Design Problem in Engineering

  • Chwee Beng LeeEmail author


This chapter provides an overview of the context of engineering in general, the types of risks encountered by engineers, their decision making and implications for instruction. In engineering practice, design problem which is the most ill-structured and complex problems is regarded as the essence of engineering practice. This chapter specifically discusses the approaches to engineering education which builds the foundation of instructional design for engineering curricula with reference to design problem. Additionally, to develop expertise rapidly, instructors must seek to embed the characteristics of high-stakes problems in the instruction to prepare students for workplace challenges and the opportunity to learn to manage risks and to foresee and minimise the negative impact of problems and solutions to those problems.


  1. Ahmed, S., Wallace, K. M., & Blessing, L. T. (2003). Understanding the differences between how novice and experienced designers approach design tasks. Research in Engineering Design, 14, 1–11. CrossRefGoogle Scholar
  2. Anderson, K., Courter, S., McGlamery, T., Nathans-Kelly, T., & Nicometo, C. (2010). Understanding engineering work and identity: A cross-case analysis of engineers within six firms. Engineering Studies, 2, 153–174. CrossRefGoogle Scholar
  3. Atman, C., Adams, R., Cardella, M., Turns, J., Mosborg, S., & Saleem, J. (2007). Engineering design processes: A comparison of students and expert practitioners. Journal of Engineering Education, 96, 359–379. CrossRefGoogle Scholar
  4. Carper, K. L. (2000). Forensic engineering. New York: Taylor & Francis.Google Scholar
  5. Christensen, S. H., Delahousse, B., & Meganck, M. (2009). Engineering in context. Copenhagen: Academica.Google Scholar
  6. Cross, N. (2004). Expertise in design: An overview. Design Studies, 25, 427–441. CrossRefGoogle Scholar
  7. Diefes-Dux, H. A., Moore, T., Zawojewski, J., Imbrie, P. K., & Follman, D. (2004). A framework for posing open-ended engineering problems: Model-eliciting activities. Frontiers in Education.
  8. Douglas, E., Koro-Ljungberg, M., McNeill, N., Malcolm, Z., & Therriault, D. (2012). Moving beyond formulas and fixations: Solving open-ended engineering problems. European Journal of Engineering Education, 37, 627–651. CrossRefGoogle Scholar
  9. Duderstadt, J. (2008). Engineering for a changing world: A roadmap to the future of engineering practice, research, and education. Ann Arbor, MI: University of Michigan.Google Scholar
  10. Dym, C. L., & Little, L. (2003). Engineering design: A project-based introduction. New York: Wiley.Google Scholar
  11. Elmaraghy, W., Elmaraghy, H., Tomiyama, T., & Monostori, L. (2012). Complexity in engineering design and manufacturing. CIRP Annals, 61, 793–814. CrossRefGoogle Scholar
  12. Ericsson, K. A. (2010). Enhancing the development of professional performance: Implications from the study of deliberate practice. In K. A. Ericsson (Ed.), Development of professional expertise: Toward measurement of expert performance and design of optimal learning environments (pp. 405–431). New York: Cambridge University Press.Google Scholar
  13. Felder, R., & Brent, R. (2003). Learning by doing. Chemical Engineering Education, 37, 282–283.Google Scholar
  14. Felder, R., Brent, R., & Prince, M. (2011). Engineering instructional development: Programs, best practices, and recommendations. Journal of Engineering Education, 100. CrossRefGoogle Scholar
  15. Frei, R., & Serugendo, G. D. M. (2010). Advances in complexity [online]. Available from:
  16. Hamilton, E., Lesh, R., Lester, R., & Brilleslyper, M. (2008). Model-eliciting activities (MEAs) as a bridge between engineering education research and mathematics education research. Advances in Engineering Education, 1, 1–25.Google Scholar
  17. Hughes, T. (2004). Human-built world: How to think about technology and culture. Chicago: University of Chicago Press.Google Scholar
  18. Jamieson, L. H., & Lohmann, J. R. (2009). Creating a culture for scholarly and systematic innovation in engineering education. Washington, DC: American Society for Engineering Education Retrieved from Google Scholar
  19. Jonassen, D. H. (2000). Toward a design theory of problem solving. Educational Technology Research and Development, 48, 63–85. CrossRefGoogle Scholar
  20. Jonassen, D. H. (2003). Using cognitive tools to represent problems. Journal of Research on Technology in Education, 35, 362–381. CrossRefGoogle Scholar
  21. Jonassen, D. H. (2004). Learning to solve problems: An instructional design guide. San Francisco: Pfeiffer.Google Scholar
  22. Jonassen, D. H. (2007). Learning to solve complex scientific problems. Mahwah, NJ: Erlbaum.Google Scholar
  23. Jonassen, D. H. (2011). Learning to solve problems: A handbook for designing problem-solving learning environments. New York: Routledge.Google Scholar
  24. Jonassen, D. H., Strobel, Y., & Lee, C. B. (2006). Everyday problem solving in engineering: Lessons for educators. Journal of Engineering Education, 95, 139–152. CrossRefGoogle Scholar
  25. Knowles, S. (2014). Engineering risk and disaster: Disaster-STS and the American history of technology. Engineering Studies, 6, 227–248. CrossRefGoogle Scholar
  26. Lee, C. B., Ling, K. V., Reimann, P., Diponegoro, Y. A., Koh, C. H., & Chew, D. (2014). Dynamic scaffolding in a cloud-based problem representation system: Empowering pre-service teachers’ problem. Campus Wide Information System, 31, 346–356. CrossRefGoogle Scholar
  27. Litzinger, T., Lattuca, L., Hadgraft, R., & Newstetter, W. (2011). Engineering education and the development of expertise. Journal of Engineering Education, 100, 123–150. CrossRefGoogle Scholar
  28. Miller, R., & Lessard, D. (2001). Understanding and managing risks in large engineering projects. International Journal of Project Management, 19, 437–443. CrossRefGoogle Scholar
  29. Mosborg, S., Adams, R., Atman, C., Turns, J., Cardella, M., & Kim, R. (2005). Conceptions of the engineering design process: An expert study of advanced practicing professionals. Proceedings of the 2005 American Society of Engineering Education Annual Conference and Exposition, Portland, Oregon.Google Scholar
  30. National Academy of Engineering. (2004). The engineer of 2020: Visions of engineering in the new century. Washington, DC: National Academies Press.Google Scholar
  31. National Research Council. (2007). Rising above the gathering storm: Energizing and employing America for a brighter economic future. Washington, DC: National Academies Press.Google Scholar
  32. Ogilvie, C. A. (2009). Changes in students’ problem-solving strategies in a course that includes context-rich, multifaceted problems. Physical Review Physics Education Research, 5, 020102. CrossRefGoogle Scholar
  33. Rugarcia, A., Felder, R., Woods, D., & Stice, J. (2000). The future of engineering education. Chemistry Engineering Education, 31, 16–25.Google Scholar
  34. Schmidt, H. G. (1983). Problem-based learning: Rationale and description. Medical Education, 17, 11–16. CrossRefGoogle Scholar
  35. Schubert, D. H., Crum, J. A., Olofsson, J., Jones G. V., Woolard, L. A., & Ronimus, A. (2009). Environmental engineering failures in Alaska. 14th Conference on Cold Regions Engineering.
  36. Sheppard, S., Macatangay, K., Colby, A., & Sullivan, W. (2009). Educating engineers, designing for the future. San Francisco: Jossey-Bass.Google Scholar
  37. Trevelyan, J. (2007). Technical coordination in engineering practice. Journal of Engineering Education, 96, 191–204. CrossRefGoogle Scholar
  38. Vest, C. (2008). Context and challenge for twenty-first century engineering education. Journal of Engineering Education, 97, 235–236.CrossRefGoogle Scholar
  39. Zhou, C. (2012). Fostering creative engineers: A key to face the complexity of engineering practice. European Journal of Engineering Education, 37, 343–353. CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Western Sydney UniversityPenrithAustralia

Personalised recommendations