MARC Record from Library of Congress

LEADER: 04353cam a2200373 i 4500
001 2013042510
003 DLC
005 20150702080313.0
008 140109s2014 nyu b 001 0 eng
010 $a 2013042510
020 $a9780415711241 (hardback)
040 $aDLC$beng$cDLC$erda$dDLC
042 $apcc
050 00 $aLB3609$b.T47 2014
082 00 $a371.5/8$223
084 $aEDU030000$aEDU009000$aEDU027000$2bisacsh
245 00 $aTest fraud :$bstatistical detection and methodology /$cedited by Neal M. Kingston and Amy K. Clark.
264 1 $aNew York :$bRoutledge,$c2014.
300 $axvi, 267 pages ;$c24 cm.
336 $atext$2rdacontent
337 $aunmediated$2rdamedia
338 $avolume$2rdacarrier
490 0 $aRoutledge research in education ;$v114
520 $a"There has been an increase in awareness (and perhaps occurrence) of individual and organized cheating on tests. Recent reports of widespread problems with state student accountability tests and teacher certification testing have raised questions about the very validity of assessment programs. While there are several books that specifically detail the issues of test security cheating on assessments, few outline the statistical procedures used for detecting various types of potential test fraud and the associated research findings. Without a significant research literature base, the new generation of researchers will have little opportunity or incentive to improve on existing methods.Enlisting a variety of experts and scholars in different fields of testing, this edited volume expands on the current literature base by including examples of detailed research findings arrived at by statistical methodology. It also provides a synthesis of the current state of the art with regard to the statistical detection of testing infidelity, particularly for large-scale assessments. By presenting methods currently used by testing organizations and research on new methods, the volume offers an important forum for expanding the literature in this area"--$cProvided by publisher.
504 $aIncludes bibliographical references and index.
505 0 $aIntroduction / Neal Kingston and Amy Clark -- A brief history of research on test fraud detection and prevention / Amy Clark and Neal Kingston -- Cheating : some ways to detect it badly / Howard Wainer -- Relationships of examinee pair characteristics and item response similarity / Jeff Allen -- A parametric approach to detect a disproportionate number of identical item responses on a test / Leonardo S. Sotaridona, Arianto Wibowo, and Irene Hendrawan -- detection of non-independent test taking by similarity analysis / Dennis Maynes -- Local outlier detection in data forensics : data mining approach to flag unusual schools / Mayuko Simon -- Macro level systems of statistical evidence indicative of cheating / Michael Chajewski, YoungKoung Kim, Judit Antal, and Kevin Sweeney -- A Bayesian hierarchical linear modeling approach for detecting cheating and aberrance / William Skorupski and Karla Egan -- Patterns of erasure behavior for a large-scale assessment / Andrew A. Mroch, Yang Lu, Chi-Yu Huang, and Deborah J. Harris -- AYP consequences and erasure behavior / Vincent Primoli -- An exploration of answer changing behavior on a computer-based high-stakes achievement test / Gail C. Tiemann and Neal M. Kingston -- Identifying non-effortful student behavior on adaptive tests : implications for test fraud detection / Steven L. Wise, Lingling Ma, and Robert A. Theaker -- A method for measuring performance inconsistency by using score differences / Dennis Maynes -- Data forensics : a compare-and-contrast analysis of multiple methods / Christie Plackner and Vincent Primoli -- Using multiple methods to detect aberrant data / Karla Egan and Jessalyn Smith -- Test security for multistage tests : a quality control perspective / Charles Lewis, Yi-Hsuan Lee and Alina A. von Davier.
650 0 $aCheating (Education)$xPrevention$xMethodology.
650 0 $aCheating (Education)$xPrevention$xStatistical methods.
650 0 $aEducational tests and measurements.
650 7 $aEDUCATION / Testing & Measurement.$2bisacsh
650 7 $aEDUCATION / Educational Psychology.$2bisacsh
650 7 $aEDUCATION / Statistics.$2bisacsh
700 1 $aKingston, Neal M.
700 1 $aClark, Amy K.