Examining cue recognition across expertise using a computer-based task

Abstract

Motivation-The study examined whether experts and novices differed in their recognition of decisionmaking cues. Research approach-To test cue recognition, the authors developed and tested a computer-based cue recognition task on a group of expert and novice offender profilers. Findings/Design-Recognition performance was assessed in relation to cue classification agreement and recognition response latency among and between the two groups. The findings revealed superior performance on both measures by the experts compared to the novices. Research limitations/Implications-The findings have implications for the cue selection process in the design of computer-based training, and decision support systems. Originality/Value-The research offers an objective means of: 1) identifying cues; 2) gauging relative cue stability/strength; 3) comparing cue recognition across expertise; and, 4) selecting a valid cue-set for use in training and support systems. Take away message-There are significant differences in cue recognition across expertise that may, in part, differentiate decision-making performance.

Cue Utilization and Broad Indicators of Workplace Expertise

“…The stimuli used in this task are provided in Appendix B. Since the utilization of cues requires refined and efficient associations between features and events, participants with a relatively higher level of cue utilization display more nuance in their ratings between items (Loveday, Wiggins, Harris, et al, 2013;Morrison, Wiggins, Bond, & Tyler, 2009;Schvaneveldt, Beringer, & Lamonica, 2001). This ability can be expressed mathematically by the variance of the participants' responses, with greater variance indicative of greater recognition of the precise relatedness of individual feature and event pairs.…”

The Capability of Static and Dynamic Features to Distinguish Competent From Genuinely Expert Practitioners in Pediatric Diagnosis

“…The PAT measures the perceived strength of association between features and outcomes in the domain by presenting domainrelevant word pairs and measuring response latency or ratings of relatedness (Morrison, Wiggins, Bond, & Tyler, 2009). Experts who possess more nuanced and refined featureevent cue associations in memory respond faster and with greater variance to pairs than nonexperts, for whom all pairs are similarly associated (Ackerman & Rathburn, 1984;Schvaneveldt, Beringer, & Lamonica, 2001).…”

The Relationship Between Pre-Flight Decision-Making and Cue Utilization

“…To establish the utilization of cues amongst pilots, two tasks were selected, the first of which was a paired association tasks based on Morrison, Wiggins, Bond, & Tyler (2009). In this case, features extracted during a cognitive interview were presented in pairs, and participants were asked to indicate, using a seven-point Likert scale, the relationship between feature pairs.…”

“…In this case, features extracted during a cognitive interview were presented in pairs, and participants were asked to indicate, using a seven-point Likert scale, the relationship between feature pairs. Both the response and the latency were recorded, and previous research suggests that experts tend to record lower response latencies and a greater variance of responses in comparison to non-experts (Morrison et al, 2009).…”