Levels of automation in a binary categorization task

Joachim Meyer

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Motivation - To study the effect of levels of automation on binary categorization decisions. Research approach - A laboratory experiment was conducted on 80 students, employing a simulated production control task that involved binary categorizations of situations. Findings/Design - The performance with the lower level of automation tended to be less affected by the quality of the aid and overall better than performance with the higher level of automation. Research limitations/Implications - The system is fairly abstract, and additional validation of the findings in more realistic settings may be desirable. Originality/Value - The study is one of a fairly small number of empirical studies on the effect of levels of automation on performance. Take away message - Lower levels of automation may actually lead to better results in a wide range of conditions.

Original languageEnglish
Title of host publicationECCE 2007 - European Conference on Cognitive Ergonomics
Subtitle of host publicationInvent Explore
Pages233-236
Number of pages4
DOIs
StatePublished - 1 Dec 2007
Event25th Anniversary Conference of the European Association for Cognitive Ergonomics, EACE - London, United Kingdom
Duration: 28 Aug 200731 Aug 2007

Publication series

NameACM International Conference Proceeding Series
Volume250

Conference

Conference25th Anniversary Conference of the European Association for Cognitive Ergonomics, EACE
Country/TerritoryUnited Kingdom
CityLondon
Period28/08/0731/08/07

Keywords

  • binary categorization decisions
  • levels of automation
  • signal detection

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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