Latent-variable Approaches Utilizing Both Item Scores and Response Times To Detect Test Fraud

Latent-variable Approaches Utilizing Both Item Scores and Response Times To Detect Test Fraud

There is a growing interest in approaches based on latent-variable models for detecting fraudulent behavior on educational tests. Wollack and Schoenig (2018) noted the presence of five types of statistical/psychometric approaches to detect the three broad types of test fraud that occur in educationa...

Full description

Bibliographic Details
Main Author: Sinharay Sandip
Format: Article
Language:English
Published: De Gruyter 2021-01-01
Series:Open Education Studies
Subjects:
chi-bar-square distribution
likelihood ratio statistic
wald statistic
Online Access:https://doi.org/10.1515/edu-2020-0137
id doaj-e49bcd5ede9040de834fe356ca74d134
record_format Article
spelling doaj-e49bcd5ede9040de834fe356ca74d1342021-09-22T06:13:06ZengDe GruyterOpen Education Studies2544-78312021-01-013111610.1515/edu-2020-0137Latent-variable Approaches Utilizing Both Item Scores and Response Times To Detect Test FraudSinharay Sandip0Educational Testing Service, Princeton, NJ, United StatesThere is a growing interest in approaches based on latent-variable models for detecting fraudulent behavior on educational tests. Wollack and Schoenig (2018) noted the presence of five types of statistical/psychometric approaches to detect the three broad types of test fraud that occur in educational tests. This paper includes a brief review of the five types of statistical/psychometric approaches mentioned by Wollack and Schoenig (2018). This paper then includes a more detailed review of the recent approaches for detecting test fraud using both item scores and response times—all of these approaches are based on latent-variable models. A real data example demonstrates the use of two of the approaches.https://doi.org/10.1515/edu-2020-0137chi-bar-square distributionlikelihood ratio statisticwald statistic
collection DOAJ
language English
format Article
sources DOAJ
author Sinharay Sandip
spellingShingle Sinharay Sandip
Latent-variable Approaches Utilizing Both Item Scores and Response Times To Detect Test Fraud
Open Education Studies
chi-bar-square distribution
likelihood ratio statistic
wald statistic
author_facet Sinharay Sandip
author_sort Sinharay Sandip
title Latent-variable Approaches Utilizing Both Item Scores and Response Times To Detect Test Fraud
title_short Latent-variable Approaches Utilizing Both Item Scores and Response Times To Detect Test Fraud
title_full Latent-variable Approaches Utilizing Both Item Scores and Response Times To Detect Test Fraud
title_fullStr Latent-variable Approaches Utilizing Both Item Scores and Response Times To Detect Test Fraud
title_full_unstemmed Latent-variable Approaches Utilizing Both Item Scores and Response Times To Detect Test Fraud
title_sort latent-variable approaches utilizing both item scores and response times to detect test fraud
publisher De Gruyter
series Open Education Studies
issn 2544-7831
publishDate 2021-01-01
description There is a growing interest in approaches based on latent-variable models for detecting fraudulent behavior on educational tests. Wollack and Schoenig (2018) noted the presence of five types of statistical/psychometric approaches to detect the three broad types of test fraud that occur in educational tests. This paper includes a brief review of the five types of statistical/psychometric approaches mentioned by Wollack and Schoenig (2018). This paper then includes a more detailed review of the recent approaches for detecting test fraud using both item scores and response times—all of these approaches are based on latent-variable models. A real data example demonstrates the use of two of the approaches.
topic chi-bar-square distribution
likelihood ratio statistic
wald statistic
url https://doi.org/10.1515/edu-2020-0137
work_keys_str_mv AT sinharaysandip latentvariableapproachesutilizingbothitemscoresandresponsetimestodetecttestfraud
_version_ 1717371886192558080

Similar Items