This exam cheating index (collusion detection) simply calculates the number of errors in common between a given pair of examinees. For example, two examinees got 80/100 correct, meaning 20 errors, and they answered all of the same questions wrongly, the EIC would be 20. If they both scored 80/100 but had only 10 wrong questions in common, the EIC would be 10. There is no probabilistic evaluation that can be used to flag examinees, as with more advanced indices. In fact, it is used inside some other indices, such as Harpp & Hogan. However, this index could be of good use from a descriptive or investigative perspective.
Note that EIC is not standardized in any way, so its range and relevant flag cutoff will depend on the number of items in your test, and how much your examinee responses vary. For a 100-item test, you might want to set the flag at 10 items. But for a 30-item test, this is obviously irrelevant, and you might want to set it at 5 (because most examinees will probably not even get more than 10 errors).
Learn more about applying EIC with SIFT, a free software program for exam cheating detection and other assessment issues.
Nathan Thompson, PhD, is CEO and Co-Founder of Assessment Systems Corporation (ASC). He is a psychometrician, software developer, author, and researcher, and evangelist for AI and automation. His mission is to elevate the profession of psychometrics by using software to automate psychometric work like item review, job analysis, and Angoff studies, so we can focus on more innovative work. His core goal is to improve assessment throughout the world.
Nate was originally trained as a psychometrician, with an honors degree at Luther College with a triple major of Math/Psych/Latin, and then a PhD in Psychometrics at the University of Minnesota. He then worked multiple roles in the testing industry, including item writer, test development manager, essay test marker, consulting psychometrician, software developer, project manager, and business leader. He is also cofounder and Membership Director at the International Association for Computerized Adaptive Testing (iacat.org). He’s published 100+ papers and presentations, but his favorite remains https://scholarworks.umass.edu/pare/vol16/iss1/1/.
