Open AccessAssessing Preknowledge Cheating via Innovative Measures: A Multiple-Group Analysis of Jointly Modeling Item Responses, Response Times, and Visual Fixation Counts
Author(s) -
Kaiwen Man,
Jeffrey R. Harring
Publication year - 2020
Publication title -
educational and psychological measurement
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.819
H-Index - 95
eISSN - 1552-3888
pISSN - 0013-1644
DOI - 10.1177/0013164420968630
Subject(s) - item response theory , cheating , fixation (population genetics) , bayesian probability , psychology , context (archaeology) , eye tracking , computer science , test (biology) , statistics , artificial intelligence , machine learning , cognitive psychology , social psychology , psychometrics , developmental psychology , mathematics , population , paleontology , demography , sociology , biology
Many approaches have been proposed to jointly analyze item responses and response times to understand behavioral differences between normally and aberrantly behaved test-takers. Biometric information, such as data from eye trackers, can be used to better identify these deviant testing behaviors in addition to more conventional data types. Given this context, this study demonstrates the application of a new method for multiple-group analysis that concurrently models item responses, response times, and visual fixation counts collected from an eye-tracker. It is hypothesized that differences in behavioral patterns between normally behaved test-takers and those who have different levels of preknowledge about the test items will manifest in latent characteristics of the different data types. A Bayesian estimation scheme is used to fit the proposed model to experimental data and the results are discussed.