An exploratory study of informed engineering design behaviors associated with scientific explanations
Tóm tắt
Design and science inquiry are intertwined during engineering practice. In this study, we examined the relationship between design behaviors and scientific explanations. Data on student design processes were collected as students engaged in a project on designing energy-efficient buildings on a blank square city block surrounded by existing buildings using a computer-aided design program, Energy3D, with built-in solar energy simulation capabilities. We used criterion sampling to select two highly reflective students among 63 high school students. The main data sources were design replays (automatic playback of student design sequences within the CAD software) and electronic notes taken by the students. We identified evidence of informed design such as problem framing, idea fluency, and balancing benefits and trade-offs. Opportunities for meaningful science learning through engineering design occurred when students attempted to balance design benefits and trade-offs. The results suggest that design projects used in classrooms should emphasize trade-off analysis and include time and resources for supporting trade-off decisions through experimentation and reflection. Future research should explore ways to visualize patterns of design behavior based on large samples of students.
Tài liệu tham khảo
Adams, RS, Turns, J, & Atman, CJ. (2003). Educating effective engineering designers: the role of reflective practice. Design Studies, 24(3), 275–294.
Apedoe, XS, Reynolds, B, Ellefson, MR, & Schunn, CD. (2008). Bringing engineering design into high school science classrooms: the heating/cooling unit. Journal of Science Education and Technology, 17(5), 454–465.
Apedoe, XS, & Schunn, CD. (2013). Strategies for success: uncovering what makes students successful in design and learning. Instructional Science, 41(4), 773–791.
Ball, LJ, & Christensen, BT. (2009). Analogical reasoning and mental simulation in design: two strategies linked to uncertainty resolution. Design Studies, 30(2), 169–186.
Baker, RS, Corbett, AT, & Wagner, AZ. (2006). Human classification of low-fidelity replays of student actions. In Proceedings of the Educational Data Mining Workshop at the 8th International Conference on Intelligent Tutoring Systems.
Brophy, S, Klein, S, Portsmore, M, & Rogers, C. (2008). Advancing engineering education in P-12 classrooms. Journal of Engineering Education, 97(3), 369–387.
Bruner, JS. (1961). The act of discovery. Harvard Educational Review, 31, 21–32.
Bucciarelli, LL. (1996). Designing engineers. Cambridge: MIT Press. Chapter 1–2, 6.
Burghardt, MD, & Hacker, M. (2004). Informed design: a contemporary approach to design pedagogy as the core process in technology. The Technology Teacher, 64(1), 6–8.
Cajas, F. (2001). The science/technology interaction: implications for science literacy. Journal of Research in Science Teaching, 38(7), 715–729.
Crismond, DP, & Adams, RS. (2012). The informed design teaching and learning matrix. Journal of Engineering Education, 101(4), 738–797.
Cross, N. (2001). Design cognition: results from protocol and other empirical studies of design activity. In CM Eastman, WM McCracken, & W Newstetter (Eds.), Design Learning and Knowing: Cognition in Design Education. New York: Elsevier Press.
Cross, N. (2006). Designerly ways of knowing. London: Springer. Chapter 1–2.
Daugherty, J, & Mentzer, N. (2008). Analogical reasoning in the engineering design process and technology education applications. Journal of Technology Education, 19(2), 7–21.
Doppelt, Y, Mehalik, MM, Schunn, CD, Silk, E, & Krysinski, D. (2008). Engagement and achievements: a case study of design-based learning in a science context. Journal of Technology Education, 19(2), 22–39.
Dorst, K. (2011). The core of ‘design thinking’ and its application. Design Studies, 32(6), 521–532.
Dubberly, H. (2004). How do you design? A compendium of models. Dubberly Design Office, San Francisco CA. [–Retrieved from http://www.dubberly.com/wp-content/uploads/2008/06/ddo_designprocess.pdf]
Fish, J, & Scrivener, SA. (1990). Amplifying the mind’s eye: sketching and visual cognition. Leonardo, 23(1), 117–126.
Goel, V, & Pirolli, P. (1992). The Structure of design problem spaces. Cognitive Science, 16(3), 395–429.
Goldschmidt, G. (1991). The dialectics of sketching. Creativity Research Journal, 4(2), 123–143.
Goldschmidt, G, & Smolkov, M. (2006). Variances in the impact of visual stimuli on design problem solving performance. Design Studies, 27(5), 549–569.
Hmelo, CE, Holton, DL, & Kolodner, JL. (2000). Designing to learn about complex systems. The Journal of the Learning Sciences, 9(3), 247–298.
Jonassen, DH. (2000). Toward a design theory of problem solving. Educational Technology Research and Development, 48(4), 63–85.
Jonassen, DH. (2012). Designing for decision making. Educational Technology Research and Development, 60(2), 341–359.
Kolko, J. (2010). Abductive thinking and sensemaking: the drivers of design synthesis. Design Issues, 26(1), 5–28.
Kolodner, JL. (2002). Facilitating the learning of design practices: lessons from an inquiry into science education. Journal of Industrial Teacher Education, 39(3), 9–40.
Kolodner, JL, Crismond, D, Fasse, BB, Gray, JT, Holbrook, J, Ryan, M, et al. (2003). Problem-based learning meets case-based reasoning in the middle-school science classroom: putting a learning-by-design curriculum into practice. Journal of the Learning Sciences, 12(4), 495–548.
Lachapelle, CP, & Cunningham, CM. (2014). Engineering in elementary schools. In S Purzer, J Strobel, & ME Cardella (Eds.), Engineering in pre-college settings: synthesizing research, policy, and practices. West Lafayette, IN: Purdue University Press.
Lawson, B, & Dorst, K. (2009). Design expertise. Oxford, UK: Architectural Press (Elsevier).
Lewis, T. (2006). Design and inquiry: bases for an accommodation between science and technology education in the curriculum? Journal of Research in Science Teaching, 43(3), 255–281.
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.
National Research Council. (1996). National science education standards. Washington, DC: National Academies Press.
National Research Council. (2009). Engineering in K-12 education: understanding the status and improving the prospects. Washington, DC: National Academies Press.
National Research Council. (2012). A framework for K-12 science education: practices, crosscutting concepts, and core ideas. Washington, DC: National Academies Press.
Achieve. (2013). Next generation science standards: for states, by states. Washington, DC: National Academies Press.
Paletz, S, Schunn, CD, & Kim, KH. (2013). The interplay of conflict and analogy in multidisciplinary teams. Cognition, 126(1), 1–19.
Papadouris, N. (2012). Optimization as a reasoning strategy for dealing with socioscientific decision‐making situations. Science Education, 96(4), 600–630.
Penner, DE, Giles, ND, Lehrer, R, & Schauble, L. (1997). Building functional models: designing an elbow. Journal of Research in Science Teaching, 34(2), 125–143.
Purzer, Ş, Strobel, J, & Cardella, ME. (2014). Engineering in pre-college settings: synthesizing research, policy, and practices. West Lafayette, IN: Purdue University Press.
Sadler, PM, Coyle, HP, & Schwartz, M. (2000). Engineering competitions in the middle school classroom: key elements in developing effective design challenges. The Journal of the Learning Sciences, 9(3), 299–327.
Scholten, M, & Sherman, SJ. (2006). Tradeoffs and theory: the double-mediation model. Journal of Experimental Psychology, 135, 237–261 and 552.
Schön, DA. (1993). The reflective practitioner: How professionals think in action. New York: Basic Books.
Schnittka, C, & Bell, R. (2011). Engineering design and conceptual change in science: addressing thermal energy and heat transfer in eighth grade. International Journal of Science Education, 33(13), 1861–1887.
Schunn, CD, Silk, EM, & Apedoe, XS. (2012). Engineering in and for science education. In J Shrager & S Carver (Eds.), The journey from child to scientist: Integrating cognitive development and the education sciences (pp. 207–225). Washington, DC: American Psychological Association.
Snetsinger, C, Brewer, C, & Brown, F. (1999). Capture the wind: students get a charge from wind energy. The Science Teacher, 66, 38–42.
Subramanian, K. (1999). Practical physics. The Science Teacher, 66, 37–39.
Svihla, V, & Petrosino, AJ. (2008). Improving our understanding of K-12 engineering education. Paper presented at the International Conference on Engineering Education. Greece: Heraklion.
Valkenburg’s, R. (1998). The reflective practice of design teams. Design Studies, 19(3), 249–271.
Vattam, SS, & Kolodner, JL. (2008). On foundations of technological support for addressing challenges facing design-based science learning. Pragmatics & Cognition, 16(2), 406–437.
Xie, C, Zhang, H, Nourian, S, Pallant, A, & Bailey, S. (2014a). A study of the instructional sensitivity of CAD logs based on time series analysis. International Journal of Engineering Education, 30(4), 760–778.
Xie, C, Zhang, H, Nourian, S, Pallant, A, & Hazzard, E. (2014b). A time series analysis method for assessing engineering design processes using a CAD tool. International Journal of Engineering Education, 30(1), 218–230.
Zhang, Z, Xie, C, & Nourian, S. (2014). Detecting iterative cycles of engineering design from student digital footprints in computer-aided design software. Poster presented at the 2014 International Conference of the Learning Sciences. Boulder CO: International Society of the Learning Sciences.
Zubrowski, B. (2002). Integrating science into design technology projects: using a standard model in the design process. Journal of Technology Education, 13(2), 47–65.