"The computer-adaptive multistage testing (ca-MST) has been developed as an alternative to computerized adaptive testing (CAT), and been increasingly adopted in large-scale assessments. Current research and practice only focus on ca-MST panels for credentialing purposes. The ca-MST test mode, therefore, is designed to gauge a single scale. The present study is the first step to investigate ca-MST panels for diagnostic purposes, which involve the assessment of multiple attributes in the same test. This study employed computer simulation to compare multidimensional ca-MST panels and their unidimensional counterparts, and to explore the factors that affect the accuracy and efficiency of multidimensional ca-MST. Nine multidimensional ca-MST panel designs - which differed in configuration and test length - were simulated under varied attribute correlation scenarios. In addition, item pools with different qualities were studied to suggest appropriate item bank design. The comparison between the multidimensional ca-MST and a sequential of unidimensional ca-MST suggested that when attributes correlated moderate to high, employing a multidimensional ca-MST provided more accurate and efficient scoring decisions than several unidimensional ca-MST with IRT scoring. However, a multidimensional ca-MST did not perform better than its unidimensional counterpart with MIRT scoring. Nevertheless, multidimensional panels are still promising for diagnostic purposes given practical considerations. The investigation on multidimensional ca-MST design indicated the following: Higher attribute correlation was associated with better scoring decision because more information carried by a correlation matrix was available for estimation. This held true across all item pool conditions. An optimal item pool would be the one that was discriminative, appropriately located and specifically designed for a configuration. The accuracy and efficiency of a multidimensional ca-MST panel would be diminished if its item pool was too easy, or not informative. According to the results, the 1-2-3 configuration design was most promising. In terms of test length, an appropriate decision would largely depend on the attribute correlation and the item pool characteristics."--Abstract from author supplied metadata.

Unlike other forms of adaptive testing, multistage testing (MST) is highly suitable for testing educational achievement because it can be adapted to educational surveys and student testing. This volume provides the first unified source of information on the design, psychometrics, implementation, and operational use of MST. It shows how to apply theoretical statistical tools to testing in novel and useful ways. It also explains how to explicitly tie the assumptions made by each model to observable (or at least inferable) data conditions.

The goal of this guide and manual is to provide a practical and brief overview of the theory on computerized adaptive testing (CAT) and multistage testing (MST) and to illustrate the methodologies and applications using R open source language and several data examples. Implementation relies on the R packages catR and mstR that have been already or are being developed by the first author (with the team) and that include some of the newest research algorithms on the topic. The book covers many topics along with the R-code: the basics of R, theoretical overview of CAT and MST, CAT designs, CAT assembly methodologies, CAT simulations, catR package, CAT applications, MST designs, IRT-based MST methodologies, tree-based MST methodologies, mstR package, and MST applications. CAT has been used in many large-scale assessments over recent decades, and MST has become very popular in recent years. R open source language also has become one of the most useful tools for applications in almost all fields, including business and education. Though very useful and popular, R is a difficult language to learn, with a steep learning curve. Given the obvious need for but with the complex implementation of CAT and MST, it is very difficult for users to simulate or implement CAT and MST. Until this manual, there has been no book for users to design and use CAT and MST easily and without expense; i.e., by using the free R software. All examples and illustrations are generated using predefined scripts in R language, available for free download from the book's website.

This open access book presents a large number of innovations in the world of operational testing. It brings together different but related areas and provides insight in their possibilities, their advantages and drawbacks. The book not only addresses improvements in the quality of educational measurement, innovations in (inter)national large scale assessments, but also several advances in psychometrics and improvements in computerized adaptive testing, and it also offers examples on the impact of new technology in assessment. Due to its nature, the book will appeal to a broad audience within the educational measurement community. It contributes to both theoretical knowledge and also pays attention to practical implementation of innovations in testing technology.

First thorough treatment of multidimensional item response theory Description of methods is supported by numerous practical examples Describes procedures for multidimensional computerized adaptive testing

Integrating Timing Considerations to Improve Testing Practices synthesizes a wealth of theory and research on time issues in assessment into actionable advice for test development, administration, and scoring. One of the major advantages of computer-based testing is the capability to passively record test-taking metadata—including how examinees use time and how time affects testing outcomes. This has opened many questions for testing administrators. Is there a trade-off between speed and accuracy in test taking? What considerations should influence equitable decisions about extended-time accommodations? How can test administrators use timing data to balance the costs and resulting validity of tests administered at commercial testing centers? In this comprehensive volume, experts in the field discuss the impact of timing considerations, constraints, and policies on valid score interpretations; administrative accommodations, test construction, and examinees’ experiences and behaviors; and how to implement the findings into practice. These 12 chapters provide invaluable resources for testing professionals to better understand the inextricable links between effective time allocation and the purposes of high-stakes testing.

The second edition of the Handbook of Test Development provides graduate students and professionals with an up-to-date, research-oriented guide to the latest developments in the field. Including thirty-two chapters by well-known scholars and practitioners, it is divided into five sections, covering the foundations of test development, content definition, item development, test design and form assembly, and the processes of test administration, documentation, and evaluation. Keenly aware of developments in the field since the publication of the first edition, including changes in technology, the evolution of psychometric theory, and the increased demands for effective tests via educational policy, the editors of this edition include new chapters on assessing noncognitive skills, measuring growth and learning progressions, automated item generation and test assembly, and computerized scoring of constructed responses. The volume also includes expanded coverage of performance testing, validity, fairness, and numerous other topics. Edited by Suzanne Lane, Mark R. Raymond, and Thomas M. Haladyna, The Handbook of Test Development, 2nd edition, is based on the revised Standards for Educational and Psychological Testing, and is appropriate for graduate courses and seminars that deal with test development and usage, professional testing services and credentialing agencies, state and local boards of education, and academic libraries serving these groups.