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How to evaluate reading and interpretation of differently structured engineering design rationales

Published online by Cambridge University Press:  18 September 2008

Marco Aurisicchio
Affiliation:
Engineering Design Centre, Department of Engineering, University of Cambridge, Cambridge, United Kingdom
Marina Gourtovaia
Affiliation:
Engineering Design Centre, Department of Engineering, University of Cambridge, Cambridge, United Kingdom
Rob Bracewell
Affiliation:
Engineering Design Centre, Department of Engineering, University of Cambridge, Cambridge, United Kingdom
Ken Wallace
Affiliation:
Engineering Design Centre, Department of Engineering, University of Cambridge, Cambridge, United Kingdom

Abstract

Documented engineering design rationale has the potential to become a key source of information about past designs. Ease of comprehension of design rationale might play a crucial role in ensuring that the full potential of documented information is realized and that the effort and time necessary to capture design rationale pay off. This research proposes an empirical methodology for evaluating how structuring design rationale and supplying it with visual nontextual cues influences reading and interpretation. The study compares reading and interpretation of technical documentation presented in different formats to engineering graduate trainees in the aerospace industry.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2008

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References

REFERENCES

Aurisicchio, M., Bracewell, R.H., & Wallace, K.M. (2003). A design data model to support rationale capture and functional synthesis. ASME Int. Design Engineering Technical Conf.Chicago.Google Scholar
Aurisicchio, M., Bracewell, R.H., & Wallace, K.M. (2006 a). Evaluation of DRed, a way of capturing and structuring engineering design processes. NordDesign 2006, Reykjavik, Iceland.Google Scholar
Aurisicchio, M., Bracewell, R.H., & Wallace, K.M. (2006 b). Characterising in detail the information requests of engineering designers. ASME Int. Design Engineering Technical Conf., pp. 10571064, Philadelphia, PA.Google Scholar
Blackwell, A.F. (1997). Correction: a picture is worth 84.1 words. Proc. 1st ESP Student Workshop, pp. 1522, Washington, DC.Google Scholar
Bracewell, R.H., Ahmed, S., & Wallace, K.M. (2004). DRed and design folders, a way of capturing, storing and passing on knowledge generated during design projects. ASME Design Engineering Technical Conf. Computers and Information in Engineering Conf.Salt Lake City, UT.CrossRefGoogle Scholar
Bracewell, R.H., & Wallace, K.M. (2003). A tool for capturing design rationale. Proc. 14th Int. Conf. Engineering DesignStockholm.Google Scholar
Brown, I. (1998). The effect of WWW document structure on students' information retrieval. Journal of Interactive Media in Education 98(12), 118.Google Scholar
Chattratichart, J., & Kuljis, J. (2001). Some evidence for graphical readership, paradigm preference, and the match-mismatch conjecture in graphical programs. 13th Workshop of the Psychology of Programming Interest GroupBournemouth, UK.Google Scholar
Conklin, J., Selvin, A., Shum, S.B., & Sierhuis, M. (2001). Facilitated hypertext for collective sensemaking: 15 years on from gIBIS. Proc. 12th ACM Conf. Hypertext and HypermediaArhus, Denmark.Google Scholar
Dickson, S.V., Simmons, D.C., & Kameenui, E.J. (1995). Text Organisation and Its Relation to Reading Comprehension: A Synthesis of the Research, Report No. 17. Eugene, OR: University of Oregon, College of Education, US National Center to Improve the Tools of Educators.Google Scholar
Duke, N.K., & Pearson, P. (2002). Effective practices for developing reading comprehension. In What Research Has to Say About Reading Instructions (Farstrup, A.E., & Samuels, S., Eds.), pp. 205242. Newark, DE: International Reading Association.Google Scholar
Dürsteler, J.C. (2007). InfoVis Diagram, No. 187. Accessed at http://www.infovis.net/ on February 5, 2008.Google Scholar
Gilmore, D.J., & Green, T.R.G. (1984). Comprehension and recall of miniature programs. International Journal of Man–Machine Studies 21, 3148.Google Scholar
Karat, J. (1997). Use-centered software evaluation methodologies. In Handbook of Human– Computer Interaction (Helander, M., Landauer, T.K., & Prabhu, P., Eds.), 2nd ed., pp. 689704. Amsterdam: Elsevier Science.Google Scholar
Karsenty, L. (1996). An empirical evaluation of design rationale documents. Proc. SIGCHI Conf. Human Factors in Computing Systems, pp. 150156.Google Scholar
Kunz, W., & Rittel, H.W.J. (1970). Issues as Elements of Information Systems, Working Paper 131. Berkeley, CA: University of California, Berkeley, Center for Planning and Development Research.Google Scholar
Landauer, T.K. (1997). Behavioral research methods in human–computer interactions. In Handbook of Human–Computer Interaction (Helander, M., Landauer, T.K., & Prabhu, P., Eds.), 2nd ed., pp. 203227. Amsterdam: Elsevier Science.CrossRefGoogle Scholar
MacLean, A., Young, R.M., Bellotti, V., & Moran, T.P. (1991). Questions, options, and criteria: elements of design space analysis. Human–Computer Interaction 6, 201250.Google Scholar
McDonald, S., & Stevenson, R.J. (1996). Disorientation in hypertext: the effects of three text structures on navigation performance. Applied Ergonomics 27(1), 6168.CrossRefGoogle ScholarPubMed
Melville, C., Hands, S., & Jones, P. (2002). Randomised trial of the effects of structuring clinic correspondence. Archives of Disease in Childhood 86, 374375.Google Scholar
North, C. (2006). Toward measuring visualization insight. IEEE Computer Graphics and applications 26, 69.Google Scholar
Purchase, H.C. (2000). Effective information visualisation: a study of graph drawing aesthetic and algorithms. Interacting with Computers 13, 147162.Google Scholar
Rodrigues, J.F., Traina, A.J.M., de Oliveira, M.C.F., & Traina, C. (2007). The spatial–perceptual design space: a new comprehension for data visualization. Information Visualization 6, 261279.CrossRefGoogle Scholar
Shin, C.E., Schallert, D.L., & Savenye, W.C. (1994). Effects of learner control, advisement and prior knowledge on young students' learning in a hypertext environment. Educational Technology Research and Development 42, 3346.Google Scholar
Stone, D., Jarret, C., Woodroffe, M., & Minocha, S. (2005). User Interface Design and Evaluation. San Mateo, CA: Morgan Kaufmann.Google Scholar
Trochim, W.M. (2006). The Research Methods Knowledge Base, 2nd ed. Accessed at http://www.socialresearchmethods.net/kb/ on February 5, 2008.Google Scholar
Vaughan, M.W., & Dillon, A. (2006). Why structure and genre matter for users of digital information: a longitudinal experiment with readers of a Web-based newspaper. International Journal of Human–Computer Studies 64, 502526.Google Scholar
Whitley, K.N. (1997). Visual programming languages and the empirical evidence for and against. Journal of Visual Languages and Computing 8(1), 109142.CrossRefGoogle Scholar