Skip to main content

Advertisement

Log in

Developing an Integrative STEM Curriculum for Robotics Education Through Educational Design Research

  • Published:
Journal of Formative Design in Learning Aims and scope Submit manuscript

Abstract

This paper presents an integrative standards-based STEM curriculum that uses robots to develop students’ computational thinking. The need for the project is rooted in both the overall lack of existing materials as well as the need for materials that directly address specific STEM standards in an integrative fashion. The paper details the first mesocycle of an educational design research project (EDR) in which a robust theoretical framework was created to support the development of a 2-week series of robotics lessons. Analysis of evaluation data from 5 fifth-grade teachers and their students revealed that the integrative curriculum supported student problem solving and teacher practices that supported cognitive demand. Implications for research, design, and instruction are discussed.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Alibali, M., & Nathan, M. (2011). Embodiment in mathematics teaching and learning: evidence from learners’ and teachers’ gestures. The Journal of the Learning Sciences, 21(2), 247–286. doi:10.1080/10508406.2011.611446.

    Article  Google Scholar 

  • Barr, D., Harrison, J., & Conery, L. (2011). Computational thinking: a digital age skill for everyone. Learning & Leading with Technology, 38(6), 20–23.

    Google Scholar 

  • Baxter, P., & Jack, S. (2008). Qualitative case study methodology: study design and implementation for novice researchers. The Qualitative Report, 13(4), 544–559.

    Google Scholar 

  • Bers, M. (2010). The TangibleK robotics program: Applied computational thinking for young children. Early Childhood Research and Practice, 12(2), 1–20.

    Google Scholar 

  • Boncoddo, R., Dixon, J. A., & Kelley, E. (2010). The emergence of a novel representation from action: evidence from preschoolers. Developmental Science, 13(2), 370–377. doi:10.1111/j.1467-7687.2009.00905.x.

    Article  Google Scholar 

  • Boston, M. D., & Smith, M. S. (2009). Transforming secondary mathematics teaching: increasing the cognitive demands of instructional tasks used in teachers’ classrooms. Journal for Research in Mathematics Education, 40, 119–156.

    Google Scholar 

  • Brown, R., Brown, J., Reardon, K., & Merrill, C. (2011). Understanding STEM: current perceptions. Technology and Engineering Teacher, 70(6), 5–9.

    Google Scholar 

  • Capraro, R. M., & Han, S. (2014). STEM: the education frontier to meet 21st century challenges. Middle Grades Research Journal, 9(3), xv–xv.

  • Capraro, R. M., Capraro, M. M., & Morgan, J. R. (2013). STEM project-based learning. Rotterdam: SensePublishers: 10(1007), 978–94.

  • Chang, C. W., Lee, J. H., Chao, P. Y., Wang, C. Y., & Chen, G. D. (2010). Exploring the possibility of using humanoid robots as instructional tools for teaching a second language in primary school. Educational Technology & Society, 13(2), 13–24.

    Google Scholar 

  • Daily, S., Leonard, A., Jorg, S., Babu, S., Gunderson, K., & Parmar, D. (2015). Embodying computational thinking: initial design of an emerging technological tool. Technology, Knowledge and Learning, 20, 79–84. doi:10.1007/s10758-014-9237-1.

    Article  Google Scholar 

  • Dick, J., Dildine, J. P., Reese, G. C., Smith, K., Storaasli, M., Travers, K. J., Wotal, S., & Zygas, D. (2005). Engaging students in authentic mathematics activities through calculators and small robots. In W. J. Masalski (Ed.), Technology-supported mathematics learning environments NCTM sixty-seventh yearbook (pp. 318–328). Reston: National Council of Teachers of Mathematics.

    Google Scholar 

  • Furner, J. M., & Kumar, D. D. (2007). The mathematics and science integration argument: a stand for teacher education. Eurasia Journal of Mathematics, Science & Technology Education, 3(3), 185–189.

    Google Scholar 

  • Gonzalez, H. B., & Kuenzi, J. J. (2012). Science, technology, engineering, and mathematics (STEM) education: a primer. Congressional Research Service, Library of Congress.

  • Grover, S., & Pea, R. (2013). Computational thinking in K-12: a review of the state of the field.

  • Han, I. (2013). Embodiment: a new perspective for evaluating physicality in learning. Journal of Educational Computing Research, 49(1), 41–59. doi:10.2190/EC.49.1.b.

    Article  Google Scholar 

  • Hmelo-Silver, C. E., Duncan, R. G., & Chinn, C. A. (2007). Scaffolding and achievement in problem-based and inquiry learning: a response to Kirschner, Sweller, and Clark (2006). Educational Psychologist, 42(2), 99–107.

    Article  Google Scholar 

  • Honey, M., Pearson, G., & Schweingruber, H. (2014). STEM integration in K-12 education: status, prospects, and an agenda for research. Rockville: Committee on Integrated STEM Education: National Research Council.

    Google Scholar 

  • Johnson, L., Adams Becker, S., Estrada, V., & Freeman, A. (2015). NMC horizon report: 2015 K-12 edition. Austin: The New Media Consortium.

    Google Scholar 

  • Kapur, M. (2008). Productive failure. Cognition and Instruction, 26(3), 379–424. doi:10.1080/07370000802212669.

    Article  Google Scholar 

  • Kapur, M., & Bielaczyc, K. (2011). Classroom-based experiments in productive failure. In Proceedings of the 33rd annual conference of the Cognitive Science Society (pp. 2812–2817). Austin: Cognitive Science Society.

    Google Scholar 

  • Karim, M. E., Lemaignan, S., & Mondada, F. (2015). A review: can robots reshape K-12 STEM education? In Advanced robotics and its social impacts (ARSO), 2015 I.E. International Workshop on (pp. 1–8). IEEE.

  • Kazakoff, E. R., Sullivan, A., & Bers, M. U. (2013). The effect of a classroom-based intensive robotics and programming workshop on sequencing ability in early childhood. Early Childhood Education Journal, 41(4), 245–255.

    Article  Google Scholar 

  • Kennedy, J., Baxter, P., & Belpaeme, T. (2014). Comparing robot embodiments in a guided discovery learning interaction with children. International Journal of Social Robotics, 7, 293–308. doi:10.1007/s12369-014-0277-4.

    Article  Google Scholar 

  • Kennedy, T., & Odell, M. (2014). Engaging students in STEM education. Science Education International, 25(3), 246–258.

    Google Scholar 

  • Khanlari, A. (2016). Teachers’ perceptions of the benefits and the challenges of integrating educational robots into primary/elementary curricula. European Journal of Engineering Education, 41(3), 320–330.

    Article  Google Scholar 

  • Lanzonder, A. (2005). Do two heads search better than one? Effects of student collaboration on web search behaviour and search outcomes. British Journal of Educational Technology, 36(3), 465–475.

    Article  Google Scholar 

  • Levenson, E., Tsamir, P., & Tirosh, D. (2010). Mathematically based and practically based explanations in the elementary school: teachers’ preferences. Journal of Mathematics Teacher Education, 13(4), 345–369.

    Article  Google Scholar 

  • Lin, T., & Anderson, R. (2008). Reflections on collaborative discourse, argumentation, and learning. Contemporary Educational Psychology, 33, 443–448. doi:10.1016/j.cedpsych.2008.06.002.

    Article  Google Scholar 

  • Ma, L. (1999). Knowing and teaching elementary mathematics: teachers’ understanding of fundamental mathematics in China and the United States. Mahwah: Lawrence Erlbaum Associates.

    Google Scholar 

  • Manlove, S., Lazonder, A. W., & de Jong, T. (2006). Regulative support for collaborative scientific inquiry learning. Journal of Computer Assisted Learning, 22, 87–98. doi:10.1111/j.1365-2729.2006.00162.x.

    Article  Google Scholar 

  • Metz, S. S. (2007). Attracting the engineers of 2020 today. In R. Burke & M. Mattis (Eds.), Women and minorities in science, technology, engineering and mathematics: upping the numbers (pp. 184–209). Northampton: Edward Elgar Publishing.

    Google Scholar 

  • McGill, M. M. (2012). Learning to program with personal robots: influences on student motivation. ACM Transactions on Computing Education, 12(1), 4:1–4:32.

    Google Scholar 

  • McKenney, S. E., & Reeves, T. C. (2012). Conducting educational research design: what, why and how. Oxford: Taylor & Francis.

    Google Scholar 

  • Meyrick, K. M. (2012). How STEM education improves student learning. Meridian, 14(1).

  • Morrison, J., French, B., & McDuffie, A. (2015). Identifying key components of teaching and learning in a STEM school. School Science and Mathematics, 115(5), 244–255. doi:10.1111/ssm.12126.

    Article  Google Scholar 

  • National Academies. (2007). Rising above the gathering storm: energizing and employing America for a brighter economic future. Washington: National Academies Press.

    Google Scholar 

  • National Research Council (US). Committee on Highly Successful Schools or Programs for K-12 STEM Education. (2011). Successful K-12 STEM education: identifying effective approaches in science, technology, engineering, and mathematics. Washington: National Academies Press.

    Google Scholar 

  • Nussbaum, E. M. (2008). Collaborative discourse, argumentation, and learning: preface and literature review. Contemporary Educational Psychology, 33(3), 345–359.

    Article  Google Scholar 

  • Pea, R. (1987). Cognitive technologies for mathematics education. In A. Schoenfled (Ed.), Cognitive science and mathematics education (pp. 89–122). Hillsdale: Erlbaum.

    Google Scholar 

  • Perlman, R. (1976). Using computer technology to provide a creative learning environment for preschool children (report no. LOGO-24). Washington: National Science Foundation.

    Google Scholar 

  • Saldaña, J. (2015). The coding manual for qualitative researchers. Los Angeles: Sage.

    Google Scholar 

  • Sengupta, P., Kinnebrew, J., Basu, S., Biswas, G., & Clark, D. (2013). Integrating computational thinking with K-12 science education using agent-based computation: a theoretical framework. Education and Information Technologies, 18, 351–380. doi:10.1007/s10639-012-9240-x.

    Article  Google Scholar 

  • Stein, M. K., Smith, M. S., Henningsen, M., & Silver, E. A. (2000). Implementing standards-based mathematics instruction: a casebook for professional development. New York: Teachers College Press.

    Google Scholar 

  • Stohlmann, M., Moore, T. J., & Roehrig, G. H. (2012). Considerations for teaching integrated STEM education. Journal of Pre-College Engineering Education Research (J-PEER), 2(1), 4. doi:10.5703/1288284314653.

    Article  Google Scholar 

  • Stoltz, S. (2015). Embodied learning. Educational Philosophy and Theory: Incorporating ACCESS, 47(5), 474–487. doi:10.1080/00131857.2013.879694.

    Article  Google Scholar 

  • Sung, W., Ahn, J., Kai, S. M., & Black, J. B. (2017). Effective planning strategy in robotics education: an embodied approach. In Society for Information Technology & Teacher Education International Conference (pp. 1065–1071). Association for the Advancement of Computing in Education (AACE).

  • Tawfik, A. A., Rong, H., & Choi, I. (2015). Failing to learn: towards a unified design approach for failure-based learning. Educational Technology Research and Development, 63(6), 975–994. doi:10.1007/s11423-015-9399-0.

    Article  Google Scholar 

  • Tekkumru-Kisa, M., Stein, M. K., & Schunn, C. (2015). A framework for analyzing cognitive demand and content-practices integration: task analysis guide in science. Journal of Research in Science Teaching, 52(5), 659–685.

    Article  Google Scholar 

  • Wang, H. H., Moore, T. J., Roehrig, G. H., & Park, M. S. (2011). STEM integration: teacher perceptions and practice. Journal of Pre-College Engineering Education Research (J-PEER), 1(2), 2.

    Google Scholar 

  • Wilensky, U., Brady, C. E., & Horn, M. S. (2014). Fostering computational literacy in science classrooms. Communications of the ACM, 57(8), 24–28.

    Article  Google Scholar 

  • Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35.

    Article  Google Scholar 

  • Witney, D., & Smallbone, T. (2011). Wild work: can using wilds enhance student collaboration for group assignment tasks? Innovations in Education and Teaching International, 48(1), 101–110. doi:10.1080/14703297.2010.54376.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to T. J. Kopcha.

Ethics declarations

Conflict of Interest

The work described in this paper was funded in part through Roborobo, Inc., a private company in South Korea. Funding helped support researcher and graduate assistant salaries during the development, implementation, and data collection associated with the curriculum. However, the funding agency had no influence on the collection, analysis, or interpretation of the data. The local school partners involved with this research did not receive any financial benefit from Roborobo Inc.

Additional information

This research was conducted as part of the Research for the Advancement of Innovative Learning (http://rail.coe.uga.edu)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kopcha, T.J., McGregor, J., Shin, S. et al. Developing an Integrative STEM Curriculum for Robotics Education Through Educational Design Research. J Form Des Learn 1, 31–44 (2017). https://doi.org/10.1007/s41686-017-0005-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41686-017-0005-1

Keywords

Navigation