Productive thinking in middle school science students’ design conversations in a design-based engineering challenge

  • Maurina L. ArandaEmail author
  • Richard Lie
  • S. Selcen Guzey


Recent education reforms highlight the importance of engineering design as a tool to improve student science learning in this new view of K-12 science education. However, little research has investigated the thought processes students use while engaging in the highly complex activity of design. Therefore, building on theories of productive thinking, we analyzed 6th grade students’ design conversations through the following research question: How do 6th grade students employ different modes of thinking when solving a design-based challenge in a science unit? Through a qualitative and descriptive case-study approach using Gallagher and Aschner’s (Merrill-Palmer Q Behav Dev 9(3):183–194, 1963) analytical framework for productive thinking, our results indicate students employ a variety of modes of thinking as they engage in design conversations in a science-based design unit. While students planned their initial design, they employed Cognitive Memory, Divergent Thinking, and Evaluative Thinking. This is not surprising since students need to recall scientific facts and hypothesize as they begin to justify their design decisions. As students finalized design decisions and communicated this design to the client, they employed more higher order modes of thinking, since they evaluated and justified their design decisions. These findings provide insights into effective teaching strategies for higher productivity and conceptual performance.


Design conversations Productive thinking K-12 STEM 



The authors would like to acknowledge all the participants, including Mr. Fisher and his students, for their contribution to this work. We would also like to acknowledge the research group who placed so much effort into this project and all its research endeavors. This work was funded by NSF grant 1238140, EngrTEAMS: Engineering to Transform the Education of Analysis, Measurement, and Science in a Team-Based Targeted Mathematics-Science Partnership.


  1. Adams, R. (2015). Inquiry into design review conversations. In R. Adams & J. Siddiqui (Eds.), Analyzing design review conversations (pp. 3–22). West Lafayette, IN: Purdue University Press.Google Scholar
  2. Akin, O., & Awolomo, O. (2015). A discursive approach to understand dependencies between design acts. In R. Adams & J. Siddiqui (Eds.), Analyzing design review conversations (pp. 217–240). West Lafayette, IN: Purdue University Press.Google Scholar
  3. Aranda, M. L., Lie, R., Guzey, S. S., Akarsu, M., Johnston, A. C., & Moore, T. J. (2018). Examining teacher talk in an engineering design-based curricular unit. Research in Science Education. Scholar
  4. Atman, C., Cardella, M., Turns, J., & Adams, R. S. (2005). Comparing freshman and senior engineering design processes. Design Studies, 26(4), 325–357.CrossRefGoogle Scholar
  5. Berland, L., Steingut, R., & Ko, P. (2014). High school student perceptions of the utility of the engineering design process. Journal of Science Education and Technology, 23(6), 705–720.CrossRefGoogle Scholar
  6. Brown, T., & Katz, B. (2009). Change by design: How design thinking transforms organizations and inspires innovation. New York, NY: Harper Collins.Google Scholar
  7. Cantrell, P., Pekcan, G., Itani, A., & Velasquez-Bryant, N. (2006). The effects of engineering modules on student learning in middle school science classrooms. Journal of Engineering Education, 95(October), 301–309.CrossRefGoogle Scholar
  8. Dankenbring, C., & Capobianco, B. M. (2016). Examining elementary school students’ mental models of sun-earth relationships as a result of engaging in engineering design. International Journal of Science and Mathematics Education, 14(5), 825–845.CrossRefGoogle Scholar
  9. Dorst, K. (1995). Analyzing design activity: New directions in protocol analysis. Design Studies, 16(2), 139–142.CrossRefGoogle Scholar
  10. Gallagher, J., & Achner, M. (1963). A preliminary report on analyses of classroom interaction. Merrill-Palmer Quarterly of Behavior and Development, 9(3), 183–194.Google Scholar
  11. Groen, C., Paretti, M., & McNair, L. (2015). Learning from student/expert dialogue to enhance engineering design education. In R. Adams & J. A. Siddiqui (Eds.), Analyzing design review conversations (pp. 197–216). West Lafayette, IN: Purdue University Press.Google Scholar
  12. Guilford, J. P. (1956). Structure of intellect. Psychological Bulletin, 53(4), 267–293.CrossRefGoogle Scholar
  13. Guzey, S. S., & Aranda, M. L. (2017). Student participation in engineering practices and discourse: An exploratory case study. Journal of Engineering Education, 106, 585–606. Scholar
  14. Humphries, J., & Ness, M. (2015). Beyond who, what, where, when, why, and how: Preparing students to generate questions in the age of common core standards. Journal of Research in Childhood Education, 4, 551–564.CrossRefGoogle Scholar
  15. Jordan, M., & McDaniel, R. (2014). Managing uncertainty during collaborative problem solving in elementary school teams: The role of peer influence in robotics engineering activity. Journal of the Learning Sciences, 23(4), 490–536.CrossRefGoogle Scholar
  16. Lachapelle, C. P., Cunningham, C. M., & Davis, M. (2017). Middle childhood education: Engineering concepts, practices, and trajectories. In M. J. de Vries (Ed.), Handbook of technology education (pp. 1–17). Switzerland: Springer International Publishing.Google Scholar
  17. Lawson, B. (2005). How designers think. New York, NY: Routledge.Google Scholar
  18. Luck, R. (2009). ‘Does this compromise your design?’ Interactionally producing a design concept in talk. CoDesign, 5(1), 21–34.CrossRefGoogle Scholar
  19. McDonnell, J. (1997). Descriptive models for interpreting design. Design Studies, 18(4), 457–473.CrossRefGoogle Scholar
  20. McDonnell, J., & Lloyd, P. (2009). Analyzing design conversations. CoDesign, 5(1), 1–4.CrossRefGoogle Scholar
  21. Mehalik, M. M., Doppelt, Y., & Schunn, C. D. (2008). Middle-school science through design-based learning versus scripted inquiry: Better overall science concept learning and equity gap reduction. Journal of Engineering Education, 97(1), 71–85.CrossRefGoogle Scholar
  22. National Research Council. (2001). Theoretical foundation for decision making in engineering design. Washington, DC: The National Academies Press.Google Scholar
  23. National Research Council. (2012). A framework for K–12 science education. Retrieved June 1, 2018 from
  24. NGSS Lead States. (2013). Next generation science standards: For states, by states. Washington, DC: The National Academic Press.Google Scholar
  25. Park, D.-Y., Park, M.-H., & Bates, A. B. (2018). Exploring young children’s understanding about the concept of volume through engineering design in a STEM activity: A case study. International Journal of Science and Mathematics Education, 16(2), 1–20.CrossRefGoogle Scholar
  26. Psathas, G. (1995). Conversation analysis: The study of talk in interaction. Thousand Oaks, CA: Sage.CrossRefGoogle Scholar
  27. Rodgers, P. (2013). Articulating design thinking. Design Studies, 34(4), 433–437.CrossRefGoogle Scholar
  28. Schnittka, C. G., & Bell, R. L. (2011). Engineering design and conceptual change in the middle school science classroom. International Journal of Science Education, 33, 1861–1887.CrossRefGoogle Scholar
  29. Silk, E. M., Schunn, C. D., & Cary, M. S. (2009). The impact of an engineering design curriculum on science reasoning in an urban setting. Journal of Science Education and Technology, 18, 209–223.CrossRefGoogle Scholar
  30. Vogler, K. (2005). Improve your verbal questioning. The Clearing House: A Journal of Educational Strategies, Issues, and Ideas, 79(2), 98–103.CrossRefGoogle Scholar
  31. Wendell, K., & Rogers, C. (2013). Engineering design-based science, science content performance, and science attitudes in elementary school. Journal of Engineering Education, 102(4), 513–540.CrossRefGoogle Scholar
  32. Wolmarans, N. (2015). Navigating boundaries: Moving between context and disciplinary knowledge when learning to design. In R. Adams & J. A. Siddiqui (Eds.), Analyzing design review conversations (pp. 197–216). West Lafayette, IN: Purdue University Press.Google Scholar
  33. Yin, R. K. (2014). Case study research: Design and methods. Los Angeles, CA: Sage.Google Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of BiologySan Francisco State UniversitySan FranciscoUSA
  2. 2.Department of Biological SciencesPurdue UniversityWest LafayetteUSA
  3. 3.Department of Curriculum and InstructionPurdue UniversityWest LafayetteUSA

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