Examining the Potential Pitfalls of Using ChatGPT in Situational Judgment Tests

Selecting the ideal employee or trainee can be a difficult task. A situational judgement test (SJTs) is one type of test that can help identify the best applicants. However, due to the open-ended nature of such a test, test-takers may be able to use online tools or resources like ChatGPT to cheat and fake their answers. Currently, little to no research has looked at how ChatGPT may affect SJTs as the use of ChatGPT in everyday life is new to many people. The proposed project aims to examine these potential affects, as well as potential tools to identify those who may have cheated. This will benefit both Acuity Insights by providing a starting point to identify those who fake using ChatGPT, and more generally provide much needed insights into the affects of using ChatGPT in open-ended selection tests, such as SJTs.

Faculty Supervisor:

Nicolas Roulin

Student:

Partner:

Acuity Insights

Discipline:

Sociology

Sector:

Education; Professional, scientific and technical services

University:

Saint Mary's University

Program: