A Human-Machine Interaction Model: Information Throughput and Weighting with Application to Multiple-Attribute-Task-Battery

Chandler A. Phillips, Rachel E. Kinsler, Daniel W. Repperger, Jayishnu Mandal, Amy T. Neidhard-Doll, David M. Kender

Research output: Contribution to journalArticlepeer-review

Abstract

The Multiple-Attribute-Task-Battery (MATB) displays five independent and concurrent tasks to which a human operator (HO) responds. MATB records the task-specific responses and so provides data on human performance. A general strategy function based on five task-specific strategy cases is described to characterise the human–MATB interaction. A prior report evaluated an implicit strategy group of 32 HOs for whom no strategy-important information was provided (i.e. all tasks are equally important). However, a specified strategy function did not characterise the group. This report evaluates an explicit strategy group of 35 HOs for whom the actual weighting of the five tasks was provided. The general strategy function is applied to both groups and characterises two different strategies. With respect to ergonomic theory and practice, a generalised strategy function is defined and applied to the human–MATB interaction that characterises two different strategy types and also provides a metric for MATB system complexity across five independent tasks.

Original languageEnglish
Pages (from-to)379-401
Number of pages23
JournalTheoretical Issues in Ergonomics Science
Volume14
Issue number4
DOIs
StatePublished - Jul 1 2013

ASJC Scopus Subject Areas

  • Human Factors and Ergonomics

Keywords

  • human-machine interaction
  • information processing
  • multiple tasking
  • Multiple-Attribute-Task-Battery
  • strategy function

Disciplines

  • Biomedical Engineering and Bioengineering
  • Industrial Engineering
  • Operations Research, Systems Engineering and Industrial Engineering

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