The Impact of Emerging Technologies on Selection Models and Research

Arthur, Winfred; Doverspike, Dennis; Kinney, Ted B.; O’Connell, Matthew S.

doi:10.4324/9781315690193-44

Cited by 8 publications

(7 citation statements)

References 1 publication

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“…As a final example, Arthur, Doverspike, Kinney, and O'Connell (2017) provide a strong note of caution regarding game-thinking in selection contexts, pointing out that job candidates are likely already highly motivated and so the enhanced engagement which game elements are meant to deliver may not have appreciable effects. Further, game mechanics related to the value of feedback may have negative consequences such as increased anxiety (Arthur et al, 2017). Hawkes et al (2018) go so far as to note that the reliability of game assessments may be affected negatively by practice effects such as those seen in the gaming world or by adding noisy variance associated with hand-eye coordination and mouse control.…”

Section: Effects Of Contextual Enhancementmentioning

confidence: 99%

“…There is ample research available to indicate that some measures are equivalent across modes (non-cognitive tests; see review by Tippins, 2015) and others are not (e.g., speeded cognitive tests; King, Ryan, Kantrowitz, Grelle, & Dainis, 2015;Mead & Drasgow, 1993). For example, non-cognitive measures may be equivalent when moving from PC to mobile assessment but cognitive measures and SJTs might not, depending on features like scrolling… (see Arthur et al, 2017;King et al, 2015 for comparisons). Morelli, Potosky, Arthur, and Tippins (2017) note that "reactive equivalence" studies comparing assessment modes are not theoretically (or even practically) informative as they do not address why mode differences occur or the reasons for the construct non-equivalence.…”

Section: Effects Of Efficiencymentioning

confidence: 99%

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The Unrealized Potential of Technology in Selection Assessment

Ryan

Derous

2019

Revista De Psicología Del Trabajo Y De Las Organizaciones

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The Unrealized Potential of Technology in Selection Assessment Over the past two decades, assessment for employee selection has undergone radical changes due to technological advances (see Tippins, 2015, for a review). Examples include changes in assessment delivery (computerized, online, mobile, use of adaptive testing), changes in assessment content (greater use of video and audio, graphics, gamification), changes in interactivity (recording of applicants, video interviewing), changes in scoring and reporting (quicker, internet delivered), and changes in many other aspects (e.g., use of algorithms and data mining). The purpose of this paper is not to provide another review of these advances as quality treatments exist (Scott, Bartram, & Reynolds, 2017; Tippins, 2015) but to discuss 3 ways incorporation and use of technological advances in assessment practice and research could be strengthened. First, we discuss the need to think more creatively regarding what is measured. That is, despite the promise of technology as a means of measuring new KSAOs (i.e., knowledge, skills, abilities, and other constructs like motivation) and richer content, many of our assessments are just "transported" traditional tools. As an example, gamified assessments (Bhatia & Ryan, 2018) most often are measuring traditional constructs in environments with game elements layered on.

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Section: Effects Of Contextual Enhancementmentioning

confidence: 99%

Section: Effects Of Efficiencymentioning

confidence: 99%

The Unrealized Potential of Technology in Selection Assessment

Ryan

Derous

2019

Revista De Psicología Del Trabajo Y De Las Organizaciones

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“…It is also worth noting that the tenets of the SCIP framework are not necessarily limited to UIT devices; and indeed, they can conceptually inform discussions of a wider range of assessments, particularly in any domain in which construct-irrelevant information processing demands associated with the testing method or medium are pertinent. For instance, the SCIP framework would be germane in the context of other technologically mediated assessment methods, such as virtual roleplays, immersive simulations, and gamified assessments (Arthur, Doverspike, Kinney, & O'Connell, 2017). As another example, one could envisage characteristics associated with situational judgment tests (e.g., item length, complexity of instructions, response format, presentation mode [paper-and-pencil vs. video]) that could very well engender differential construct-irrelevant cognitive load, which then results in differential test scores (Arthur et al, 2014;Chan & Schmitt, 1997).…”

Section: Arthur Keiser and Doverspike's (2017) Scip Frameworkmentioning

confidence: 99%

A Call for Conceptual Models of Technology in I-O Psychology: An Example From Technology-Based Talent Assessment

Morelli¹,

Potosky

Arthur

et al. 2017

Ind. Organ. Psychol.

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The rate of technological change is quickly outpacing today's methods for understanding how new advancements are applied within industrial-organizational (I-O) psychology. To further complicate matters, specific attempts to explain observed differences or measurement equivalence across devices are often atheoretical or fail to explain why a technology should (or should not) affect the measured construct. As a typical example, understanding how technology influences construct measurement in personnel testing and assessment is critical for explaining or predicting other practical issues such as accessibility, security, and scoring. Therefore, theory development is needed to guide research hypotheses, manage expectations, and address these issues at this intersection of technology and I-O psychology. This article is an extension of a Society for Industrial and Organizational Psychology (SIOP) 2016 panel session, which (re)introduces conceptual frameworks that can help explain how and why measurement equivalence or nonequivalence is observed in the context of selection and assessment. We outline three potential conceptual frameworks as candidates for further research, evaluation, and application, and argue for a similar conceptual approach for explaining how technology may influence other psychological phenomena.

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“…As a result, applicants are afforded the opportunity to complete employment‐related tests and assessments in virtually any location and using any device of their choosing. Consistent with the persistent rise in mobile device ownership among the general population (Pew Research Center, 2015, 2019), the use of mobile devices for unproctored employment‐related testing has become increasingly commonplace (Arthur et al., 2017, 2018). Although several advantages associated with UIT have been proffered, the seemingly unrestricted internet access permitted by new technologies also raises concerns regarding potential device‐type effects on the observed scores of UITs.…”

Section: Introductionmentioning

confidence: 99%

The testing environment as an explanation for unproctored internet‐based testing device‐type effects

Traylor

Hagen

Williams

et al. 2020

Int J Selection Assessment

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Device‐type effects on cognitive tests appear to covary with whether unproctored internet‐based test (UIT) scores were obtained operationally or nonoperationally. The present study examined whether the testing environment and distractions therein—one of three contextual factors identified as plausible explanations—accounts for this covariation. Four‐hundred and twenty‐five college students were randomly assigned to one of three conditions which differed by the testing environment and device used to complete a cognitive test. Test scores did not differ between conditions despite greater distractions reported by those who tested in the distracting environment. Results were replicated within‐study, and suggest that the self‐selection and testing‐stakes hypotheses warrant subsequent empirical examination as explanations for the differences in device‐type effects observed in operational and nonoperational settings.

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The Impact of Emerging Technologies on Selection Models and Research

Cited by 8 publications

References 1 publication

The Unrealized Potential of Technology in Selection Assessment

The Unrealized Potential of Technology in Selection Assessment

A Call for Conceptual Models of Technology in I-O Psychology: An Example From Technology-Based Talent Assessment

The testing environment as an explanation for unproctored internet‐based testing device‐type effects

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