Item Selection Algorithm Based on Collaborative Filtering for Item Exposure Control

In computerized adaptive testing, overexposure of items in the bank is a serious problem and might result in item compromise. We develop an item selection algorithm that utilizes the entire bank well and reduces the overexposure of items. The algorithm is based on collaborative filtering and selects...

Full description

Saved in:
Bibliographic Details
Published in:Educational measurement, issues and practice issues and practice, 2023-12, Vol.42 (4), p.6-18
Main Authors: Pan, Yiqin, Livne, Oren, Wollack, James A., Sinharay, Sandip
Format: Article
Language:English
Subjects:
Accuracy
Adaptive Testing
Algorithms
Computer Assisted Testing
computerized adaptive testing
Item Banks
Measurement
recommendation system
Test Items
test security
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In computerized adaptive testing, overexposure of items in the bank is a serious problem and might result in item compromise. We develop an item selection algorithm that utilizes the entire bank well and reduces the overexposure of items. The algorithm is based on collaborative filtering and selects an item in two stages. In the first stage, a set of candidate items whose expected performance matches the examinee's current performance is selected. In the second stage, an item that is approximately matched to the examinee's observed performance is selected from the candidate set. The expected performance of an examinee on an item is predicted by autoencoders. Experiment results show that the proposed algorithm outperforms existing item selection algorithms in terms of item exposure while incurring only a small loss in measurement precision.
ISSN:0731-1745
1745-3992
DOI:10.1111/emip.12578