Detecting Preknowledge Cheating via Innovative Measures: A Mixture Hierarchical Model for Jointly Modeling Item Responses, Response Times, and Visual Fixation Counts

Autor/inn/en	Man, Kaiwen; Harring, Jeffrey R.
Titel	Detecting Preknowledge Cheating via Innovative Measures: A Mixture Hierarchical Model for Jointly Modeling Item Responses, Response Times, and Visual Fixation Counts
Quelle	In: Educational and Psychological Measurement, 83 (2023) 5, S.1059-1080 (22 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Man, Kaiwen) ORCID (Harring, Jeffrey R.)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0013-1644
DOI	10.1177/00131644221136142
Schlagwörter	Cheating; Reaction Time; Test Items; Responses; Eye Movements; Behavior Patterns; Test Bias; Bayesian Statistics; College Students; Accuracy + Suchen Sie Ihr Suchwort? Prellen; Reaktionsvermögen; Test content; Testaufgabe; Augenbewegung; Testkritik; Collegestudent
Abstract	Preknowledge cheating jeopardizes the validity of inferences based on test results. Many methods have been developed to detect preknowledge cheating by jointly analyzing item responses and response times. Gaze fixations, an essential eye-tracker measure, can be utilized to help detect aberrant testing behavior with improved accuracy beyond using product and process data types in isolation. As such, this study proposes a mixture hierarchical model that integrates item responses, response times, and visual fixation counts collected from an eye-tracker (a) to detect aberrant test takers who have different levels of preknowledge and (b) to account for nuances in behavioral patterns between normally-behaved and aberrant examinees. A Bayesian approach to estimating model parameters is carried out via an MCMC algorithm. Finally, the proposed model is applied to experimental data to illustrate how the model can be used to identify test takers having preknowledge on the test items. (As Provided).
Anmerkungen	SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01