Computerized Multistage Testing: Theory and Applications

Duanli Yan, Alina A. von Davier, Charles Lewis

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May 7, 2014 by Chapman and Hall/CRC
Reference - 546 Pages - 90 B/W Illustrations
ISBN 9781466505773 - CAT# K14586
Series: Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences

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Features

  • Represents one of the first books on the design, psychometrics, implementation, and operational use of MST
  • Details the steps in the implementation process of an MST design
  • Describes the advantages of MST over linear tests and CATs, including shorter tests and exposure control for items
  • Emphasizes the flexibility of MST in providing consistently accurate assessment for rapidly changing populations
  • Explores the most recent practical applications and their challenges

Summary

Devising tests that evaluate a nation’s educational standing and implement efficacious educational reforms requires a careful balance among the contributions of technology, psychometrics, test design, and the learning sciences. 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. Computerized Multistage Testing: Theory and Applications covers the methodologies, underlying technology, and implementation aspects of this type of test design.

The book discusses current scientific perspectives and practical considerations for each step involved in setting up an MST program. It covers the history of MST, test design and implementation for various purposes, item pool development and maintenance, IRT-based and classical test theory-based methodologies for test assembly, routing and scoring, equating, test security, and existing software. It also explores current research, existing operational programs, and innovative future assessments using MST.

Intended for psychologists, social scientists, and educational measurement scientists, 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.