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Wearable Technologies to Promote STEM Learning and Attitudes PROCEEDINGS

, , University of Nebraska-Lincoln, United States ; , University of Nebraska at Omaha, United States ; , , University of Nebraska-Lincoln, United States

E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, in Kona, Hawaii, United States Publisher: Association for the Advancement of Computing in Education (AACE), Chesapeake, VA

Abstract

Given their integration of engineering, computing, and fashion, wearable technologies promise to be an excellent interdisciplinary context to support student science, technology, engineering, and math (STEM) learning and interest. The technology can provide an ideal hands-on learning space for female students, who tend to be more interested in textiles and design than their male counterparts. This paper presents initial pilot results from the Wearable Technology project (WearTec), which leverages innovative and emerging wearable technologies for STEM teaching and learning. The current results show the positive effects of a wearable technologies program in increasing students’ knowledge of circuitry and engineering design, as well as their self-efficacy with wearable technologies and producing e-textile products. Results also show that formal and informal educators can develop confidence in delivering wearable technologies curriculum through focused professional development.

Citation

Nugent, G., Barker, B., Grandgenett, N., Melander, J. & Nelson, C. (2015). Wearable Technologies to Promote STEM Learning and Attitudes. In Proceedings of E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 878-883). Kona, Hawaii, United States: Association for the Advancement of Computing in Education (AACE). Retrieved September 21, 2018 from .

Keywords

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References

  1. Albanese, M.A. & Mitchell, S. (1993). Problem-based learning: A review of literature on its outcomes and implementation issues. Academic Medicine, 68, 52–81.
  2. Barker, B., Melander, J., Grandgenett, N. & Nugent, G. (2015). Utilizing wearable technologies as a pathway to STEM. In D. Slykhuis& G. Marks (Eds.), Proceedings of Society for Information Technology& Teacher Education International Conference 2015 (pp. 1770-1776). Chesapeake, VA: Association for the
  3. Barron, B., & Darling-Hammond, L. (2008). Powerful learning: Studies show deep understanding derives from collaborative methods. San Rafael, CA: Edutopia. Retrieved from http://www.edutopia.org/inquiry-projectlearning-research
  4. Buechley, L., Peppler, K., Eisenberg, M., Kafai, Y. (2013). Textile Messages: Dispatches from the world for etextiles and education. New York, NY: Peter Lang.
  5. Hmelo-Silver, C.E. (2004). Problem-based learning: What and how do students learn? Educational Psychology Review, 16, 235–266.
  6. Hmelo, C.E., Gotterer, G.S., & Bransford, J.D. (1997). A theory-driven approach to assessing the cognitive effects of PBL. Instructional Science, 25, 387–408.
  7. Husain, A. (2011). Problem-based learning: A current model of education. Oman Medical Journal, 26, 295.
  8. Jonassen, D. (2000). Computers as mindtools for schools: Engaging critical thinking (2nd ed.). Upper Saddle River, NJ: Prentice-Hall.
  9. Klegeris, A., & Hurren, H. (2011). Impact of problem-based learning in a large classroom setting: Student perception and problem-solving skills. Advances in Physiology Education, 35, 408–415.
  10. McGrath, E., Lowes, S., McKay, M., Sayres, M., & Lin, P. (2012). Robots underwater! Learning science, engineering, and 21st century skills: The evolution of curricula, professional development and research informal and informal contexts. In B.S. Barker, G. Nugent, N. Grandgenett, & V.I. Adamchuk (Eds.), Robots in K–12 education: A new technology for learning (pp. 141–167). Hershey, PA: IGI Global.
  11. Norman, G.R., & Schmidt, H.G. (1992). The psychological basis of problem-based learning: A review of the evidence. Academic Medicine, 67, 557–565.
  12. Nugent, G.C., Barker, B., Grandgenett, N., & Welch, G. (2014). Robotics camps, clubs, and competitions: Results from a US robotics project. In J. Lee, P. Martinet, M. Strand, S. Ghidoni, & M. Munaro (Eds.), Proceedings of 4th International Workshop Teaching Robotics, Teaching with Robotics& 5th International Conference Robotics in Education Padova (Italy) July 18, 2014 (pp. 11–18).
  13. Nugent, G., Barker, B., Welch, G., Grandgenett, N., Wu, C., & Nelson, C. (2015). A model of factors contributing to STEM learning and career orientation. International Journal of Science Education. Advance online publication.
  14. Papert, S. (1993). Mindstorms: Children, computers, and powerful ideas (2nd ed.). New York, NY: Basic Books.
  15. Piaget, J. (1972). The psychology of the child. New York, NY: Basic Books.
  16. Pressley, M., Hogan, K., Wharton-McDonald, R., Mistretta, J., & Ettenberger, S. (1996). The challenges of instructional scaffolding: The challenges of instruction that supports student thinking. Learning Disabilities Research& Practice, 11(3), 138–146.
  17. Riskowski, J., Todd, C., Wee, B., Dark, M., & Harbor, J. (2009). Exploring the effectiveness of an interdisciplinary water resources engineering module in an eighth grade science course. International Journal of Engineering education, 25, 181–195.
  18. Sorge, C. (2007). What happens: relationship of age and gender with science attitudes from elementary to middle school. Science Educator, 16, 33 – 37.
  19. Wiznia, D., Korom, R., Marzuk, P., Safdieh, J., & Grafstein, B. (2012). PBL 2.0: Enhancing problem-based learning through increased student participation. Medical Education Online, 17.

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