Characterizing the efficiency of collaborative visual search with systems factorial technology.

Professional tasks such as air traffic control and search-and-rescue often involve visual scanning. A novel technology known as gaze-sharing is intended to help people to scan in teams by allowing each of them to see where the other is looking. However, evidence for the helpfulness of shared-gaze displays has been mixed (Brennan, Chen, Dickinson, Neider, & Zelinsky, 2008; Neider, Chen, Dickinson, Brennan, & Zelinsky, 2010). The present study used a novel mathematical analysis to measure the scanning efficiency of teammates linked by the shared-gaze technology in a 2-person visual search-and-consensus task. Results show that shared gaze helped the second searchers find and confirm the target after the first searcher had spotted it, but increased the time for the first searcher to detect the target. Results imply limits on the value of the shared-gaze technology as a way to improve real-world visual search. S C I E N T I F I C A B S T R A C T Shared-gaze technology can improve paired individuals’ performance in challenging visual search tasks (Brennan et al., 2008; Neider et al., 2010). To better characterize collaborative search behavior, the current study measured parallel channel efficiency by workload capacity (Townsend & Nozawa, 1995) for pairs of searchers performing a speeded visual search task with or without shared-gaze cursors. Workload capacity was calculated based on the response time of the first searcher to report the target (CzOR) and based on the response time of the second searcher to report it (CzAND). Under shared-gaze conditions, CzAND scores indicated highly efficient performance, but CzOR scores indicated performance losses. Sharedgaze displays reduced the time necessary for the second searcher to confirm a target after the first searcher had found it, but increased the time needed for the first searchers’ target detection. Results imply limits on the benefits of shared gaze displays in difficult visual search tasks. This article was published April 24, 2017. Yusuke Yamani, Department of Psychology, Old Dominion University; Mark B. Neider, Department of Psychology, University of Central Florida; Arthur F. Kramer, Beckman Institute, University of Illinois; Jason S. McCarley, School of Psychology, Flinders University. Arthur F. Kramer is now at the Department of Psychology and Department of Mechanical and Industrial Engineering, Northeastern University. This research is supported by ARC Discovery DP150100661 (the Australian Research Council) awarded to Jason S. McCarley. Thanks to Cecil Reynolds, Carrick Williams, and Jim Townsend for helpful comments on an earlier version of the manuscript. Authors also thank Ron Carbonari for programming the experiment and John Powers, Connor Riggs, and Anya Knecht for data collection. The authors have made available for use by others the data that underlie the analyses presented in this paper (see Yamani, Neider, Kramer, & McCarley, 2017), thus allowing replication and potential extensions of this work by qualified researchers. Next users are obligated to involve the data originators in their publication plans, if the originators so desire. For further discussion on this topic, please visit the Archives of Scientific Psychology online public forum at http://arcblog.apa. org. Correspondence concerning this article should be addressed to Yusuke Yamani, Department of Psychology, Old Dominion University, 236B Mills Godwin Building, Norfolk, VA 23529. E-mail: yyamani@odu.edu Archives of Scientific Psychology 2017, 5, 1–9 © 2017 American Psychological Association DOI: http://dx.doi. org/10.1037/arc000003