TY - GEN
T1 - Predicting creativity in the wild
T2 - ACM 2012 Conference on Computer Supported Cooperative Work, CSCW'12
AU - Tripathi, Priyamvada
AU - Burleson, Winslow
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
KW - creativity support tools (cst)
KW - experience sample method
KW - sociometric modeling
KW - wearable computing
UR - http://www.scopus.com/inward/record.url?scp=84858267845&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84858267845&partnerID=8YFLogxK
U2 - 10.1145/2145204.2145386
DO - 10.1145/2145204.2145386
M3 - Conference contribution
AN - SCOPUS:84858267845
SN - 9781450310864
T3 - Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW
SP - 1203
EP - 1212
BT - CSCW'12 - Proceedings of the ACM 2012 Conference on Computer Supported Cooperative Work
Y2 - 11 February 2012 through 15 February 2012
ER -