ERIC Number: EJ1371341
Record Type: Journal
Publication Date: 2023
Pages: 23
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0731-1745
EISSN: EISSN-1745-3992
A Machine Learning Approach for the Simultaneous Detection of Preknowledge in Examinees and Items When Both Are Unknown
Pan, Yiqin; Wollack, James A.
Educational Measurement: Issues and Practice, v42 n1 p76-98 Spr 2023
Pan and Wollack (PW) proposed a machine learning method to detect compromised items. We extend the work of PW to an approach detecting compromised items and examinees with item preknowledge simultaneously and draw on ideas in ensemble learning to relax several limitations in the work of PW. The suggested approach also provides a confidence score, which is based on an autoencoder to represent our confidence that the detection result truly corresponds to item preknowledge. Simulation studies indicate that the proposed approach performs well in the detection of item preknowledge, and the confidence score can provide helpful information for users.
Descriptors: Artificial Intelligence, Prior Learning, Item Analysis, Test Content, Test Items, Knowledge Level, Informed Consent
Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://bibliotheek.ehb.be:2191/en-us
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A