Show and tell: Testing an alternative simulation-based method for assessing demonstrated soft skills

There is growing recognition that enhanced soft skill acquisition and development are critical for society and its members to adapt to the changes associated with the future of work in Canada, Soft skills in a work context are commonly measured in interviews, but this method has its drawbacks as there is the possibility for interviewer bias and interviewee faking, both of which could skew the assessment of skills in interviews. To circumvent these issues, nugget.ai developed an online simulation-based method for screening soft skills. The nugget.ai app places assessment takers in a simulation that replicates the job context and the work duties that are typically associated with it. nugget.ai differs from common assessment companies such as Hogan and plum.io in that it invites assessment takers to demonstrate their knowledge, skills, and abilities instead of relying on self-report methods. This method allows nugget.ai to assess soft-skills while minimizing the issues associated with typical methods of assessing soft skills such as interviews. With this proposed research, we aim to test the validity and reliability of nugget.ai’s simulation-based soft skill screening method, in hopes of promoting the use of a more valid and reliable hiring tool to organizations.

Faculty Supervisor:

Peter Hausdorf

Student:

Marian Pitel;Melissa Pike

Partner:

nugget.ai

Discipline:

Psychology

Sector:

Professional, scientific and technical services

University:

University of Guelph