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oai:www.ideals.illinois.edu:2142/82114 2023-07-11 col_2142_5131 col_2142_11614 com_2142_5130 com_2142_11613 com_2142_8903

Jason McCarley Dixon, Stephen R. 2015-09-25T20:39:14Z 2015-09-25T20:39:14Z 10000-01-01 2006 2006 We report three experiments that examine the effects of imperfect automation on operator trust and dependence. By manipulating the automation bias to either present false alarms or misses, the data reveal patterns of operator behavior consistent with a multiple-process cognitive model that allows non-selective effects of automation errors on operator behavior. These non-selective effects were eliminated by reducing the salience of the automation errors. Made available in DSpace on 2015-09-25T20:39:14Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3242835.pdf: 3988743 bytes, checksum: c550bc726bbf248a42b615684982c56b (MD5) Previous issue date: 2006 Embargo set by: Seth Robbins for item 83395 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs U of I Only 119 p. Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2006. http://hdl.handle.net/2142/82114 (MiAaPQ)AAI3242835 eng Psychology, Experimental Imperfect Diagnostic Automation: How Adjusting Bias and Saliency Affects Operator Trust text Psychology Psychology University of Illinois at Urbana-Champaign Dissertation Ph.D.