TY - GEN
T1 - Empirical studies of design thinking
T2 - ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2013
AU - Cagan, Jonathan
AU - Dinar, Mahmoud
AU - Shah, Jami J.
AU - Leifer, Larry
AU - Linsey, Julie
AU - Smith, Steven M.
AU - Vargas-Hernandez, Noe
N1 - Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - Empirical methods used for studying design thinking have included verbal protocols, case studies, and controlled experiments. Studies have looked at the role of design methods, strategies, tools, environment, experience, and group dynamics. Early empirical studies were casual and exploratory with loosely defined objectives and informal analysis methods. Current studies have become more formal, factor controlled, aiming at hypothesis testing, using statistical DOE and analysis methods such as ANOVA. Popular pursuits include comparison of experts and novices, identifying and overcoming fixation, role of analogies, effectiveness of ideation methods, and other various tools. A variety of data may be collected, related to both the process and the outcome (designs).There are still no standards for designing, collecting and analyzing data, partly due to the lack of cognitive models and theories of design thinking. Data analysis is tedious and the rate of discoveries has been slow. Future studies may need to develop computer based data collection and automated analyses, which may facilitate collection of massive amounts of data with the potential of rapid advancement of the rate of discoveries and development of cognitive models of design thinking.
AB - Empirical methods used for studying design thinking have included verbal protocols, case studies, and controlled experiments. Studies have looked at the role of design methods, strategies, tools, environment, experience, and group dynamics. Early empirical studies were casual and exploratory with loosely defined objectives and informal analysis methods. Current studies have become more formal, factor controlled, aiming at hypothesis testing, using statistical DOE and analysis methods such as ANOVA. Popular pursuits include comparison of experts and novices, identifying and overcoming fixation, role of analogies, effectiveness of ideation methods, and other various tools. A variety of data may be collected, related to both the process and the outcome (designs).There are still no standards for designing, collecting and analyzing data, partly due to the lack of cognitive models and theories of design thinking. Data analysis is tedious and the rate of discoveries has been slow. Future studies may need to develop computer based data collection and automated analyses, which may facilitate collection of massive amounts of data with the potential of rapid advancement of the rate of discoveries and development of cognitive models of design thinking.
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U2 - 10.1115/DETC2013-13302
DO - 10.1115/DETC2013-13302
M3 - Conference contribution
AN - SCOPUS:84896914335
SN - 9780791855928
T3 - Proceedings of the ASME Design Engineering Technical Conference
BT - 25th International Conference on Design Theory and Methodology; ASME 2013 Power Transmission and Gearing Conference
PB - American Society of Mechanical Engineers
Y2 - 4 August 2013 through 7 August 2013
ER -