Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Investigating the cognitive load - productivity tradeoff in multitasking

Chis, Maximilian (2023) Investigating the cognitive load - productivity tradeoff in multitasking. Master's Thesis, University of Pittsburgh. (Unpublished)

[img]
Preview
PDF (2023_03_18)
Download (1MB) | Preview

Abstract

Although multitasking is considered solely to negatively impact performance, the majority of analyses of multitasking have been doing in experimental settings where the tasks analyzed are of a non-interdependent nature. I argue that multitasking as it occurs in the workforce is a highly complex task which balances multiple competing needs of logistical efficiency, cognitive load, and minimizaton of idle time. I examine this model of multitasking in the context of study 3 of the Artificial Social Intelligence for Successful Teams (ASIST) program, funded by the Defense Advanced Research Project Agency (DARPA). Though the study was not designed with multitasking in mind and thus has a number of confounds, enough evidence exists to suggest a number of probable reasons for the persistence of multitasking in modern life and the multiple "task axes" on which multitasking can occur.


Share

Citation/Export:
Social Networking:
Share |

Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Chis, Maximilianmac372@pitt.edumac372
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Thesis AdvisorLewis, Michaelcmlewis@pitt.edu
Committee MemberDu, Nanad136@pitt.edu
Committee MemberLebiere, Christian
Date: 17 August 2023
Date Type: Publication
Defense Date: 7 December 2022
Approval Date: 17 August 2023
Submission Date: 15 December 2022
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 91
Institution: University of Pittsburgh
Schools and Programs: School of Computing and Information > Information Science
Degree: MSIS - Master of Science in Information Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: Artificial Intelligence Cognitive Modeling
Date Deposited: 17 Aug 2023 17:34
Last Modified: 17 Aug 2023 17:34
URI: http://d-scholarship.pitt.edu/id/eprint/44036

Metrics

Monthly Views for the past 3 years

Plum Analytics


Actions (login required)

View Item View Item