ACM Home Page
Please provide us with feedback. Feedback
Using temporal patterns (t-patterns) to derive stress factors of routine tasks
Full text PdfPdf (614 KB)
Source
Conference on Human Factors in Computing Systems archive
Proceedings of the 27th international conference extended abstracts on Human factors in computing systems table of contents
Boston, MA, USA
SESSION: Spotlight on work in progress session 1 table of contents
Pages 4081-4086  
Year of Publication: 2009
ISBN:978-1-60558-247-4
Authors
Oliver Brdiczka  Palo Alto Research Center (PARC), Palo Alto, CA, USA
Norman Makoto Su  University of California, Irvine, CA, USA
Bo Begole  Palo Alto Research Center (PARC), Palo Alto, CA, USA
Sponsors
ACM: Association for Computing Machinery
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 8,   Downloads (12 Months): 56,   Citation Count: 0
Additional Information:

abstract   references   index terms   collaborative colleagues  

Tools and Actions: Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1520340.1520621
What is a DOI?

ABSTRACT

We describe the use of a statistical technique called T-pattern analysis to derive and characterize the routineness of tasks. T-patterns provide significant advantages over traditional sequence analyses by incorporating time. A T-pattern is characterized by a significant time window (critical interval) that describes the duration of this pattern. Our analysis is based on data collected from shadowing 10 knowledge workers over a total of 29 entire work days. We report on the statistics of detected T-patterns and derived correlations with participant perceptions of workload, autonomy, and productivity.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

1
2
3
 
4
M. S. Magnusson. Discovering hidden time patterns in behavior: T-patterns and their detection. Behavior Research Methods, Instruments, & Computers, 32(1):93---110, 2000.
 
5
 
6
 
7
L.R. Rabiner. A tutorial on hidden Markov models and selected applications in speech recognition. In Proceedings of the IEEE, number 2, pages 257--286, 1989.
 
8
S.G. Hart, and L.E. Staveland. Development of nasa-tlx (task load index): Results of empirical and theoretical research. Human Mental Workload 1, 139--183, 1988.
 
9
J.R. Hackman, and G.R. Oldham. The Job Diagnostic Survey: An Instrument for the Diagnosis of Jobs and the Evaluation of Job Redesign Projects. Storming Media, New Haven, CT: Yale University, Department of Administration Science, 1974.
 
10
J.R. Idaszak, and F. Drasgow. A revision of the job diagnostic survey: Elimination of a measurement artifact. Journal of Applied Psychology 72, 1, 69--74, 1987.
 
11
M.T. Halpern, R. Shikiar, R., A.M. Rentz, and Z.M. Khan. Impact of smoking status on workplace absenteeism and productivity. Tobacco Control 10, 3, 233--238, 2001.

Collaborative Colleagues:
Oliver Brdiczka: colleagues
Norman Makoto Su: colleagues
Bo Begole: colleagues