Cizek / Wollack Handbook of Detecting Cheating on Tests

Erscheinungsjahr 2016
ISBN: 978-1-317-58809-2
Verlag: CRC Press
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 444 Seiten

Reihe: Educational Psychology Handbook

Given the increased reliance on testing in education, the importance of identifying cheating is today more important than ever. The Handbook of Detecting Cheating on Tests is a comprehensive book that describes the variety of ways people cheat and the quantitative methods that have been developed to detect and combat them. It includes not only the spectrum of existing techniques, but presents new, innovative methodologies as well. By using two common data sets across chapters, it is able to collect all of this information in one place in a way that is rigorous and comparable. Edited by two of the foremost experts on the subject, it includes contributions from leading experts in the field.

Autoren/Hrsg.

Cizek, Gregory J.

Wollack, James A.

Fachgebiete

• Sozialwissenschaften Pädagogik Pädagogik

Inhaltsverzeichnis

Section I: Introduction. 1. Introduction and Context Gregory J. Cizek & James A. Wollack 2. A Standardized Approach to Evaluating Methodologies James A. Wollack & Gregory J. Cizek Section II: Methodologies to Identify Cheating on Tests. Section IIA: Detecting Similarity, Answer Copying, & Aberrance. 3. Similarity, Answer Copying, and Aberrance: Understanding the Status Quo Cengiz Zopluoglu 4. Practicality of Aberrance Statistics in Detecting Unusual Testing Behavior Rory McCorkle, Shungwon Ro & Larissa Smith 5. Detection of Answer Similarity Using the M4 Index Dennis Maynes Section IIB: Detecting Preknowledge and Item Compromise 6. Detecting Preknowledge and Item Compromise: Understanding the Status Quo Carol Eckerly 7. Detection of Test Collusion using Cluster Analysis James Wollack & Dennis Maynes 8. Detection of Preknowledge using Differential Person and Item Functioning Lisa O’Leary & Russell Smith 9. Identification of Test Collusion by the Methods of Information Theory and Combinatorial Optimization Dmitry Belov 10. Cheating Detection on Computer Simulations Michael Jodoin 11. Using Response Time Data to Detect Compromised Items and/or People Wim van der Linden Section IIC - Detecting Unusual Gain Scores and Test Tampering 12. Detecting Erasures and Unusual Gain Scores: Understanding the Status Quo Scott Bishop 13. Detection of Test Tampering at the Group Level James Wollack & Carol Eckerly 14. A Bayesian Hierarchical Linear Model for Detecting Group-Level Cheating and Aberrance William P. Skorupski & Karla Egan 15. Using Nonlinear Regression to Identify Unusual Performance Level Classification Rates J. Michael Clark, William Skorupski, & Stephen Murphy 16. Detecting Unexpected Changes in Pass Rates: A Comparison of Two Statistical Approaches Yuanyuan Z. McBride & Matthew N. Gaertner Section III: Theory, Practice, and the Future of Quantitative Methods. 17. Security Vulnerabilities Facing NextGen Accountability Testing Joseph Martineau or Kristen Huff 18. Establishing Baseline Data for Incidents of Misconduct in the NextGen Assessment Environment Deborah Harris, Chi-Yu Huang, & Rya Dunnington 19. Visual Displays of Test Fraud Data Russell Smith & Brett Foley 20. A Bayesian Argument for Test Fraud Analyses William P. Skorupski & Howard Wainer 21. When Numbers Are Not Enough: Collection and Use of External Information to Assess the Ethics and/or Professionalism of Examinees Suspected of Test Fraud Marc Weinstein Section IV: Conclusions 22. What We Have Learned About the Standardized Datasets Allan Cohen, Jerry Melican, John Fremer, Wayne Camara, Denny Way, or Tom Haladyna 23. Conclusions and Final Thoughts Gregory J. Cizek & James A. Wollack

Über Autor(innen)

Gregory J. Cizek is Professor of Educational Measurement and Assessment in the School of Education at the University of North Carolina, Chapel Hill

James A. Wollack is Associate Professor of Quantitative Methods and Director of Testing and Evaluation Services at the University of Wisconsin, Madison