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Handbook of Research on Educational Communications and Technology pp 675–688Cite as

Advancing Children’s Engineering Through Desktop Manufacturing

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Abstract

Children’s engineering involves design of a solution under specified constraints in response to a particular need or goal. Desktop manufacturing systems enable students to engineer complex solutions with tangible products, expanding the range of possible approaches to engineering education. Desktop manufacturing technologies encompass digital fabrication systems such as 3D printers and computer-controlled die cutting systems and related technologies such as 3D scanners. These systems offer an entry point for advancing children’s engineering as well as connecting to other STEM subjects.

Because desktop manufacturing systems have only recently become affordable in schools and are continuing to evolve rapidly, the conditions under which they may be best used in classrooms are not yet well defined. However, there are several promising directions that may guide future research in this area. The design process involved in desktop manufacturing affords an opportunity for connections among multiple representations. The virtual design on the computer screen and the corresponding physical object that is produced are two representations of the same underlying construct. Negotiating these representations offers connections to mathematics taught in schools such as ratios, proportion, and scaling. Computer-assisted design programs developed as learning tools can capture information about student design choices and underlying thought processes. Construction of physical prototypes through desktop manufacturing involves extensive involvement of motor skills that may have linkages with student achievement. Digital objects and designs developed at one school can be disseminated via the Internet and reproduced at other sites, allowing designs to be shared and adapted for specific educational goals.

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References

  • Ainsworth, S. (2006). DeFT: A conceptual framework for considering learning with multiple representations. Learning and Instruction, 16(3), 183–198.

    Article  Google Scholar 

  • Ainsworth, S., & Loizou, A. (2003). The effects of self-explaining when learning with text or diagrams. Cognitive Science, 27, 669–681.

    Article  Google Scholar 

  • Atman, C., Chimka, J. R., Bursic, K. M., & Nachtmann, H. N. (1999). A comparison of freshman and senior engineering design processes. Design Studies, 20(2), 131–152.

    Article  Google Scholar 

  • Atman, C., Kilgore, D., & McKenna, A. (2008). Characterizing design learning: a mixed-methods study of engineering designers’ use of language. Journal of Engineering Education, 97(3), 309–326.

    Article  Google Scholar 

  • Bailey, R., & Szabo, Z. (2006). Assessing engineering design process knowledge. International Journal of Engineering Education, 22(3), 508–518.

    Google Scholar 

  • Barsalou, L. W. (2010). Grounded cognition: Past, present, and future. Topics in Cognitive Science, 2, 716–724.

    Article  Google Scholar 

  • Berry, R. Q., III, Bull, G., Browning, C., Thomas, C. D., Starkweather, K., & Aylor, J. H. (2010). Preliminary considerations regarding use of digital fabrication to incorporate engineering design principles in elementary mathematics education. Contemporary Issues in Technology and Teacher Education, 10(2), 167–172.

    Google Scholar 

  • Blikstein, P., & Wilensky, U. (2007). Bifocal modeling: a framework for combining computer modeling, robotics and real-world sensing. Paper presented at the annual meeting of the American Educational Research Association (AERA 2007), Chicago, USA.

    Google Scholar 

  • Blikstein, P., & Wilensky, U. (2010). Materialsim: a constructionist agent-based modeling approach to engineering education. In M.J. Jacobson and P. Reimann (Eds.), Designs for learning environments of the future: 17 International perspectives from the learning sciences (pp. 17–60). New York: Springer-Verlag.

    Google Scholar 

  • Bradsher, K. (2010). China drawing high-tech researcher from U.S. The New York Times. Retrieved from http://www.nytimes.com/2010/03/18/business/global/18research.html?ref=keithbradsher&_r=0.

    Google Scholar 

  • Bruner, J. S. (1966). Toward a theory of instruction. Cambridge, MA: Belkapp.

    Google Scholar 

  • Bull, G., & Groves, J. (2009). The democratization of production. Learning and Leading with Technology, 37(3), 36–37.

    Google Scholar 

  • *Bull, G., Knezek, G., & Gibson, D. (2009). A rationale for incorporating engineering education into the teacher education curriculum. Contemporary Issues in Technology and Teacher Education, 9(3), 222–225.

    Google Scholar 

  • Bull, G., Smith, S & Stearns, P. (2011, March). Fab@School: children’s engineering in the elementary classroom. Paper presented at the national conference of the Society for Information Technology and Teacher Education. Nashville, TN.

    Google Scholar 

  • Burghardt, M. D. (2000). Developing the field of children’s engineering, Paper presented at the ERM Division, ASEE 2000 Annual Conference, St. Louis.

    Google Scholar 

  • Burghardt, M. D., Hecht, D., Russo, M., Lauckhardt, J., & Hacker, M. (2010). A study of mathematics infusion in middle school technology education classes. Journal of Technology Education, 22(1), 58–74.

    Google Scholar 

  • 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(4), 301–309.

    Article  Google Scholar 

  • *Chiu, J. L., Bull, G., Berry, R. Q., & Kjellstrom, W. R. (2012). Teaching Engineering Design with Digital Fabrication: Imagining, Creating, and Refining Ideas. In N. Levine & C. Mouza (Eds.), Emerging Technologies for the Classroom: A Learning Sciences Perspective. New York, NY: Springer.

    Google Scholar 

  • Council, N. R. (2011). A framework for K-12 science education: Practices, crosscutting concepts, and core ideas. Washington, DC: The National Academies.

    Google Scholar 

  • Cunningham, C. M. (2009). Engineering is elementary. The Bridge, 30(3), 11–17.

    Google Scholar 

  • Davis, E. E., Pitchford, N. J., & Limback, E. (2011). The interrelation between cognitive and motor development in typically developing children aged 4–11 years is underpinned by visual processing and fine manual control. British Journal of Psychology, 102(3), 569–584.

    Article  Google Scholar 

  • de Koning, B. B., & Tabbers, H. K. (2011). Facilitating understanding of movements in dynamic visualizations: An embodied perspective. Educational Psychology Review, 23, 501–521.

    Article  Google Scholar 

  • Diamond, A. (2000). Close interrelation of motor development and cognitive development and of the cerebellum and prefrontal cortex. Child Development, 71, 44–56.

    Article  Google Scholar 

  • Diamond, A., & Lee, K. (2011). Interventions shown to aid executive function development in children 4 to 12 years old. Science, 333, 959–964.

    Article  Google Scholar 

  • Duncan, R. G., & Reiser, B. J. (2007). Reasoning across ontologically distinct levels: Students’ understandings of molecular genetics. Journal of Research in Science Teaching, 44(7), 938–959.

    Article  Google Scholar 

  • *Dym, C. L., Agogino, A. M., Eris, O., Frey, D. D., & Leifer, L. J. (2005). Engineering design thinking, teaching, and learning. Journal of Engineering Education, 94(1), 103–120.

    Google Scholar 

  • Fortus, D., Dershimer, R. C., Krajcik, J., Marx, R. W., Mamlok, & Naaman, R. (2004). Design-based science and student learning. Journal of Research in Science Teaching, 41(10), 1081–1110.

    Article  Google Scholar 

  • Funk, S. G., Sturner, R. A., & Green, J. A. (1986). Preschool prediction of early school performance: Relationship of McCarthy scales of Children’s abilities prior to school entry to achievement in kindergarten, first and second grades. Journal of School Psychology, 24, 181–194.

    Article  Google Scholar 

  • *Gershenfeld, N. A. (2005). Fab: the coming revolution on your desktop—from personal computers to personal fabrication. New York, NY: Basic Books.

    Google Scholar 

  • Gibson, J. J. (1979). The ecological approach to visual perception. Boston, MA: Houghton Mifflin.

    Google Scholar 

  • Ginsburg, H. P., Klein, A., & Starkey, P. (1998). The development of children’s mathematical knowledge: Connecting research with ­practice. In I. E. Sigel & K. A. Renninger (Eds.), Handbook of child psychology (Child psychology in practice (5th Ed.), Vol. 4, pp. 401–476). New York, NY: Wiley & Sons.

    Google Scholar 

  • Glenberg, A. M. (1997). What memory is for. The Behavioral and Brain Sciences, 2, 1–55.

    Google Scholar 

  • Goldberg, A., Russell, M., & Cook, A. (2003). The effect of computers on student writing: a metaanalysis of studies from 1992 to 2002. Journal of Technology, Learning, and Assessment, 2(1), 1–47.

    Google Scholar 

  • Goldman, S. R. (2003). Learning in complex domains: When and why do multiple representations help? Learning and Instruction, 13(2), 239–244.

    Article  Google Scholar 

  • Grissmer, D., Grimm, K. J., Aiyer, S. M., Murrah, W. M., & Steele, J. S. (2010). Fine motor skills and early comprehension of the world: Two new school readiness indicators. Developmental Psychology, 46(5), 1008–1017.

    Article  Google Scholar 

  • Hayes, C. C., Goel, A. K., Tumer, I. Y., Agogino, A. M., & Regli, W. C. (2011). Intelligent support for product design: Looking backward, looking forward. Journal of Computing and Information Science in Engineering, 11(2), 021007.

    Article  Google Scholar 

  • Hickey, D. T., Kindfield, A. C. H., Horwitz, P., & Christie, M. A. T. (2003). Integrating curriculum, instruction, assessment, and evaluation in a technology-supported genetics learning environment. American Educational Research Journal, 40(2), 495.

    Article  Google Scholar 

  • Hmelo, C. E., Holton, D. L., & Kolodner, J. L. (2000). Designing to learn about complex systems. The Journal of the Learning Sciences, 9(3), 247–298.

    Article  Google Scholar 

  • Horwitz, P. (1995). Linking models to data: Hypermodels for science education. The High School Journal, 79(2), 148–156.

    Google Scholar 

  • Horwitz, P., & Christie, M. (1999). Hypermodels: Embedding curriculum and assessment in computer-based manipulatives. Journal of Education, 181, 1–24.

    Google Scholar 

  • Hsu, M., Cardella, M., & Purzer, S. (2010). Elementary students’ learning progressions and prior knowledge on engineering design process. Paper presented at the Annual Meeting of the National Association for Science Teaching.

    Google Scholar 

  • Hsu, M. C., Purzer, S., & Cardella, M. E. (2011). Elementary teachers’ views about teaching design, engineering, and technology. Journal of Pre-College Engineering Education Research (J-PEER), 1(2), 5.

    Google Scholar 

  • Jin, Y., & Chusilp, P. (2006). Study of mental iteration in different design situations. Design Studies, 27(1), 25–55.

    Article  Google Scholar 

  • Jin, Y., & Li, W. (2007). Design concept generation: A hierarchical coevolutionary approach. Journal of Mechanical Design, Transactions of the ASME, 129(10), 1012–1022.

    Article  Google Scholar 

  • Johnstone, A. H. (1991). Why is science difficult to learn? Things are seldom what they seem. Journal of Computer Assisted Learning, 7, 75–83.

    Article  Google Scholar 

  • Jonson, B. (2005). Design ideation: The conceptual sketch in the digital age. Design Studies, 26(6), 613–624.

    Article  Google Scholar 

  • Kaput, J., & Schorr, R. (2008). The case of SimCalc, algebra, and calculus. Research on Technology and the Teaching and Learning of Mathematics: Cases and Perspectives, 2, 211.

    Google Scholar 

  • *Katehi, L., Pearson, G., & Feder, M. (2009). Engineering in K-12 Education. Washington, DC: The National Academies Press.

    Google Scholar 

  • Kelley, T. R. (2008). Cognitive processes of students participating in engineering-focused design instruction. Journal of Technology Education, 19(2).

    Google Scholar 

  • Kolodner, J. L., Camp, P., Crismond, D., Fasse, B., Gray, J., Holbrook, J., et al. (2003). Problem-based learning meets case-based reasoning in the middle-school classroom: Putting learning by design into practice. The Journal of the Learning Sciences, 12, 495–547.

    Article  Google Scholar 

  • Kozma, R. (2000). The use of multiple representations and the social construction of understanding in chemistry. In M. Jacobson & R. Kozma (Eds.), Innovations in science and mathematics education: Advanced designs for technologies of learning (pp. 314–322). Mahwah, NJ: Erlbaum.

    Google Scholar 

  • Kozma, R. (2003). The material features of multiple representations and their cognitive and social affordances for science understanding. Learning and Instruction, 13(2), 205–226.

    Article  Google Scholar 

  • Lachapelle, C. P., & Cunningham, C. M. (2007). Engineering is elementary: Children’s changing understandings of science and engineering. American Society for Engineering Education Annual. Honolulu, HI: Conference & Exposition.

    Google Scholar 

  • Lakoff, G., & Johnson, M. (1980). Metaphors we live by. Chicago: The University of Chicago Press.

    Google Scholar 

  • Lakoff, G., & Núñez, R. E. (2000). Where mathematics comes from. New York, NY: Basic Books.

    Google Scholar 

  • Landy, J. M., & Burridge, K. (1999). Fundamental motor skills and movement activities for young children. New York, NY: Centre for Applied Research in Education.

    Google Scholar 

  • Leiner, H. C., Leiner, A. L., & Dow, R. S. (1993). The role of the cerebellum in the human brain. Trends in Neurosciences, 16(11), 453–454.

    Article  Google Scholar 

  • Lewis, J., & Wood-Robinson, C. (2000). Genes, chromosomes, cell division and inheritance-do students see any relationship? International Journal of Science Education, 22(2), 177–195.

    Article  Google Scholar 

  • *Lipson H., & Kurman, M., (2010). Factory@Home: The emerging economy of personal fabrication. Report commissioned by the White House Office of Science & Technology Policy.

    Google Scholar 

  • Lubinski, D. (2010). Spatial ability and STEM: a sleeping giant for talent identification and development. Personality and Individual Differences, 49, 344–351.

    Article  Google Scholar 

  • Luo, Z., Jose, P. E., Huntsinger, C. S., & Pigott, T. D. (2007). Fine motor skills and mathematics achievement in East Asian American and European American kindergartners and first graders. British Journal of Developmental Psychology, 25(4), 595–614.

    Article  Google Scholar 

  • Magill, F. N. (Ed.). (1996). International encyclopedia of psychology. London: Fitzroy Dearborn.

    Google Scholar 

  • Malone E., Lipson H., (2006) Fab@Home: the personal desktop fabricator kit, Proceedings of the 17th Solid Freeform Fabrication Symposium, Austin TX.

    Google Scholar 

  • Marbach-Ad, G., & Stavy, R. (2000). Students’ cellular and molecular explanations of genetic phenomena. Journal of Biological Education, 34(4), 200–205.

    Article  Google Scholar 

  • Mentzer, N., & Park, K. (2011). High school students as novice designers. Paper presented at the Annual Conference of the American Society for Engineering Education, Vancouver, BC.

    Google Scholar 

  • Moskal, B. M., Skokan, C., Kosbar, L., Dean, A., Westland, C., Barker, H., et al. (2007). K-12 outreach: Identifying the broader impacts of four outreach projects. Journal of Engineering Education, 96(3), 173–189.

    Article  Google Scholar 

  • National Academy of Engineering, 2012 Bernard M. Gordon Prize. Retrieved January 5, 2012, from http://www.nae.edu/Activities/Projects/Awards/GordonPrize

  • National Science Board. (2007). National action plan for addressing the critical needs of the U.S. science, technology, engineering, and mathematics education system. Washington, DC: National Science Board.

    Google Scholar 

  • Park, G., Lubinski, D., & Benbow C. P. (2010). Recognizing spatial intelligence: our schools, and our society, must do more to ­recognize spatial reasoning, a key kind of intelligence. Scientific American, Retrieved from http://www.scientificamerican.com/article.cfm?id=recognizing-spatial-intel

  • Rivoli, G. J., & Ralston, P. A. S. (2009). Elementary and middle school engineering outreach: Building a STEM pipeline. In B. Bernal, (Ed.), Proceedings of the 2009 ASEE Southeastern Section Conference. Retrieved from http://icee.usm.edu/ICEE/conferences/ASEE-SE-2010/Conference%20Files/ASEE2009/ASEE2009SE%20frame.htm.

  • Robertson, B. F., & Radcliffe, D. F. (2009). Impact of CAD tools on creative problem solving in engineering design. Computer-Aided Design, 41(3), 136–146.

    Article  Google Scholar 

  • Rogers, C., & Portsmore, M. (2004). Bringing engineering to elementary school. Journal of STEM Education, 5(3–4), 17–28.

    Google Scholar 

  • Seitz, J. A. (2000). The bodily basis of thought. New Ideas in Psychology, 18(1), 23–40.

    Article  Google Scholar 

  • Silk, E. M., Schunn, C. D., & Strand-Cary, M. (2009). The impact of an engineering design curriculum on science reasoning in an urban setting. Journal of Science Education and Technology, 18(3), 209–223.

    Article  Google Scholar 

  • Smith, J. P., diSessa, A., & Roschelle, J. (1994). Misconceptions reconceived: A constructivist analysis of knowledge in transition. The Journal of the Learning Sciences, 3(2), 115–163.

    Article  Google Scholar 

  • Society of Manufacturing Engineering. (2009). SME unveils annual Innovations that could change the way you manufacture. Retrieved from http://www.sme.org/cgi-bin/get-press.pl?%26%2620090016%26PR%26%26SME%26

  • Svihla, V., & Petrosino, A. J. (2008). Improving our understanding of K-12 engineering education. Paper presented at the International Conference on Engineering Education. Heraklion, Greece.

    Google Scholar 

  • Tseng, T., Bryant, C., & Blikstein, P. (2011) Mechanix: an interactive display for exploring engineering design through a tangible interface. Proceedings of Tangible and Embedded Interaction (IDC 2011), Madeira, Portugal.

    Google Scholar 

  • U.S. Department of Education. (2010). National Educational Technology Plan 2010: Transforming American Education: Learning Powered by Technology. Washington DC: Office of Educational Technology, U.S. Department of Education.

    Google Scholar 

  • Voelcker-Rehage, C. (2005). Der Zusammenhang zwischen motorischer und kognitiver Entwicklung im frühen Kindesalter – Ein Teilergebnis der MODALIS-Studie, [The relationship between motoric and cognitive development in early childhood - A partial result from the MODALIS Study]. Deutsche Zeitschrift für Sportmedizin, 56, 358–359.

    Google Scholar 

  • Woodbury, R., & Burrow, A. (2006). Whither design space. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 20(1), 63–82.

    Google Scholar 

  • Zucker, A. (2008). Transforming schools with technology: How smart use of digital tools helps achieve six key education goals. Cambridge, MA: Harvard Education Publishing Group.

    Google Scholar 

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Acknowledgments

This material is based upon the work supported by the National Science Foundation. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. The authors appreciate helpful comments from the University of Virginia Children’s Engineering research group and thank the teachers and students involved in the projects.

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Authors and Affiliations

  1. University of Virginia, Curry School of Education, 405 Emmet Street, South, Charlottesville, VA, 22903, USA

    Glen Bull, Jennifer Chiu & Robert Berry

  2. Cornell University, 242 Upson Hall, Ithaca, NY, 14853, USA

    Hod Lipson

  3. The Concord Consortium, 25 Love Lane, Concord, MA, 01742, USA

    Charles Xie

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  1. Glen Bull
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  2. Jennifer Chiu
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  4. Hod Lipson
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  5. Charles Xie
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Correspondence to Glen Bull .

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Editors and Affiliations

  1. , Department of Learning Technologies, C, University of North Texas, North Elm 3940, Denton, 76207-7102, Texas, USA

    J. Michael Spector

  2. W. Sunset Blvd. 1812, St. George, 84770, Utah, USA

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  3. , Centr. Instructiepsychol.&-technologie, K.U. Leuven, Andreas Vesaliusstraat 2, Leuven, 3000, Belgium

    Jan Elen

  4. Research Drive, Iacocca A109 111, Bethlehem, 18015, Pennsylvania, USA

    M. J. Bishop

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Bull, G., Chiu, J., Berry, R., Lipson, H., Xie, C. (2014). Advancing Children’s Engineering Through Desktop Manufacturing. In: Spector, J., Merrill, M., Elen, J., Bishop, M. (eds) Handbook of Research on Educational Communications and Technology. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3185-5_54

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