Graduate Thesis Or Dissertation
 

Metacognition, Numeracy, and Automation-aided Decision-making

Public Deposited

Downloadable Content

Download PDF
Request Accessible Version
https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/n583z111s

Descriptions

Attribute NameValues
Creator
Abstract
  • Automated decision aids can improve human decision-making but the benefits are often compromised by inefficient use. The current experiment examined whether metacognition—the ability to assess self-performance—and numeracy—the ability to understand and work with numbers—predict the efficiency of automation use in a signal detection task. Two-hundred twenty-one participants classified random dot images as blue or orange dominant, receiving assistance from an 84% reliable decision aid on some trials. Type 1 and metacognitive signal detection measures were estimated from participants’ confidence ratings, and numeracy was measured using a subjective scale. The inefficiency of automation use was assessed by measuring the deviation from optimal bias following cues from the aid (bias error). Data gave strong evidence that metacognition was not associated with bias error, and anecdotal evidence that numeracy and suboptimality were weakly negatively correlated. These results suggest that operators used a strategy of combining the aid’s judgments with their own that is not metacognitively driven, but may depend on numeracy.
License
Resource Type
Date Issued
Degree Level
Degree Name
Degree Field
Degree Grantor
Commencement Year
Advisor
Committee Member
Academic Affiliation
Rights Statement
Publisher
Peer Reviewed
Language
Accessibility Feature

Relationships

Parents:

This work has no parents.

In Collection:

Items

Thumbnail Title Date Uploaded Visibility Actions
file details GylesShannonP2019.pdf 2019-06-14 Public Download