The rising reliance on testing in American education and for licensure and certification has been accompanied by an escalation in cheating on tests at all levels. Edited by two of the foremost experts on the subject, the Handbook of Quantitative Methods for Detecting Cheating on Tests offers a comprehensive compendium of increasingly sophisticated data forensics used to investigate whether or not cheating has occurred. Written for practitioners, testing professionals, and scholars in testing, measurement, and assessment, this volume builds on the claim that statistical evidence often requires less of an inferential leap to conclude that cheating has taken place than do other, more common sources of evidence.
This handbook is organized into sections that roughly correspond to the kinds of threats to fair testing represented by different forms of cheating. In Section I, the editors outline the fundamentals and significance of cheating, and they introduce the common datasets to which chapter authors' cheating detection methods were applied. Contributors describe, in Section II, methods for identifying cheating in terms of improbable similarity in test responses, preknowledge and compromised test content, and test tampering. Chapters in Section III concentrate on policy and practical implications of using quantitative detection methods. Synthesis across methodological chapters as well as an overall summary, conclusions, and next steps for the field are the key aspects of the final section.
Publisher: Taylor & Francis Ltd
Number of pages: 428
Weight: 998 g
Dimensions: 254 x 178 mm
"Today, cheating increasingly presents ever-changing challenges to the integrity of test results used for admissions, graduation, certification, professional licensure, and accountability. Cizek and Wollack are two of the most recognized and cited experts on educational test security, and the Handbook of Quantitative Methods for Detecting Cheating on Tests provides the most comprehensive treatment of statistical methods for detection that simply must be incorporated into any large-scale assessment program used for high-stakes decisions."
--Wayne Camara, Senior Vice President, Research, ACT
This edited volume has taken the importance of test security in test validation to a different level. It reflects the maturity of the field of cheating detection, whereby statistical probabilities are no longer presented as inferential leaps into vague, colluded, remote chances of cheating behavior; rather, they are presented using precise empirical evidence that identifies specific cheating behaviors on which one can act. The authors bring together comprehensive knowledge on increasing data forensics and methodologies alongside legally presentable evidence to help reduce the fraudulent use of test results. The book will sit atop my bookshelf for years to come.
--Ardeshir Geranpayeh, Head of Automated Assessment & Learning at Cambridge English Language Assessment, University of Cambridge, UK