This paper compares the efficacy of four digital drawing tools—mouse, iPad, Wacom Cintiq, and Bamboo1—when measured by user perception of technical and esthetic quality outcomes. The tools were assessed through the experiences of 20 senior–level undergraduate students majoring in interior design. The results indicate the mouse was preferred overall, contradicting previous studies showing students’ preference for digital drawing tablets. However, as we show, drawing is an affordance–based interaction that is influenced by participants’ prior experience with both hand and digital drawing tools. We therefore propose a grounded–theory model underscoring the importance of hand–eye–interface (HEI) and layout and orientation (LO) in supporting successful introduction of any new drawing tool. Further implications of the HEI–LO model suggest facilitating learning with multiple opportunities to use a wide range of tools to embed experiences in long–term memory, strengthen learned conventions, and promote positive affordances for both hand and digital media.
Get full access to this article
View all access options for this article.
References
1.
BaddeleyA. D. (2002). Is working memory still working. European Psychologist, 7(2), 85–97.
2.
BildaZ. (2001). Designers’ cognition in traditional versus digital media during conceptual design. Master's thesis. Bilkent University, Bilkent, Turkey.
3.
BildaZ., & DemirkanH. (2003). An insight on designers’ sketching activities in traditional versus digital media. Design Studies, 24(1), 27–50.
4.
ChattaramanV., TanL. & PeekP. (2013). Incorporation of pen–based digital drawing tools in apparel and interior design instruction for effective design communication. Proceedings of the 2013 Annual Conference of the International Textile and Apparel Association, New Orleans, LA.
5.
ClarkL. & ClarkJ. (2010). Environmental design and emerging technologies: Today and the near future. Celebrating our foundations: Teaching, scholarship service. Proceedings of the IDEC Annual International Conference, Atlanta, GA. pp. 338–341.
DickinsonJ., YuZ., ZengY., & AntunesH. (2005). Pen–tablet as a CAD interface alternative. Robotics and Computer Integrated Manufacturing, 21(4–5), 465–474.
10.
DortaT., PérezE., & LesageA. (2008). The ideation gap: Hybrid tools, design flow and practice. Design Studies, 29(2), 121–141.
11.
EricssonK. A., & KintschW. (1995). Long–term working memory. Psychological Review, 102, 211–245.
12.
GoelV. (1995). Sketches of thought. Cambridge, MA: The MIT Press.
13.
GoldschmidtG. (1991). The dialectics of sketching. Creativity and Research Journal, 4(2), 123–143.
14.
GoldschmidtG. (1995). The designer as a team of one. Design Studies, 16(2), 189–209.
15.
GoldschmidtG. (2003). Cognitive economy in design reasoning. Berlin, Germany: Springer–Verlag.
16.
GoldschmidtG., & RogersP. A. (2013). The design thinking approaches of three different groups of designers based on self–reports. Design Studies, 34(4), 454–471.
17.
GrgicJ., & StillJ. D. (2010, May). Affordance interactions are affected by spatial working memory load. Poster Presented at the Annual Meeting of the Midwestern Psychological Association, Chicago, IL.
18.
HartsonH. R. (2003). Cognitive, physical, sensory, and functional affordances in interaction design. Behaviour & Information Technology, 22(5), 315–338.
19.
HowardT. J., CulleyS. J., & DekoninckE. (2008). Describing the creative design process by the integration of engineering design and cognitive psychology literature. Design Studies, 29, 160–180.
20.
JinY., & ChusilpP. (2006). Study of mental iteration in different design situations. Design Studies, 27, 25–55.
21.
JohnsonL., SmithR., WillisH., LevineA., & HaywoodK. (2011). The 2011 Horizon Report. Austin, TX: The New Media Consortium.
22.
KanJ. W. T., BildaZ., & GeroJ. S. (2007). Comparing entropy measures of idea links in design protocols: Linkography entropy measurement and analysis of differently conditioned design sessions. Artificial Intelligence for Engineering Design Analysis and Manufacturing, 21, 367–377.
23.
KannengiesserU., & GeroJ. S. (2012). A process framework of affordances in design. Journal of Design Issues, 28, 50–62.
24.
KochK. & DominaT. (2003). Strategic planning for evolving CAD labs. Proceedings of the 2003 Annual Conference of the International Textile and Apparel Association, Savannah, GA.
25.
LimS., QinS. F., PrietoP., WrightD., & ShackletonJ. (2004). A study of sketching behavior to support free–form surface modeling from on–line sketching. Design Studies, 25, 393–413.
26.
MaldonadoH., LeeB., and KlemmerS. (2006). Technology for design education: A case study. Presented at CHI 2006, Montreal, QC, Canada.
27.
MartinC., & GuerinD. (2005). The interior design profession's body of knowledge. Interior Design Educators Council. Retrieved September 15, 2014, from http://www.careersininteriordesign.com/idbok.pdf
28.
McCarneyR., WarnerJ., IliffeS., Van HaselenR., GriffinM., & FisherP. (2007). The Hawthorne effect: A randomised, controlled trial. BMC Medical Research Methodology, 7(30). doi: 10.1186/1471-2288-7-30.
29.
MeneelyJ. (2010). In search of the digital muse: Divining the role of digital sketching in interior design education. Proceedings of the Interior Design Educators Council Annual International Conference, Atlanta, GA.
30.
MeneelyJ., & DankoS. (2007). Motive, mind, and media: Digital sketching in the creative culture of design. Journal of Interior Design, 32(3), 69–90.
31.
OrlikowskiW. (1993). CASE tools are organizational change: Investigating incremental and radical changes in systems development. MIS Quarterly, 17(3), 309–340.
RaskinJ. (1994, September). Intuitive equals familiar. Communications of the ACM, 37(9), 17.
34.
SchonD. A., & WigginsG. (1992). Kinds of seeing and their function in designing. Design Studies, 13, 135–156.
35.
ŞenyapiliB., & BasaY. (2006). The shifting tides of academe: Oscillation between hand and computer in architectural education. International Journal of Technology and Design Education, 16(3), 273–283.
36.
ShahJ. J., SmithS. M., & Vargas–HernandezN. (2003). Metrics for measuring ideation effectiveness. Design Studies, 24, 111–134.
37.
StillJ. D., & DarkV. J. (2008). An empirical investigation of affordances and conventions. In GeroJ. S. & GoelA. K. (Eds.), Design computing and cognition ‘08 (pp. 457–472). Dordrecht, the Netherlands: Springer.
38.
StillJ. D., & DarkV. J. (2013). Cognitively describing and designing affordances. Design Studies, 34(3), 285–301.
39.
StonesC., & CassidyT. (2007). Comparing synthesis strategies of novice graphic designers using digital and traditional design tools. Design Studies, 28(1), 59–72.
40.
SunL., XiangW., ChaiC., WangC., & HuangQ. (2013). Creative segment: A descriptive theory applied to computer–aided sketching. Design Studies, 35(1), 54–79.
41.
TanL. (March 22, 2012). Analysis of technologies for effective design communication. [Poster]. Presented at the Interior Design Educators Council Annual International Conference, Baltimore, MD.
42.
TangH. H., LeeY. Y., & GeroJ. S. (2010). Comparing collaborative co–located and distributed design processes in digital and traditional sketching environments: A protocol study using the function–behaviour–structure coding scheme. Design Studies, 32, 1–29.
43.
TauraT., YamamotoE., FasihaM. Y. N., GokaM., MukaiF., NagaiY., . (2012). Constructive simulation of creative concept generation process in design: a research method for difficult–to–observe design–thinking processes. Journal of Engineering Design, 23, 297–321.
44.
ThornberryT. P., & KrohnM. D. (2000). The self–report method for measuring delinquency and crime. Criminal Justice, 4, 33–83.
45.
WonP. H. (2001). The comparison between visual thinking using computer and conventional media in the concept generation stages of design. Automation in Construction, 10, 319–325.
