The use of mobile assessment in personnel selection is an increasing trend that offers benefits to job applicants and organizations, including increased convenience of testing and expanded applicant pools (Tippins, 2011). Fewer than 10 published studies have examined the measurement equivalence of pre-employment cognitive ability assessments administered over mobile compared to non-mobile devices. Some of this research has found evidence of measurement equivalence and no score differences across device types while other studies contradict these results (Arthur et al., 2017). The present study is the first to investigate the measurement equivalence of a mobile-delivered, adaptively administered pre-hire cognitive ability assessment. This study is also the first to investigate how a specific item characteristic, item scrolling requirement (i.e., if scrolling is required to view the entire item or not), impacts mobile test functioning. Archival operational data from a large national restaurant chain was obtained to conduct differential item functioning (DIF) analyses of mobile cognitive assessment items completed by job applicants for five different roles. Mean assessment scores were significantly lower for applicants who completed the assessment on a mobile device compared to a non-mobile device. Item scrolling requirements were not found to predict DIF across mobile and non-mobile devices. Regarding practical implications, a number of mobile cognitive assessment best practices are presented, including ensuring tests are evaluated for measurement equivalence and adverse impact prior to administration. It is hoped that future research will investigate the criterion-related validity and adverse impact potential of static and adaptive mobile assessments.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-1317 |
| Date | 01 January 2020 |
| Creators | Zemen, Betsir |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations, 2020- |
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