Examining the effects of passive and active strategy use during interactive search for lego bricks

Abstract

In many important search tasks, observers must find what they are looking for using only visual information (e.g., X-ray baggage screening/medical screening). However, numerous other search tasks can only be effectively completed when the searcher uses their hands to find what they are looking for (e.g., “rummage” search). Unfortunately, it is not currently well understood how observers conduct such “interactive” searches, nor what the best strategies might be for doing so. Here, we first review the limited literature on interactive search. We then present a novel methodology for the study of interactive search that involves having observers seek out Lego targets in a cluttered tray of assorted bricks. In our Validation Task, we confirm the validity of this approach by demonstrating that it produces sensible patterns of diminishing returns in response time as targets are removed from the set, as well as hastened search times for larger targets. In our Experiment, we modify the approach, refining its systematicity and experimental control. We also build on prior work exploring strategy use in visual search by investigating the extent to which active and passive strategy use impacts performance in interactive search. In contrast to our prior findings in hybrid visual search (Madrid & Hout, 2019), our current findings suggest that in interactive search, an active search strategy can be superior to a passive one. We close by offering a conceptual model (the Interactive Multiple Decision Model; i-MDM) that explicates the steps involved in a search task of this nature, and we then provide suggestions for how to further refine the task to achieve higher internal validity and to delve deeper into questions of theoretical importance in the field of interactive search.

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ORCID for Hayward Godwin: orcid.org/0009-0005-1232-500X

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