Using Highlighting to Train Attentional Expertise

• NCJ Number: 250069
• Journal: PLoS ONE Volume: 11 Issue: 1 Dated: January 2016
• Author(s): B. Roads; M. C. Mozer; T. A. Busey
• Date Published: January 2016
• Length: 0 pages
• Grant Number(s): 2009-DN-BX-K226
• Agencies: NIJ-Sponsored
• Publication Type: Research Paper; Research (Applied/Empirical); Report (Study/Research); Report (Grant Sponsored)

Annotation

Since acquiring expertise in complex visual tasks is time consuming, this article proposes an attentional highlighting paradigm to facilitate the efficient training of novices on where to look in these tasks.

Abstract

Highlighting involves dynamically modulating the saliency of a visual image to guide attention along the fixation path of a domain expert who had previously viewed the same image. Experiment 1 trained naive subjects via attentional highlighting on a fingerprint-matching task. Before and after training, subjects were asked to freely inspect images containing pairs of prints and determine whether the prints matched. Fixation sequences were automatically scored for the degree of expertise exhibited using a Bayesian discriminative model of novice and expert gaze behavior. Highlighted training causes gaze behavior to become more expert-like not only on the trained images but also on transfer images, indicating generalization of learning. Experiment 2 controlled for the possibility that the increase in expertise was due to mere exposure. Subjects were trained via highlighting of fixation sequences from novices, not experts, and observed no transition toward expertise. In Experiment 3, to determine the specificity of the training effect, it trained subjects with expert fixation sequences from images other than the one being viewed, which preserves coarse-scale statistics of expert gaze but provides no information about fine-grain features. Observing at least a partial transition toward expertise, the study obtained only weak evidence that the highlighting procedure facilitates the learning of critical local features. Possible improvements to the highlighting procedure are discussed. (Publisher abstract modified)