Topic: Selection, Evidence Based Management, Assessment
Publication: International Journal of Selection and Assessment (JUN 2012)
Article: Offsetting Performance Losses Due to Cheating in Unproctored Internet-Based Testing by Increasing the Applicant Pool
Authors: Richard N. Landers & Paul R. Sackett
Reviewed By: Thaddeus Rada
Unproctored Internet testing (UIT) has been a hot topic in IO psychology over the past several years. In a nutshell, UIT allows organizations to post some of their selection tests online, allowing applicants to access them from virtually anywhere, so they can complete them on their own time. Some of the research on UIT has confirmed its strengths, such as its accessibility and efficiency, but other research has highlighted some of its limitations; in particular, there remains widespread concern about cheating in UIT. Because UIT is unproctored (it’s right there in the name), applicants are not under any supervision when they take such tests, so it’s possible that cheating could occur in a wide variety of ways.
While many authors have debated the extent to which cheating in UIT is a problem (e.g., how prevalent it is, how to cope with it, etc.), Landers and Sackett argue that if UIT increases the size of the applicant pool, even if some of these individuals do cheat, the organization may still derive benefit from a UIT program. Their logic goes something like this: if an organization is only looking to hire a set number of people (e.g., 50), then increasing the size of the applicant pool allows the organization to increase the cut score that an individual needs to exceed in order to be hired, thus making it harder for cheaters to get job offers. To test their ideas, Landers and Sackett conducted a computer simulation, which confirmed their belief in the power of a large applicant pool to compensate for some of UIT’s limitations.
While it does not remove all the concerns that exist about UIT, Landers and Sackett’s study does demonstrate that some of UIT’s benefits outweigh its limitations. This study’s findings hinge, to a large extent, on the capacity of a UIT intervention to increase the size of the applicant pool. As such, the authors suggest that practitioners carefully assess whether or not they anticipate that this will be the case before recommending that an organization adopt UIT.
Landers, R. N., & Sackett, P. R. (2012). Offsetting performance losses due to cheating in unproctored Internet-based testing by increasing the applicant pool. International Journal of Selection and Assessment, 20, 220-228.
human resource management, organizational industrial psychology, organizational management