Title

Predicting And Interpreting Identification Errors In Military Vehicle Training Using Multidimensional Scaling

Keywords

incidental learning; multidimensional scaling; training; vehicle identification

Abstract

We compared methods for predicting and understanding the source of confusion errors during military vehicle identification training. Participants completed training to identify main battle tanks. They also completed card-sorting and similarity-rating tasks to express their mental representation of resemblance across the set of training items. We expected participants to selectively attend to a subset of vehicle features during these tasks, and we hypothesised that we could predict identification confusion errors based on the outcomes of the card-sort and similarity-rating tasks. Based on card-sorting results, we were able to predict about 45% of observed identification confusions. Based on multidimensional scaling of the similarity-rating data, we could predict more than 80% of identification confusions. These methods also enabled us to infer the dimensions receiving significant attention from each participant. This understanding of mental representation may be crucial in creating personalised training that directs attention to features that are critical for accurate identification.Practitioner Summary: Participants completed military vehicle identification training and testing, along with card-sorting and similarity-rating tasks. The data enabled us to predict up to 84% of identification confusion errors and to understand the mental representation underlying these errors. These methods have potential to improve training and reduce identification errors leading to fratricide. © 2014 © 2014 Taylor & Francis.

Publication Date

1-1-2014

Publication Title

Ergonomics

Volume

57

Issue

6

Number of Pages

844-855

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1080/00140139.2014.899631

Socpus ID

84901692564 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84901692564

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