The rising reliance on testing in American education and for licensure and certification has
been accompanied by an escalation in cheating on tests at all levels. Edited by two of the …

Complex interactive test items are becoming more widely used in assessments. Being
computer-administered, assessments using interactive items allow logging time-stamped …

Researchers frequently use machine-learning methods in many fields. In the area of
detecting fraud in testing, there have been relatively few studies that have used these …

As technologies have been improved, item preknowledge has become a common concern
in the test security area. The present study proposes an unsupervised‐learning‐based …

The detection of examinees who have previously accessed proprietary test content is a
primary concern in the context of test security. Researchers have proposed using item …

Abstract Machine learning has evolved and expanded as an interdisciplinary research
method for educational sciences. However, cheating detection of test collusion among …

The earliest efforts for detecting preknowledge involve the use of person-fit statistics. A
person-fit statistic detects item score patterns that are unlikely given the item response …

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 …

Test collusion (TC) is sharing of test materials or answers to test questions before or during
the test (important special case of TC is item preknowledge). Because of potentially large …

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 …