<?xml version="1.0" encoding="UTF-8" ?><xml><records><record><database name="!wdg&apos;s ref list_v8.enl" path="/Users/gray/Documents/!wdg&apos;s ref list_v8.enl">!wdg&apos;s ref list_v8.enl</database><source-app name="EndNote" version="10.0">EndNote</source-app><rec-number>2273</rec-number><ref-type name="Conference Paper">47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Neth, Hansjörg</style></author><author><style face="normal" font="default" size="100%">Khemlani, Sangeet S.</style></author><author><style face="normal" font="default" size="100%">Oppermann, Brittney</style></author><author><style face="normal" font="default" size="100%">Gray, Wayne D.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Juggling multiple tasks: A rational analysis of multitasking inn a synthetic task environment</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 50th annual meeting of the Human Factors and Ergonomics Society</style></secondary-title></titles><dates><year><style face="normal" font="default" size="100%">2006</style></year></dates><pub-location><style face="normal" font="default" size="100%">San Francisco, CA</style></pub-location><publisher><style face="normal" font="default" size="100%">HFES</style></publisher><abstract><style face="normal" font="default" size="100%">Tardast (Shakeri 2003; Shakeri &amp; Funk, in press) is a new and intriguing paradigm to investigate human multitasking behavior, complex system management, and supervisory control. We present a replication and extension of the original Tardast study that assesses operators’ learning curve and explains gains in performance in terms of increased sensitivity to task parameters and a superior ability of better operators to prioritize tasks. We then compare human performance profiles to various artificial software agents that provide benchmarks of optimal and baseline performance and illustrate the outcomes of simple heuristic strategies. Whereas it is not surprising that human operators fail to achieve an ideal criterion of performance, we demonstrate that humans also fall short of a principally achievable standard. Despite significant improvements with practice, Tardast operators exhibit stable sub-optimal performance in their time-to-task allocations.</style></abstract><urls><pdf-urls><url><style face="normal" font="default" size="100%">internal-pdf://NKOG_580_HFES06-1107683584/NKOG_580_HFES06.pdf</style></url></pdf-urls></urls></record></records></xml>