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E-grāmata: Test Fraud: Statistical Detection and Methodology [Taylor & Francis e-book]

Edited by (University of Kansas, USA), Edited by (University of Kansas, USA)
  • Formāts: 284 pages, 36 Tables, black and white; 34 Line drawings, black and white
  • Sērija : Routledge Research in Education
  • Izdošanas datums: 28-Apr-2014
  • Izdevniecība: Routledge
  • ISBN-13: 9781315884677
  • Taylor & Francis e-book
  • Cena: 168,97 €*
  • * this price gives unlimited concurrent access for unlimited time
  • Standarta cena: 241,39 €
  • Ietaupiet 30%
  • Formāts: 284 pages, 36 Tables, black and white; 34 Line drawings, black and white
  • Sērija : Routledge Research in Education
  • Izdošanas datums: 28-Apr-2014
  • Izdevniecība: Routledge
  • ISBN-13: 9781315884677
"There has been an increase in awareness (and perhaps occurrence) of individual and organized cheating on tests. Recent reports of widespread problems with state student accountability tests and teacher certification testing have raised questions about the very validity of assessment programs. While there are several books that specifically detail the issues of test security cheating on assessments, few outline the statistical procedures used for detecting various types of potential test fraud and the associated research findings. Without a significant research literature base, the new generation of researchers will have little opportunity or incentive to improve on existing methods.Enlisting a variety of experts and scholars in different fields of testing, this edited volume expands on the current literature base by including examples of detailed research findings arrived at by statistical methodology. It also provides a synthesis of the current state of the art with regard to the statistical detection of testing infidelity, particularly for large-scale assessments. By presenting methods currently used by testing organizations and research on new methods, the volume offers an important forum for expanding the literature in this area"--

There has been an increase in awareness (and perhaps occurrence) of individual and organized cheating on tests. Recent reports of widespread problems with state student accountability tests and teacher certification testing have raised questions about the very validity of assessment programs. While there are several books that specifically detail the issues of test security cheating on assessments, few outline the statistical procedures used for detecting various types of potential test fraud and the associated research findings. Without a significant research literature base, the new generation of researchers will have little opportunity or incentive to improve on existing methods.

Enlisting a variety of experts and scholars in different fields of testing, this edited volume expands on the current literature base by including examples of detailed research findings arrived at by statistical methodology. It also provides a synthesis of the current state of the art with regard to the statistical detection of testing infidelity, particularly for large-scale assessments. By presenting methods currently used by testing organizations and research on new methods, the volume offers an important forum for expanding the literature in this area.

List of Figures
xiii
List of Tables
xv
1 Introduction
1(3)
Neal M. Kingston
Amy K. Clark
2 A Brief History of Research on Test Fraud Detection and Prevention
4(4)
Amy K. Clark
Neal M. Kingston
3 Cheating: Some Ways to Detect it Badly
8(15)
Howard Wainer
PART I Similarities in Response Patterns
4 Relationships of Examinee Pair Characteristics and Item Response Similarity
23(15)
Jeff Allen
5 A Parametric Approach to Detect a Disproportionate Number of Identical Item Responses on a Test
38(15)
Leonardo S. Sotaridona
Arianto Wibowo
Irene Hendrawan
6 Detection of Non-independent Test Taking by Similarity Analysis
53(30)
Dennis Maynes
PART II Macro Level Cheating
7 Local Outlier Detection in Data Forensics: Data Mining Approach to Flag Unusual Schools
83(18)
Mayuko Simon
8 Macro Level Systems of Statistical Evidence Indicative of Cheating
101(20)
Michael Chajewski
Youngkoung Kim
Judit Antal
Kevin Sweeney
9 A Bayesian Hierarchical Linear Modeling Approach for Detecting Cheating and Aberrance
121(16)
William Skorupski
Karla Egan
PART III Answer Changing Behavior
10 Patterns of Examinee Erasure Behavior for a Large-Scale Assessment
137(12)
Andrew A. Mroch
Yang Lu
Chi-Yu Huang
Deborah J. Harris
11 AYP Consequences and Erasure Behavior
149(9)
Vincent Primoli
12 An Exploration of Answer Changing Behavior on a Computer-Based High-Stakes Achievement Test
158(17)
Gail C. Tiemann
Neal M. Kingston
PART IV Detection of Aberrant Responses
13 Identifying Non-Effortful Student Behavior on Adaptive Tests: Implications for Test Fraud Detection
175(11)
Steven L. Wise
Lingling Ma
Robert A. Theaker
14 A Method for Measuring Performance Inconsistency by Using Score Differences
186(17)
Dennis Maynes
PART V Multiple Methods of Detection
15 Data Forensics: A Compare-and-Contrast Analysis of Multiple Methods
203(17)
Christie Plackner
Vincent Primoli
16 Using Multiple Methods to Detect Aberrant Data
220(10)
Karla L. Egan
Jessalyn Smith
17 Test Security for Multistage Tests: A Quality Control Perspective
230(9)
Charles Lewis
Yi-Hsuan Lee
Alina A. Von Davier
Appendix A 239(4)
Appendix B 243(4)
Appendix C 247(2)
References 249(10)
Contributors 259(6)
Index 265
Neal Kingston is the Director of the Achievement and Assessment Institute, Co-Director of the Center for Educational Testing and Evaluation, and Professor of Educational Psychology at the University of Kansas. He has managed all aspects of the educational testing process for both general and alternate assessments, including as an Executive Director at Educational Testing Service, Associate Commissioner for Curriculum and Assessment at the Kentucky Department of Education, Senior Vice President at Measured Progress, Vice President and General Manager at CTB/McGraw-Hill, and Director of CETE at the University of Kansas. He has published and presented more than 100 articles, papers, and book chapters on assessment.



Amy Clark is a Research Associate in psychometrics at the Center for Educational Testing and Evaluation at the University of Kansas. She began her career as a classroom teacher and received both her M.S and Ph.D. in Educational Psychology from the University of Kansas specializing in Research, Evaluation, Measurement, and Statistics. Her research interests include exploring potential threats to validity, accountability issues, and diagnostic assessment.