Assessment Engineering in Test Design presents an engineering-inspired, multi-disciplinary approach to the field of applied measurement that bridges the gap between the craft of item writing and test design, the statistical sophistication of psychometric methods for scale development and maintenance, and score interpretations. This book directly addresses the topic of “next generation” assessment design head-on by proposing a new perspective, a new understanding, of the challenge of designing, developing, and implementing large- (and small-) scale educational testing programs.

It introduces Assessment Engineering (AE) as a principled approach to test design where human judgment and creative license during test blueprinting and item writing are replaced with carefully developed cognitive task models that can generate highly consistent test forms that support intended statistical score scale properties and interpretations over time. In doing so, it shows how AE integrates key technologies and design principles from industrial engineering, cognitive science, information technology, machine learning and artificial intelligence, data science, statistical quality control, and advanced psychometrics to the practice of test design and development. Ultimately, this integrated approach offers improved and more consistent overall assessment quality; implementation of highly structured designs and scalable automation to reduce item production costs; reduction of item pretesting costs and exposure; improved calibration and scale maintenance over time; and more consistent generation and deployment of very high-quality, low-cost test items to meet both low- and high-volume production demands over time.

Written by a major contributor to the literature on test design and scoring, Assessment Engineering in Test Design is an essential read for all students of psychology and related disciplines as well as test developers and psychometricians.

About the Author

Richard M. Luecht is a Professor Emeritus of Educational Research Methodology at UNC-Greensboro. He has designed numerous algorithms and software programs for automated test assembly and devised a computerized adaptive multistage testing framework used by several large-scale testing programs.

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