activities in psychometrics align with Bayesian thinking.\nThe first part of the book introduces foundational principles and statistical models, including conceptual issues, normal distribution models, Markov chain Monte Carlo estimation, and regression. Focusing more directly on psychometrics, the second part covers popular psychometric models, including classical test theory, factor analysis, item response theory, latent class analysis, and Bayesian networks. Throughout the book, procedures are illustrated using examples primarily from educational assessments. A supplementary website provides the datasets, WinBUGS code, R code, and Netica files used in the examples.

Science & Math

Mislevy, Robert J.

Levy, Roy

Mathematics

Routledge

Sociocognitive Foundations of Educational Measurement

Several key developments challenge the field of educational measurement today: demands for tests at larger scales with higher stakes, an improved understanding of how people develop capabilities, and new technologies for interactive digital assessments. Sociocognitive Foundations of Educational Measurement integrates new developments in educational measurement and educational psychology in order to provide researchers, testing professionals, and students with an innovative sociocognitive perspective on assessment. This comprehensive volume begins with a broad explanation of the sociocognitive perspective and the foundations of assessment, then provides a series of focused applications to major topics such as assessment arguments, validity, fairness, interactive assessment, and a conception of "measurement" in educational assessment. Classical test theory, item response theory, categorical models, mixture models, cognitive diagnosis models, and Bayesian networks are explored from the resulting perspective. Ideal for specialists in these areas, graduate students, developers, and scholars in both educational measurement and fields that contribute to a sociocognitive perspective, this book consolidates nearly a decade of research into a fresh perspective on educational measurement.

Behavioral Sciences

Several key developments challenge the field of educational measurement today: demands for tests at larger scales with higher stakes, an improved understanding of how people develop capabilities, and new technologies for interactive digital assessments. Sociocognitive Foundations of Educational Measurement integrates new developments in educational measurement and educational psychology in order to provide researchers, testing professionals, and students with an innovative sociocognitive perspective on assessment. This comprehensive volume begins with a broad explanation of the sociocognitive perspective and the foundations of assessment, then provides a series of focused applications to major topics such as assessment arguments, validity, fairness, interactive assessment, and a conception of "measurement" in educational assessment. Classical test theory, item response theory, categorical models, mixture models, cognitive diagnosis models, and Bayesian networks are explored from the resulting perspective. Ideal for specialists in these areas, graduate students, developers, and scholars in both educational measurement and fields that contribute to a sociocognitive perspective, this book consolidates nearly a decade of research into a fresh perspective on educational measurement.

Computerized Adaptive Testing (CAT) is now entering a new phase of its existence, having developed into a viable alternative form of measurement backed by rigorous technology involving far more than hardware and software. Computer technology, test development, statistics, and mental test theory all play a role in CAT and are thus united in this primer.  Based on 30 years of solid research, this book will educate the novice and serve as a compendium of state-of-the-art data for professionals. A hypothetical test taken as a prelude to employment, the "Gedanken Computerized Adaptive Test," is used throughout as a common example that highlights important features and problems presented by different types of computerized testing.

Computerized Adaptive Testing: A Primer

Health, Fitness & Dieting

Wainer, Howard

Dorans, Neil J.

Flaugher, Ronald

Green, Bert F.

Mental Health

Computerized Adaptive Testing

This celebrated primer presents an introduction to all of the key ingredients in understanding computerized adaptive testing technology, test development, statistics, and mental test theory. Based on years of research, this accessible book educates the novice and serves as a compendium of state-of-the-art information for professionals interested in computerized testing in the areas of education, psychology, and other related social sciences. A hypothetical test taken as a prelude to employment is used as a common example throughout to highlight this book's most important features and problems. Changes in the new edition include: *a completely rewritten chapter 2 on the system considerations needed for modern computerized adaptive testing; *a revised chapter 4 to include the latest in methodology surrounding online calibration and in the modeling of testlets; and *a new chapter 10 with helpful information on how test items are really selected, usage patterns, how usage patterns influence the number of new items required, and tools for managing item pools.

Education & Teaching

Schools & Teaching

A Single Cohesive Framework of Tools and Procedures for Psychometrics and Assessment Bayesian Psychometric Modeling presents a unified Bayesian approach across traditionally separate families of psychometric models. It shows that Bayesian techniques, as alternatives to conventional approaches, offer distinct and profound advantages in achieving many goals of psychometrics. Adopting a Bayesian approach can aid in unifying seemingly disparate―and sometimes conflicting―ideas and activities in psychometrics. This book explains both how to perform psychometrics using Bayesian methods and why many of the activities in psychometrics align with Bayesian thinking. The first part of the book introduces foundational principles and statistical models, including conceptual issues, normal distribution models, Markov chain Monte Carlo estimation, and regression. Focusing more directly on psychometrics, the second part covers popular psychometric models, including classical test theory, factor analysis, item response theory, latent class analysis, and Bayesian networks. Throughout the book, procedures are illustrated using examples primarily from educational assessments. A supplementary website provides the datasets, WinBUGS code, R code, and Netica files used in the examples.

Psychology & Counseling

Chapman and Hall/CRC

Bayesian inference networks, a synthesis of statistics and expert systems, have advanced reasoning under uncertainty in medicine, business, and social sciences. This innovative volume is the first comprehensive treatment exploring how they can be applied to design and analyze innovative educational assessments.
Part I develops Bayes nets’ foundations in assessment, statistics, and graph theory, and works through the real-time updating algorithm. Part II addresses parametric forms for use with assessment, model-checking techniques, and estimation with the EM algorithm and Markov chain Monte Carlo (MCMC). A unique feature is the volume’s grounding in Evidence-Centered Design (ECD) framework for assessment design. This “design forward” approach enables designers to take full advantage of Bayes nets’ modularity and ability to model complex evidentiary relationships that arise from performance in interactive, technology-rich assessments such as simulations. Part III describes ECD, situates Bayes nets as an integral component of a principled design process, and illustrates the ideas with an in-depth look at the BioMass project: An interactive, standards-based, web-delivered demonstration assessment of science inquiry in genetics.
This book is both a resource for professionals interested in assessment and advanced students. Its clear exposition, worked-through numerical examples, and demonstrations from real and didactic applications provide invaluable illustrations of how to use Bayes nets in educational assessment. Exercises follow each chapter, and the online companion site provides a glossary, data sets and problem setups, and links to computational resources.

Bayesian Networks in Educational Assessment (Statistics for Social and Behavioral Sciences)

Computers & Technology

Almond, Russell G.

Steinberg, Linda S.

Yan, Duanli

Williamson, David M.

Computer Science

Springer

Bayesian inference networks, a synthesis of statistics and expert systems, have advanced reasoning under uncertainty in medicine, business, and social sciences. This innovative volume is the first comprehensive treatment exploring how they can be applied to design and analyze innovative educational assessments.Part I develops Bayes nets’ foundations in assessment, statistics, and graph theory, and works through the real-time updating algorithm. Part II addresses parametric forms for use with assessment, model-checking techniques, and estimation with the EM algorithm and Markov chain Monte Carlo (MCMC). A unique feature is the volume’s grounding in Evidence-Centered Design (ECD) framework for assessment design. This “design forward” approach enables designers to take full advantage of Bayes nets’ modularity and ability to model complex evidentiary relationships that arise from performance in interactive, technology-rich assessments such as simulations. Part III describes ECD, situates Bayes nets as an integral component of a principled design process, and illustrates the ideas with an in-depth look at the BioMass project: An interactive, standards-based, web-delivered demonstration assessment of science inquiry in genetics.This book is both a resource for professionals interested in assessment and advanced students.  Its clear exposition, worked-through numerical examples, and demonstrations from real and didactic applications provide invaluable illustrations of how to use Bayes nets in educational assessment. Exercises follow each chapter, and the online companion site provides a glossary, data sets and problem setups, and links to computational resources.

Intended as a resource for game developers, learning designers, and assessment experts, “Psychometric Considerations in Game-based Assessment” presents findings from efforts to build and test a new type of classroom tool – game-based assessments. This book explores the opportunities and challenges for psychometricians and measurement experts in using gameplay data to assess student learning, and proposes a design approach that links the process of game design with the process of assessment design.

Psychometric Considerations in Game-based Assessment

Hoffman, Erin

John, Michael

Oranje, Andreas

Bauer, Malcolm I.

von Davier, Alina

Hao, Jiangang

Corrigan, Seth

DiCerbo, Kristen

CreateSpace Independent Publishing Platform

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