Research on creative performance indicates that a combination of the primary sources such as known concepts and existing ideas plays an important role in the generation of new ideas. Although studies show a link between the combinational approach to ideation and creativity, how individual differences in cognitive styles are related to this approach is not well understood. This exploratory study examines the domain–specific relationship between individuals’ cognitive styles and improvement of creative performance within the structured combinational ideation process where mixing various ideas is encouraged. Fifty interior design students enrolled in the second year of an interior design program at a Midwestern university participated in this study. The workshop designed for this study was structured in the following stages: initial design (ID) + the combinational ideation process (the variation process [VP] + the combination process [CP]) + final design (FD). The participants’ creative performance was measured at the ID and the FD phases by three experts. Findings indicated that intuitive individuals generally showed the highest creativity in the ID phase, but they showed a decrease of creativity in the FD, implying that a structured combinational ideation method might not be the best method for intuitive individuals. In contrast, individuals possessing an adaptive and an analytical information processing style showed an increase of creativity in the FD after completing the structured combinational ideation process, suggesting that students with a nonintuitive cognitive style benefit most from this method. The result of this research will provide design educators with meaningful insight into the instruction methods that take students’ cognitive styles into consideration, especially in helping nonintuitive students who struggle in the ideation process.
Get full access to this article
View all access options for this article.
References
1.
AllinsonC. W., & HayesJ. (1996). The cognitive style index: A measure of intuition–analysis for organizational research. Journal of Management Studies, 33(1), 119–135.
2.
AllinsonC., & HayesJ. (2012). The cognitive style index: Technical manual and user guide. Harlow, UK: Pearson Education Ltd.
3.
AllinsonC. W., & HayesJ. (2010). Interpreting your CSI scores (Unpublished manuscript).
4.
AmabileT. M. (1983). The social psychology of creativity: A componential conceptualization. Journal of Personality and Social Psychology, 45(2), 357–376.
5.
AmabileT. M. (1996). Creativity in context: Update to the social psychology of creativity. Boulder, CO: Westview Press.
6.
AmabileT. M., HadleyC. N., & KramerS. J. (2002). Creativity under the gun. Harvard Business Review, 80, 52–63.
7.
BackhausK., & LiffJ. P. (2007). Cognitive styles and approaches to studying in management education. Journal of Management Education, 31, 445–466.
8.
BaughmanW. A., & MumfordM. D. (1995). Process–analytic models of creative capacities: Operations influencing the combination–and–reorganization process. Creativity Research Journal, 8, 37–62.
9.
BeckenbachF., & DaskalakisM. (2013). Invention and innovation as creative problem–solving activities. In Encyclopedia of creativity, invention, innovation and entrepreneurship. (pp. 1118–1131). New York, NY: Springer.
10.
BeckerM. (1995). 19th Century foundations of creativity research. Creativity Research Journal, 8, 219–229.
11.
BesemerS. P., & O'QuinK. (1999). Confirming the three–factor creative product analysis matrix model in an American sample. Creativity Research Journal, 12(4), 287–296.
12.
BethuneG. W. (1837). Genius (An address delivered before the literary societies of Union College).
13.
BodenM. A. (1998). Creativity and artificial intelligence. Artificial Intelligence, 103(1-2), 347–356.
14.
ChanJ., & SchunnC. D. (2015). The importance of iteration in creative conceptual combination. Cognition, 145, 104–115.
15.
CicchettiD. V. (1994). Guidelines, criteria, and rules of thumb for evaluating normed and standardized assessment instruments in psychology. Psychological Assessment, 6(4), 284–290.
16.
CropleyA. (2006). In praise of convergent thinking. Creativity Research Journal, 18(3), 391–404.
17.
DeanD. L., HenderJ. M., RodgersT. L., & SantanenE. (2006). Identifying good ideas: Constructs and scales for idea evaluation. Journal of the Association for Information Systems, 7(10), 646–699.
18.
DoboliA., UmbarkarA., SubramanianV., & DoboliS. (2014). Two experimental studies on creative concept combinations in modular design of electronic embedded systems. Design Studies, 35(1), 80–109. https://doi.org/10.1016/j.destud.2013.10.002
19.
EntwistleN. (1988). Motivational factors in students’ approaches to learning. In Learning strategies and learning styles. (pp. 21–51). Boston, MA: Springer.
20.
EstesZ., & WardT. B. (2002). The emergence of novel attributes in concept modification. Creativity Research Journal, 14(2), 149–156.
21.
FanZ. (2008). Cross–cultural differences in human information processing: An empirical study of Westerners and Asians (MPhil thesis, University of Hong Kong).
22.
FinkeR. A., WardT. B., & SmithS. M. (1992). Creative cognition: Theory, research, and applications. Cambridge, MA: MIT Press.
23.
GarfieldM. J., TaylorN. J., DennisA. R., & SatzingerJ. W. (2001). Modifying paradigms—Individual differences, creativity techniques, and exposure to ideas in group idea generation. Information Systems Research, 12(3), 322–333.
24.
GeroJ. S. (1994). Computational models of creative design processes. In Artificial intelligence and creativity. (pp. 269–281). Dordrecht, Netherlands: Springer.
25.
GomezJ. G. (2007). What do we know about creativity?Journal of Effective Teaching, 7(1), 31–43.
26.
HammondK. R., HammR. M., GrassiaJ., & PearsonT. (1987). Direct comparison of the efficacy of intuitive and analytical cognition in expert judgement. IEEE Transactions on Systems, Man, and Cybernetics, 17, 753–770.
27.
HanJ., ParkD., ShiF., ChenL., & ChildsP. (2017). Three driven approaches to combinational creativity. Paper presented at the DS 87–8 Proceedings of the 21st International Conference on Engineering Design (ICED 17): Vol 8. Human Behaviour in Design. Vancouver, Canada.
28.
HayesJ., & AllinsonC. W. (1996). The implications of learning styles for training and development: A discussion of the matching hypothesis. British Journal of Management, 7(1), 63–73.
HoneyP., & MumfordA. (1992). The manual of learning styles. Maidenhead, UK: Peter Honey Publications.
31.
HornD., & SalvendyG. (2006). Consumer–based assessment of product creativity: A review and reappraisal. Human Factors and Ergonomics in Manufacturing & Service Industries, 16(2), 155–175.
32.
JamesW. (1880). Great men, great thoughts, and the environment (lecture delivered before the Harvard Natural History Society). Atlantic Monthly, 46, 441–459.
KlahrD. (2002). Exploring science: The cognition and development of discovery processes. Cambridge, MA: MIT Press.
35.
KoestlerA. (1964). The act of creation. New York, NY: Macmillan.
36.
KozbeltA., BeghettoR. A., & RuncoM. A. (2010). Theories of creativity. In KaufmanJ. C. & SternbergR. J. (Eds.), The Cambridge handbook of creativity. (pp. 20–46). New York, NY: Cambridge University Press.
37.
MaW. W. K., SunK., & MaJ. (2012). The influence of cognitive learning styles on the use of online learning environments. In CheungS., . (Eds.), ICHL 2012, LNCS. Berlin Heidelberg: Springer–Verlag.
38.
MalychaC. P., & MaierG. W. (2017). The random–map technique: Enhancing mind–mapping with a conceptual combination technique to Foster creative potential. Creativity Research Journal, 29(2), 114–124.
39.
MeccaJ. T., & MumfordM. D. (2014). Imitation and creativity: Beneficial effects of propulsion strategies and specificity. Journal of Creative Behavior, 48(3), 209–236.
40.
MednickS. (1962). The associative basis of the creative process. Psychological Review, 69(3), 220–232.
41.
MeneelyJ., & PortilloM. (2005). The adaptable mind in design: Relating personality, cognitive style, and creative performance. Creativity Research Journal, 17(2–3), 155–166.
42.
MessickS. (1976). Personality consistencies in cognition and creativity. In MessickS., . (Eds.), Individuality in learning. (pp. 4–22). San Francisco, CA: Jossey–Bass.
43.
MobleyM. I., DoaresL. M., & MumfordM. D. (1992). Process analytic models of creative capacities: Evidence for the combination and reorganization process. Creativity Research Journal, 5(2), 125–155.
44.
MooreS., O'MaidinD., & McElligottA. (2003). Cognitive styles among computer systems students: Preliminary findings. Journal of Computing in Higher Education, 14(2), 45–67.
45.
Pei–ShanT., DengchuanC., & Yao–JenF. (2009). A study of cognitive style on design performance. Paper presented at the Proceedings of IASDR, Korea.
RobertsA. (2006). Cognitive styles and student progression in architectural design education. Design Studies, 27(2), 167–181.
48.
RuncoM. A., & ChandI. (1995). Cognition and creativity. Educational Psychology Review, 7(3), 243–267.
49.
RuncoM. A., & CharlesR. E. (1993). Judgments of originality and appropriateness as predictors of creativity. Personality and Individual Differences, 15(5), 537–546.
ScottG. M., LonerganD. C., & MumfordM. D. (2005). Conceptual combination: Alternative knowledge structures, alternative heuristics. Creativity Research Journal, 17(1), 79–98.
52.
SelbyE. C., ShawE. J., & HoutzJ. C. (2005). The creative personality. Gifted Child Quarterly, 49(4), 300–314.
53.
ShahJ. J., SmithS. M., & Vargas–HernandezN. (2003). Metrics for measuring ideation effectiveness. Design Studies, 24(2), 111–134.
54.
SharanY., & SharanS. (1992). Expanding cooperative learning through group investigation. New York, NY: Teachers College Press.
55.
SmithS. M., & WardT. B. (2012). Cognition and the creation of ideas. In K. J. Holyoak & R. G. Morrison (Eds.), Oxford handbook of thinking and reasoning (pp. 456–474). New York, NY: Oxford University Press.
56.
SteinM. I. (1953). Creativity and culture. The Journal of Psychology, 36(2), 311–322.
57.
SternbergR. J., & LubartT. I. (1996). Investing in creativity. American Psychologist, 51(7), 677–688.
