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Examining cue recognition across expertise using a computer-based task
Author(s) -
Ben W. Morrison,
Mark W. Wiggins,
Nigel W. Bond,
Michael D. Tyler
Publication year - 2009
Publication title -
electronic workshops in computing
Language(s) - English
Resource type - Conference proceedings
ISSN - 1477-9358
DOI - 10.14236/ewic/ndm2009.8
Subject(s) - task (project management) , computer science , set (abstract data type) , selection (genetic algorithm) , originality , psychology , cognitive psychology , artificial intelligence , social psychology , engineering , systems engineering , programming language , creativity
Motivation - The study examined whether experts and novices differed in their recognition of decision-making 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.

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