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A meta-synthesis of primary and secondary student design cognition research

  • Greg J. StrimelEmail author
  • Eunhye Kim
  • Michael E. Grubbs
  • Tanner J. Huffman
Article

Abstract

Design within primary and secondary schools has been increasingly emphasized over the past decade. As a response to this increased interest, qualitative research examining students’ cognitive processes involved in the practices of design has been on the rise. These studies have commonly employed the concurrent think-aloud research methodology to examine and describe an individual’s or group’s thought processes while engaged in a design task. However, the variety of coding schemes used to code and describe the collected think-aloud data has limited the synthesis of findings across design cognition studies, which can be a concern as the synthesis of qualitative studies can potentially lead to the development of more formal and possibly more generalizable theories (Glaser and Strauss in Status passage, Aldine, Chicago, 1971). Nevertheless, a study conducted by Grubbs, Strimel, and Kim (2018) examined the different coding schemes used in analyzing the design cognition of primary and secondary students that were published between 1995 and 2016. Their investigation led to the identification of three distinct themes for the foundation and intent of the various design cognition coding schemes and provided a basis for a more informed meta-synthesis of design cognition research. Therefore, this study examined the design cognition studies identified by Grubbs et al. (2018) and synthesized both the findings and discussions of each, according to the three coding scheme themes. The results of this investigation can provide deeper insights into primary and secondary students’ design thinking and can help inform design pedagogy.

Keywords

Design Design cognition Think-aloud protocols Engineering education Technology education 

Notes

References

  1. Atman, C., Adams, R. S., Cardella, M., Turns, J., Mosborg, S., & Saleem, J. (2007). Engineering design processes: A comparison of students and expert practitioners. Journal of Engineering Education, 96(4), 359–379.Google Scholar
  2. Atman, C. J., & Bursic, K. M. (1998). Verbal protocol analysis as a method to document engineering student design processes. Journal of Engineering Education, 87(2), 121–132.Google Scholar
  3. Bowers, D. H., & Evans, D. L. (1990). The role of visualization in engineering design. In Proceedings of the NSF symposium on modernization of the engineering design graphics curriculum, Austin, TX.Google Scholar
  4. Crismond, D. P., & Adams, R. S. (2012). A scholarship of integration: The matrix of informed design. Journal of Engineering Education, 101(4), 738–797.  https://doi.org/10.1002/j.2168-9830.2012.tb01127.x.Google Scholar
  5. Critical Appraisal Skills Programme (CASP). 10 questions to help you make sense of qualitative research. Retrieved from http://docs.wixstatic.com/ugd/dded87_25658615020e427da194a325e7773d42.pdf.
  6. Cross, N. (2004). Expertise in design: An overview. Design Studies, 25(5), 427–441.Google Scholar
  7. De Vries, M. J. (2018). The T and E in STEM: From promise to practice. In M. J. de Vries, S. Fletcher, S. Kruse, P. Labudee, M. Lang, I. Mammes, C. Max, D. Münk, B. Nicholl, J. Strobel, & M. Winterbottom (Eds.), Research in technology education. New York: Waxmann.Google Scholar
  8. El-Zanfaly, D. (2015). [I3] Imitation, iteration and improvisation: Embodied interaction in making and learning. Design Studies, 41((Part A)), 79–109.  https://doi.org/10.1016/j.destud.2015.09.002.Google Scholar
  9. Ericsson, K. A., & Simon, H. A. (1993). Protocol analysis: Verbal reports as data. Cambridge, MA: Massachusetts Institute of Technology Press.Google Scholar
  10. Erwin, E. J., Brotherson, M. J., & Summers, J. A. (2011). Understanding qualitative metasynthesis: Issues and opportunities in early childhood intervention research. Journal of Early Intervention, 33(3), 186–200.Google Scholar
  11. Field, B. W. (1994). A course in spatial visualization. In Proceedings of the 6th international conference on engineering design graphics and descriptive geometry, Tokyo.Google Scholar
  12. Gero, J. S., & Kannengiesser, U. (2004). The situated Function–Behavior–Structure framework. Design Studies, 25(4), 373–391.Google Scholar
  13. Glaser, B. G., & Strauss, A. L. (1971). Status passage. Chicago: Aldine.Google Scholar
  14. Glass, G., et al. (1981). Meta-analysis in social research. Newbury Park, CA: Sage.Google Scholar
  15. Grubbs, M. E. (2016). Further characterization of high school pre- and non-engineering students’ cognitive activity during engineering design (Doctoral dissertation). Retrieved from ProQuest Dissertations and Theses database. (UMI No. 3662376).Google Scholar
  16. Grubbs, M. E. & Strimel, G. J. (2016). Cognitive research: Transferring theories and findings to k-12 engineering educational practice, American Society for Engineering Education 103rd Annual Conference and Exposition. New Orleans, LA, June 26, 2016.Google Scholar
  17. Grubbs, M. E., Strimel, G. J., & Kim, E. (2018). Examining design cognition coding schemes for P-12 engineering/technology education. International Journal of Technology and Design Education, 28(4), 899–920.Google Scholar
  18. Halfin, H. H. (1973). Technology: A process approach. (Doctoral dissertation, West Virginia University, 1973) Dissertation Abstracts International, (1) 1111A.Google Scholar
  19. Hill, R. B. (1997). The design of an instrument to assess problem-solving activities in technology education. Journal of Technology Education, 9(1), 31–46.Google Scholar
  20. Hope, G. (2000). Beyond their capability? Drawing, designing and the young child. Journal of Design & Technology Education, 5(2), 106–114.Google Scholar
  21. Huffman, T. J., Strimel, G. J., & Grubbs, M. E. (2018). Determining the engineering knowledge dimension: What all high school students should know to be engineering literate. In Paper presented at the American Society of engineering education annual conference, Salt Lake City, UT.Google Scholar
  22. Hynes, M., Portsmore, M., Dare, E., Milto, E., Rogers, C., & Hammer, D. (2011). Infusing engineering design into high school STEM courses. Retrieved from http://ncete.org/flash/pdfs/Infusing_Engineering_Hynes.pdf.
  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, J., & Lee, C. B. (2006). Everyday problem solving in engineering: Lessons for engineering educators. Journal of Engineering Education, 95(2), 139–151.  https://doi.org/10.1002/j.2168-9830.2006.tb00885.x.Google Scholar
  25. Kannengiesser, U., Gero, J., Wells, J., & Lammi, M. (2015). Do high school students benefit from pre-engineering design education? In Proceedings of the 20th international conference on engineering design (ICED). Human behaviour in design (Vol 11, pp. 267–276), July 27–30, Milan, Italy.Google Scholar
  26. Kelley, T. R. (2008). Cognitive processes of students participating in engineering-focused design instruction. Journal of Technology Education, 19(2), 50–64.Google Scholar
  27. Kelley, T. R. (2017). Design sketching: A lost skill. Technology and Engineering Teacher, 76(8), 8–12.Google Scholar
  28. Kelley, T. R., Brenner, D. C., & Pieper, J. T. (2010). Two approaches to engineering design: Observations in stem education. Journal of stem Teacher Education, 47(2), 5–40.Google Scholar
  29. Kelley, T. R., Capobianco, B. M., & Kaluf, K. J. (2015). Concurrent think-aloud protocols to assess elementary design students. International Journal of Technology and Design Education, 25(4), 521–540.Google Scholar
  30. Kelley, T. R., & Sung, E. (2017a). Examining elementary school students’ transfer of learning through engineering design think-aloud protocol analysis. Journal of Technology Education, 28(2), 83–108.Google Scholar
  31. Kelley, T. R., & Sung, E. (2017b). Sketching by design: Teaching sketching to young learners. International Journal of Technology and Design Education, 27(3), 363–386.Google Scholar
  32. Lammi, M. D. (2011) Characterizing high school students’ systems thinking in engineering design through the function–behavior–structure (FBS) framework. All Graduate Theses and Dissertations. Paper 849. http://digitalcommons.usu.edu/etd/849.
  33. Lammi, M. D., & Becker, K. (2013). Engineering design thinking. Journal of Technology Education, 24(2), 55–77.Google Scholar
  34. Lammi, M. D. & Gero, J. S. (2011). Comparing design cognition of undergraduate engineering students and high school pre-engineering students. In Paper presented at the 2011 frontiers in education conference, Rapid City, SD.Google Scholar
  35. Major, C., & Savin-Baden, M. (2010). An introduction to qualitative research synthesis: Managing the information explosion in social science research. New York, NY: Routledge.Google Scholar
  36. McKim, R. H. (1980). Experiences in visual thinking. Boston, MA: PWS Publishers.Google Scholar
  37. Mentzer, N. (2014). Team based engineering design thinking. Journal of Technology Education, 25(2), 52–72.Google Scholar
  38. Mentzer, N., Becker, K., & Sutton, M. (2015). Engineering design thinking: High school students’ performance and knowledge. Journal of Engineering Education, 104(4), 417–432.Google Scholar
  39. Middleton, H. E (1998). The role of visual imagery in solving complex problems in design. Unpublished Dissertation. Griffith University.Google Scholar
  40. Moore, P. L., Atman, C. J., Bursic, K. M., Shuman, L. J. & Gottfried, B. S. (1995). Do freshmen design texts adequately define the engineering design process? In ASEE annual conference proceedings.Google Scholar
  41. National Academy of Engineering and National Research Council. (2014). STEM integration in K-12 education: Status, prospects, and an agenda for research. Washington, DC: The National Academies Press.  https://doi.org/10.17226/18612.Google Scholar
  42. Noblit, G. W., & Hare, R. D. (1988). Meta-ethnography: Synthesizing qualitative studies. Newbury Park, CA: Sage.Google Scholar
  43. Purcell, A. T., Gero, J. S., Edwards, H., & McNeill, T. (1996). The data in design protocols: The issue of data coding, data analysis in the development of models of the design process. In N. Cross, H. Christiaans, & K. Dorst (Eds.), Analysing design activity (pp. 225–252). Chichester: Wiley.Google Scholar
  44. Sandelowski, M., Docherty, S., & Emden, C. (1997). Qualitative meta-synthesis: Issues and techniques. Research in Nursing & Health, 20, 365–371.Google Scholar
  45. Scruggs, T. E., Mastropieri, M. A., & McDuffie, K. A. (2006). Summarizing qualitative research in special education: Purposes and procedures. In T. E. Scruggs & M. A. Mastropieri (Eds.), Advances in learning and behavioural disabilities (Vol. 19, pp. 325–346)., Applications of research methodology Oxford, UK: Elsevier.Google Scholar
  46. Sorby, S. A. (2009). Educational research in developing 3-D spatial skills for engineering students. International Journal of Science Education, 31(3), 459–480.Google Scholar
  47. Sorby, S. A., & Baartmans, B. J. (1996). A course for the development of 3-D spatial visualization skills. Engineering Design Graphics Journal, 60(1), 13–20.Google Scholar
  48. Strimel, G. J. (2014). Engineering design: A cognitive process approach (Doctoral dissertation). Retrieved from ProQuest Dissertations and Theses database. (UMI No. 3662376).Google Scholar
  49. Strimel, G. J., Grubbs, M. E., & Wells, J. G. (2016). Engineering education: A clear decision. Technology and Engineering Teacher, 76(1), 19–24.Google Scholar
  50. Welch, M. (1996). The strategies used by ten grade 7 students, working in single-sex dyads, to solve a technological problem. Unpublished doctoral dissertation, McGill University, Montreal, Canada.Google Scholar
  51. Welch, M., & Lim, H. S. (2000). The strategic thinking of novice designers: Discontinuity between theory and practice. Journal of Technology Studies, 26(2), 34–44.Google Scholar
  52. Wells, J., Lammi, M., Grubbs, M., Gero, J., Paretti, M. & Williams, C. (2014). Design cognition of high school students: Initial comparison of those with and without pre-engineering experiences. In Proceedings of the technology education research conference, Australia.Google Scholar
  53. Wilson, A. A., Smith, E. R., & Householder, D. L. (2013). High school students’ cognitive activity while solving authentic problems through engineering design processes. In Proceedings of the American Society of engineering education. Atlanta, Georgia.Google Scholar
  54. Zimmer, L. (2006). Qualitative meta-synthesis: A question of dialoguing with texts. Journal of Advanced Nursing, 53, 311–318.Google Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of Technology Leadership and InnovationPurdue UniversityWest LafayetteUSA
  2. 2.School of Engineering EducationPurdue UniversityWest LafayetteUSA
  3. 3.Career and Technology EducationBaltimore County Public SchoolsTowsonUSA
  4. 4.Department of Integrative STEM EducationThe College of New JerseyEwing TownshipUSA

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