research-article

Understanding multitasking through parallelized strategy exploration and individualized cognitive modeling

Authors:

Anthony J. HornofAuthors Info & Claims

CHI '14: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Pages 3885 - 3894

https://doi.org/10.1145/2556288.2557351

Published: 26 April 2014 Publication History

Abstract

Human multitasking often involves complex task interactions and subtle tradeoffs which might be best understood through detailed computational cognitive modeling, yet traditional cognitive modeling approaches may not explore a sufficient range of task strategies to reveal the true complexity of multitasking behavior. This study proposes a systematic approach for exploring a large number of strategies using a computer-cluster-based parallelized modeling system. The paper demonstrates the efficacy of the approach for investigating and revealing the effects of different microstrategies on human performance, both within and across individuals, for a time-pressured multimodal dual task. The modeling results suggest that multitasking performance is not simply a matter of interleaving cognitive and sensorimotor processing but is instead heavily influenced by the selection of subtask microstrategies.

References

[1]

Ballas, J., Heitmeyer, C., and Perez-Quinones, M. (1992). Evaluating two aspects of direct manipulation in advanced cockpits. In Proceedings of CHI, 127--134.

Digital Library

[2]

Brumby, D. P., Salvucci, D. D., and Howes, A. (2009). Focus on driving: How cognitive constraints shape the adaptation of strategy when dialing while driving. In Proceedings of CHI, 1629--1638.

Digital Library

[3]

Card, S. K., Moran, T. P., and Newell, A. (1983). The psychology of human-computer interaction. Hillsdale, NJ: Lawrence Erlbaum Associates.

Digital Library

[4]

Gluck, K. A., Stanley, C. T., Moore, L. R., Reitter, D., and Halbr�gge, M. (2010). Exploration for understanding in cognitive modeling. Journal of Arti'cial General Intelligence, 2(2), 88--107.

[5]

Gray, W. D. and Boehm-Davis, D. A. (2000). Milliseconds matter: An introduction to microstrategies and to their use in describing and predicting interactive behavior. J. Exp. Psychol.: Applied, 6(4), 322--335.

[6]

Halverson, T. and Hornof, A. J. (2011). A computational model of "active vision" for visual search in human-computer interaction. HumanComputer Interaction, 26, 285--314.

Digital Library

[7]

Hornof, A. J. and Zhang, Y. (2010). Task-constrained interleaving of perceptual and motor processes in a time-critical dual task as revealed through eye tracking. In Proceedings of the 10th International Conference on Cognitive Modeling, 97--102.

[8]

Hornof, Zhang, and Halverson (2010). Knowing where and when to look in a time-critical multimodal dual task. In Proceedings of CHI, 2103--2112.

Digital Library

[9]

Howes, A., Lewis, R. L., and Vera, A. (2009). Rational adaptation under task and processing constraints: Implications for testing theories of cognition and action. Psychological Review, 116(4), 717--751.

[10]

Janssen, C., Brumby, D., Dowell, J., Chater, N., and Howes, A. (2011). Identifying optimum performance trade-offs using a cognitively bounded rational analysis model of discretionary task interleaving. Topics in Cognitive Science, 3(1), 123--139.

[11]

Kieras, D. E. and Meyer, D. E. (1997). An overview of the EPIC architecture for cognition and performance with application to human-computer interaction. Human-Computer Interaction, 12(4), 391--438.

Digital Library

[12]

Kieras, D. E. and Meyer, D. E. (2000). The role of cognitive task analysis in the application of predictive models of human performance. In J. M. Schraagen, S. F. Chipman, V. L. Shalin, & V. Shalin (Eds.), Cognitive task analysis (pp. 237--260). Mahwah, NJ: Erlbsum.

[13]

Olson, R. L., Hanowski, R. J., Hickman, J. S., and Bocanegra, J. (2009). Driver distraction in commercial vehicle operations. Technical report #FMCSARRR-09-045. U.S. Dept. of Transportation.

[14]

Roberts, S. and Pashler, H. (2000). How persuasive is a good 't' A comment on theory testing. Psychological Review, 107(2), 358--367.

[15]

Richtel, M. (2009, December 6). Promoting the car phone, despite risks. New York Times. Retrieved from http://www.nytimes.com.

[16]

Salvucci, D. and Taatgen, N. (2008). Threaded cognition: An integrated theory of concurrent multitasking. Psychological Review, 115(1), 101--130.

[17]

Sanford, E. C. (1888). Personal equation. The American Journal of Psychology, 2(1), pp. 3--38.

[18]

Wickens, C. D. (2002). Multiple resources and performance prediction. Theoretical Issues in Ergonomics Science, 3(2), 159--177.

[19]

Williams, A. F. and Lund A. K. (1986). Seat belt use laws and occupant crash protection in the USA. Am. J. Public Health, 76(12), 1438--1442.

[20]

Zhang, Y. and Hornof, A. (2012). A discrete movement model for cursor tracking derived from moment-tomoment tracking data and the modeling of a dual-task experiment. In Proceedings of the 56th Human Factors and Ergonomics Society Annual Meeting, 1000--1024.

Cited By

Vuong TJacucci GRuotsalo T(2024)Naturalistic Digital Behavior Predicts Cognitive AbilitiesACM Transactions on Computer-Human Interaction10.1145/366034131:3(1-32)Online publication date: 7-May-2024
https://dl.acm.org/doi/10.1145/3660341
Seymour T(2022)EPICpy: A Python Interface for EPIC Computational Cognitive ModelingJournal of Open Source Software10.21105/joss.045337:76(4533)Online publication date: Aug-2022
https://doi.org/10.21105/joss.04533
Moss JWong ADurriseau JBradshaw G(2021)Tracking strategy changes using machine learning classifiersBehavior Research Methods10.3758/s13428-021-01720-454:4(1818-1840)Online publication date: 26-Oct-2021
https://doi.org/10.3758/s13428-021-01720-4
Show More Cited By

Index Terms

Understanding multitasking through parallelized strategy exploration and individualized cognitive modeling
1. Computing methodologies
  1. Artificial intelligence
    1. Philosophical/theoretical foundations of artificial intelligence
  2. Modeling and simulation
    1. Model development and analysis
      1. Model verification and validation
2. Human-centered computing
  1. Human computer interaction (HCI)

Recommendations

Quantitative modeling of user performance in multitasking environments
Abstract
Multitasking is one of the most important skills required for human operators to perform highly-complex and safety-critical jobs. This study proposed and validated a quantitative model for the study of user performance improvement in a ...
Highlights
- An approach to quantify information and improve user performance in multitasking.
- User performance improved after the rearrangement of task weights for multitasks.
- Task difficulty is an effective method to manipulate mental demand ...
Towards a better understanding of adaptive multitasking by individuals
CHI EA '12: CHI '12 Extended Abstracts on Human Factors in Computing Systems

This paper reports work in progress on understanding how multitasking performance is influenced by two factors: task difficulty and task priority. In a task that involved switching between typing and controlling a cursor, these two factors were ...
Cognitive coordinating behaviors in multitasking web search
SIGIR '11: Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval

This paper investigates how users cognitively coordinate multitasking Web search across different information search problems. The analysis suggests that (1) multitasking is a prevalent Web search behavior including both sequential multitasking (31%) ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

CHI '14: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

April 2014

4206 pages

ISBN:9781450324731

DOI:10.1145/2556288

General Chairs:
Matt Jones
Swansea University, Wales, UK
,
Philippe Palanque
Universit� Paul Sabatier, France
,
Program Chairs:
Albrecht Schmidt
University of Stuttgart, Germany
,
Tovi Grossman
Autodesk Research, Canada

Copyright � 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 April 2014

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

CHI '14

Sponsor:

SIGCHI

CHI '14: CHI Conference on Human Factors in Computing Systems

April 26 - May 1, 2014

Ontario, Toronto, Canada

Acceptance Rates

CHI '14 Paper Acceptance Rate 465 of 2,043 submissions, 23%;

Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

10
Total Citations
View Citations
843
Total Downloads

Downloads (Last 12 months)31
Downloads (Last 6 weeks)2

Reflects downloads up to 21 Oct 2024

Other Metrics

View Author Metrics

Citations

Cited By

Vuong TJacucci GRuotsalo T(2024)Naturalistic Digital Behavior Predicts Cognitive AbilitiesACM Transactions on Computer-Human Interaction10.1145/366034131:3(1-32)Online publication date: 7-May-2024
https://dl.acm.org/doi/10.1145/3660341
Seymour T(2022)EPICpy: A Python Interface for EPIC Computational Cognitive ModelingJournal of Open Source Software10.21105/joss.045337:76(4533)Online publication date: Aug-2022
https://doi.org/10.21105/joss.04533
Moss JWong ADurriseau JBradshaw G(2021)Tracking strategy changes using machine learning classifiersBehavior Research Methods10.3758/s13428-021-01720-454:4(1818-1840)Online publication date: 26-Oct-2021
https://doi.org/10.3758/s13428-021-01720-4
Wobbrock J(2019)Situationally-Induced Impairments and DisabilitiesWeb Accessibility10.1007/978-1-4471-7440-0_5(59-92)Online publication date: 4-Jun-2019
https://doi.org/10.1007/978-1-4471-7440-0_5
Minotra DDikmen MHo ABurns C(2018)Does Predictability Play a Role in Task Management? An Experimental Study With a Financial Trading SimulationIEEE Transactions on Human-Machine Systems10.1109/THMS.2018.286059548:6(702-711)Online publication date: Dec-2018
https://doi.org/10.1109/THMS.2018.2860595
Mubin OTejlavwala DArsalan MAhmad MSimoff S(2018)An assessment into the characteristics of award winning papers at CHIScientometrics10.1007/s11192-018-2778-7116:2(1181-1201)Online publication date: 1-Aug-2018
https://dl.acm.org/doi/10.1007/s11192-018-2778-7
Farmer GJanssen CNguyen ABrumby D(2017)Dividing Attention Between Tasks: Testing Whether Explicit Payoff Functions Elicit Optimal Dual‐Task PerformanceCognitive Science10.1111/cogs.1251342:3(820-849)Online publication date: 27-Jun-2017
https://doi.org/10.1111/cogs.12513
Kieras DHornof A(2017)Cognitive architecture enables comprehensive predictive models of visual searchBehavioral and Brain Sciences10.1017/S0140525X1600012140Online publication date: 24-May-2017
https://doi.org/10.1017/S0140525X16000121
Balint JReynolds BBlaha LHalverson T(2017)Visualizing Eye Movements in Formal Cognitive ModelsEye Tracking and Visualization10.1007/978-3-319-47024-5_6(93-111)Online publication date: 4-Feb-2017
https://doi.org/10.1007/978-3-319-47024-5_6
Gould SCox ABrumby DWiseman S(2016)Short links and tiny keyboardsInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2016.07.00996:C(38-53)Online publication date: 1-Dec-2016
https://dl.acm.org/doi/10.1016/j.ijhcs.2016.07.009

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents