Predicting creativity in the wild: Experience sample and sociometric modeling of teams

Priyamvada Tripathi, Winslow Burleson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Relationships between creativity in teamwork, and team members' movement and face-to-face interaction strength were investigated "in the wild" using sociometric badges (wearable sensors), electronic Experience Sampling Methods (ESM), the KEYS team creativity assessment instrument, and qualitative methods, in academic and industry settings. Activities (movement and face-to-face interaction) and creativity of one five-member and two seven-member teams were tracked for twenty-five days, eleven days, and fifteen days respectively. Paired-sample t-test confirmed average daily movement energy during creative days was significantly greater than on non-creative days and that face-to-face interaction tie strength of team members during creative days was significantly greater than for non-creative days. The combined approach of principal component analysis (PCA) and linear discriminant analysis (LDA) conducted on movement and face-to-face interaction data yielded a model that predicted creativity with 87.5% and 91% accuracy, respectively. Computational models that predict team creativity hold particular promise to enhance Creativity Support Tools.

Original languageEnglish (US)
Title of host publicationCSCW'12 - Proceedings of the ACM 2012 Conference on Computer Supported Cooperative Work
Pages1203-1212
Number of pages10
DOIs
StatePublished - 2012
EventACM 2012 Conference on Computer Supported Cooperative Work, CSCW'12 - Seattle, WA, United States
Duration: Feb 11 2012Feb 15 2012

Publication series

NameProceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW

Other

OtherACM 2012 Conference on Computer Supported Cooperative Work, CSCW'12
Country/TerritoryUnited States
CitySeattle, WA
Period2/11/122/15/12

Keywords

  • creativity support tools (cst)
  • experience sample method
  • sociometric modeling
  • wearable computing

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Networks and Communications

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