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An effective educational tool: construction kits for fun and meaningful learning

  • Sibel Somyürek
Article

Abstract

The integration of robotics in education is still relatively new and represents an important advance in education practices. So, this paper aims to share the results from the perspectives of both students and trainers in an experimental case research in which LEGO Mindstorms construction kits were used. Sixty-two students between the ages of 8 and 14 participated in the study. Multiple data collection methods were used to ensure the richness and diversity of the data. According to the findings, constructivist learning experiences that students had in this training program were themed into the four major themes; active learning, authentic learning, multiple perspectives and collaborative learning. Learning through construction kits offered opportunities to deepen the students’ understanding of various concepts with hands-on exploration and design, resulting in fun and enjoyment. It also promoted students’ active involvement and fostered the collaboration that leads to developing multiple perspectives.

Keywords

Constructivist learning Interactive learning environments Construction kits Robotic technologies Pedagogical issues 

References

  1. Ackermann, E. K. (1996). Perspective-taking and object construction: Two keys to learning. In Y. Kafai & M. Resnik (Eds.), Constructionism in practice: Designing, thinking and learning in a digital world (pp. 25–37). Mahwah, NJ: Lawrence Erlbaum.Google Scholar
  2. Akpınar, B., & Aydın, K. (2007). Türkiye ve bazı ülkelerin eğitim reformlarının karşılaştırılması. Fırat Üniversitesi Doğu Anadolu Bölgesi Araştırmaları Dergisi, 6(1), 82–88.Google Scholar
  3. Akşit, N. (2007). Educational reform in Turkey. International Journal of Educational Development, 27(2), 129–137.CrossRefGoogle Scholar
  4. Alimisis, D., & Kynigos, C. (2009). Constructionism and robotics in education. In D. Alimisis (Ed.), Teacher education on robotics-enhanced constructivist pedagogical methods (pp. 11–26). School of Pedagogical and Technological Education (ASPETE) ISBN 978-960-6749-49-0. USA: AACE.Google Scholar
  5. Arlegui, J., Menegatti, E., Moro, M. and Pina, A. (2008). Robotics, computer science curricula and interdisciplinary activities. In Proceedings of the TERECoP Workshop Teaching with robotics, Conference SIMPAR 2008 (pp. 10–21). Venice, Italy.Google Scholar
  6. Ausubel, D. P. (1962). A subsumption theory of meaningful verbal learning and retention. The Journal of General Psychology, 66, 213–244.CrossRefGoogle Scholar
  7. Avenstrup, R. (2007). The challenge of curriculum reform and implementation: Some implications of a constructivist approach. Ministry of National Education. Retrieved December, 10, 2010.Google Scholar
  8. Babadogan, C., & Olkun, S. (2006). Program development models and reform in Turkish primary school mathematics curriculum. International Journal for Mathematics Teaching and Learning, 1–6.Google Scholar
  9. Beer, R. D., Hillel, J. C., & Richard, F. D. (1999). Using robotics to teach science and engineering. Communications of the ACM, 42(6), 85–92.CrossRefGoogle Scholar
  10. Benitti, F. B. V. (2012). Exploring the educational potential of robotics in schools: A systematic review. Computers and Education, 58(3), 978–988.CrossRefGoogle Scholar
  11. Bologna (1999). Joint declaration of the European Ministers of Education Convened in Bologna on the 19th of June 1999. European Ministers of Education., retrieved December 3, 2012 from http://www.en.us.es/us/temasuniv/espacio-euro.2004.
  12. Bulut, M. (2007). Curriculum reform in Turkey: A case of primary school mathematics curriculum. Eurasia Journal of Mathematics, Science and Technology Education, 3(3), 203–212.Google Scholar
  13. Cey, T. (2001). Moving towards constructivist classroom, retrieved December 3, 2012 from http://www.usask.ca/education/coursework/802papers/ceyt/ceyt.htm.
  14. Chambers, J. M., Carbonaro, M., & Rex, M. (2007). Scaffolding knowledge construction through robotic technology: A middle school case study. Electronic Journal for the Integration of Technology in Education, 6, 55–70.Google Scholar
  15. Chanlin, L. J. & Chan, K.C. (2000). PBL approach in web-based instruction. Journal of Instructional Psychology, 31(2).Google Scholar
  16. Chioccariello, A., Manca, S., & Sarti, L. (2004). Children’s playful learning with a robotic construction kit. In J. Siraj-Blatchford (Ed.), Developing new technologies for young children (pp. 93–174). UK: Trentham Books Limited.Google Scholar
  17. Cooper, M., Keating, D., Harwin, W., & Dautenhahn, K. (1999). Robots in the classroom: Tools for accessible education. In C. Buhler & H. Knops (Eds.), Assistive technology on the threshold of the new millennium (pp. 448–452). Amsterdam: IOS Press.Google Scholar
  18. Creswell, J. W. (2012). Educational research: Planning, conducting, and evaluating quantitative and qualitative research: International edition (4th ed.). Boston: Pearson Education.Google Scholar
  19. Dewey, J. (1910). How we think. Boston: D.C. Heath & Co.CrossRefGoogle Scholar
  20. Duffy, T. M., & Cunningham, D. J. (1996). Constructivism: Implications for the design and delivery of instruction. In D. H. Jonassen (Ed.), Educational communications and technology (pp. 170–199). New York: Simon & Schuster Macmillan.Google Scholar
  21. Ertl, H. (2006). Educational standards and the changing discourse on education: The reception and consequences of the PISA study in Germany. Oxford Review of Education, 32(5), 619–634.CrossRefGoogle Scholar
  22. Gibbons, B. A. (2003). Supporting elementary science education for English learners: A constructivist evaluation instrument. Journal of Educational Research, 96(6), 371–380.CrossRefGoogle Scholar
  23. Grek, S. (2009). Governing by numbers: The PISA ‘effect’ in Europe. Journal of Education Policy, 24(1), 23–37.CrossRefGoogle Scholar
  24. Gür, B. S., Celik, Z., & Özoğlu, M. (2012). Policy options for Turkey: a critique of the interpretation and utilization of PISA results in Turkey. Journal of Education Policy, 27(1), 1–21.CrossRefGoogle Scholar
  25. Hannafin, M. J., & Hooper, S. R. (1993). Learning principles. In M. Fleming & W. H. Levie (Eds.), Instructional message design: Principles from the behavioral and cognitive sciences (2nd ed.). Englewood Cliffs, NJ: Educational Technology Publications.Google Scholar
  26. Honebein, P. C., Duffy, T. M., & Fishman, B. J. (1993). Constructivism and the design of learning environments: Context and authentic activities for learning. Designing environments for constructive learning (pp. 87–108). Berlin: Springer.CrossRefGoogle Scholar
  27. Hsieh, H. F., & Shannon, S. E. (2005). Three approaches to qualitative content analysis. Qualitative Health Research, 15(9), 1277–1288.CrossRefGoogle Scholar
  28. Jermann, P., Soller, A., & Muehlenbrock, M. (2001). From mirroring to guiding: A review of the state of the art technology for supporting collaborative learning. In P. Dillenbourg, A. Eurelings, & K. Hakkarainen (Eds.), EuroCSCL 2001 proceedings: European perspectives on computer-supported collaborative learning (pp. 324–331). Maastricht, The Netherlands: Maastricht McLuhan Institute.Google Scholar
  29. Johnson, P. A. (1999). Problem-based, cooperative learning in the engineering classroom. Journal of Professional Issues in Engineering Education and Practice, 125(1), 8–11.CrossRefGoogle Scholar
  30. Johnson, M. S., & Finucane, P. M. (2000). The emergence of problem-based learning in medical education. Journal of Evaluation in Clinical Practice, 6(3), 281–291.CrossRefGoogle Scholar
  31. Johnson, D. W., & Johnson, R. (1999). Learning together and alone: Cooperative, competitive, and individualistic learning. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
  32. Jonassen, D. H. (1991). Objectivism versus constructivism: Do we need a new philosophical paradigm? Educational Technology Research and Development, 39(3), 5–14.CrossRefGoogle Scholar
  33. Jonassen, D. H. (1999). Designing constructivist learning environments. In C. M. Reigeluth (Ed.), Instructional-design theories and models (Vol. II, pp. 215–239). New Jersey: Lawrence Erlbaum Associates.Google Scholar
  34. Jones, E. D., & Southern, T. W. (2003). Balancing perspectives on mathematics instruction. Focus on Exceptional Children, 35(9), 1–16.Google Scholar
  35. Kelly, D. L. (2003). Overview of PIRLS. PIRLS, 1.Google Scholar
  36. Kynigos, C. (1995). Programming as a means of expressing and exploring ideas in a directive educational system: Three case studies. In A. A. diSessa, C. Hoyles, & R. Noss (Eds.), Computers and exploratory learning NATO ASI Series (pp. 399–420). Berlin: Springer.CrossRefGoogle Scholar
  37. Levy, S. T., & Mioduser, D. (2008). Does it ‘‘want’’ or ‘‘was it programmed to…’’? Kindergarten children’s explanations of an autonomous robot’s adaptive functioning. International Journal of Technology and Design Education, 18, 337–359.CrossRefGoogle Scholar
  38. Li, L-Y, Chang, C-W & Chen, G-D. (2009). Researches on using robots in education. In M. Chang, R. Kuo, K.Kinshuk, G.-D.Chen & M. Hirose (Eds.) Proceeding Edutainment ‘09 Proceedings of the 4th International Conference on E-learning and games: Learning by playing. Game-based education system design and development. Volume 5670/2009, (pp. 479–482). Berlin: Springer.Google Scholar
  39. Liu, E. Z.-F. (2010). Early adolescents’ perceptions of educational robots and learning of robotics. British Journal of Educational Technology, 41(3), E44–E47.CrossRefGoogle Scholar
  40. Mayer, R. E. (2002). Rote versus meaningful learning. Theory into Practice, 41(4), 226–232.CrossRefGoogle Scholar
  41. Mayer, R. E. (2004). Should there be a three-strikes rule against pure discovery learning? American Psychologist, 59(1), 14–19.CrossRefGoogle Scholar
  42. McGrath, J. E., & Hollingshead, A. B. (1993). Putting the “group” back in group support systems: Some theoretical issues about dynamic processes in groups with technological enhancements. In L. M. Jessup & J. S. Valacich (Eds.), Group support systems: New perspectives (pp. 78–96). NY: Macmillan.Google Scholar
  43. Mezirow, J. (1990). How critical reflection triggers transformative learning. Fostering critical reflection in adulthood, 1–20.Google Scholar
  44. Mitnik, R., Nussbaum, M., & Soto, A. (2008). An autonomous educational mobile robot mediator. Autonomous Robot, 25(4), 367–382.CrossRefGoogle Scholar
  45. Moallem, M. (2003). An interactive online course: A collaborative design model. Educational Technology Research and Development, 51(4), 85–103.CrossRefGoogle Scholar
  46. Neo, M. (2003). Developing a collaborative learning environment using a web based design. Journal of Computer Assisted learning, 19, 462–473.CrossRefGoogle Scholar
  47. Norman, G. R., & Schmidt, H. G. (1992). The psychological basis of problem-based learning: A review of the evidence. Academic Medicine, 67(9), 557–565.Google Scholar
  48. Nourbakhsh, I., Crowley, K., Bhave, A., Hamner, E., Hsium, T., Perez-Bergquist, A., et al. (2005). The robotic autonomy mobile robots course: Robot design, curriculum design, and educational assessment. Autonomous Robots, 18(1), 103–127.CrossRefGoogle Scholar
  49. Novak, J. D. (2002). Meaningful learning: The essential factor for conceptual change in limited or inappropriate propositional hierarchies leading to empowerment of learners. Science Education, 86(4), 548–571.CrossRefGoogle Scholar
  50. Nugent, G., Barker, B., Grandgenett, N. & Adamchuk, V. (2009). The use of digital manipulatives in K-12: Robotics, GPS/GIS and programming. In 39th ASEE/IEEE Frontiers in Education Conference. October 18–21, 2009, San Antonio, TX.Google Scholar
  51. OECD. (2004). Learning for Tomorrow’s World. First Results from PISA 2003. France, Paris: OECD.Google Scholar
  52. OECD. (2012). PISA 2012 assessment and analytical framework. Mathematics, reading, science, problem solving and financial literacy. Paris: OECD Publishing.Google Scholar
  53. Papert, S. (1980). Mindstorms: Children, computers and powerful ideas. New York: Basic Books.Google Scholar
  54. Papert, S., & Harel, I. (1991). Situating constructionism. Constructionism, 36, 1–11.Google Scholar
  55. PIRLS (2001). PIRLS 2001 International Report. Availble from http://timssandpirls.bc.edu/pirls2001i/PIRLS2001_Pubs_IR.html Access date: 10 February 2014.
  56. Resnick, M., Martin, F., Berg, R., Borovoy, R., Colella, V., Kramer, K. & Silverman, B. (1998). Digital manipulatives. In Proceedings of the CHI ‘98 conference, Los Angeles.Google Scholar
  57. Resnick, M., & Ocko, S. (1991). LEGO/Logo: Learning through and about design. In I. Harel & S. Papert (Eds.), Constructionism (pp. 141–150). Norwood, NJ: Ablex Publishing.Google Scholar
  58. Riley, K. (2004). Schooling the citizens of tomorrow: The challenges for teaching and learning across the global north/south divide. Journal of Educational Change, 5(4), 389–415.Google Scholar
  59. Rogers, C., & Merredith, P. (2004). Bringing engineering to elementary school. Journal of STEM Education, 5(3/4), 17–28.Google Scholar
  60. Ryu, H. J., Kwak, S. S., & Kim, M. S. (2008). Design factors for external form of robots as elementary school teaching assistants. The Bulletin of Japanese Society for Science of Design (JSSD), 54(5), 39–48.Google Scholar
  61. Sahlberg, P. (2006). Education reform for raising economic competitiveness. Journal of Educational Change, 7(4), 259–287.CrossRefGoogle Scholar
  62. Schank, R. C., Berman, T. R., & Macpherson, K. A. (1999). Learning by doing. In C. M. Reigeluth (Ed.), Instructional design theories and models: A new paradigm of instructional theory (Vol. II, pp. 161–181). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  63. Schmitt, B. (2000). Creating and managing brand experiences on the internet. Design Management Journal (Former Series), 11(4), 53–58.CrossRefGoogle Scholar
  64. Shamlian, S.V., Killfoile, K., Kellogg, R., Duvallet, F. (2006). Fun with robots: A student-taught undergraduate robotics course. Robotics and Automation, 2006. In Proceedings 2006 IEEE International Conference (pp. 369–374), May 15–19, Orlando, Florida, USA.Google Scholar
  65. Shin, N., Jonassen, D. H., & McGee, S. (2003). Predictors of well-structured and ill-structured problem solving in an astronomy simulation. Journal of Research in Science Teaching, 40(1), 6–33.CrossRefGoogle Scholar
  66. Simonson, M. R., & Thompson, A. (1997). Educational computing foundations (3rd ed.). Upper Saddle River, New Jersey: Prentice-Hall Inc.Google Scholar
  67. Skadberg, Y. X., & Kimmel, J. R. (2004). Visitors’ flow experience while browsing a Web site: its measurement, contributing factors and consequences. Computers in Human Behavior, 20(3), 403–422.CrossRefGoogle Scholar
  68. Smith, P. L., Ragan, T. J., & Ragan, T. (1999). Instructional design (2nd ed.). Upper Saddle River, NJ: Prentice-Hall Inc.Google Scholar
  69. Thomson, S., Cresswell, J., & De Bortoli, L. (2004). Facing the future: A focus on mathematical literacy among Australian 15-year-old students in PISA 2003. Camberwell, VIC: Australian Council for Educational Research.Google Scholar
  70. Von Glasersfeld, E. (1993). Questions and answers about radical constructivism. In K. Tobin (Ed.), The practice of constructivism in science education (pp. 23–38). Hillsdale: Lawrence Erlbaum.Google Scholar
  71. Wilson, B. (Ed.). (1996). Constructivist learning environments: Case studies in instructional design. New Jersey: Educational Technology Publications.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Department of Computer Education and Instructional TechnologiesGazi University, Gazi Education FacultyAnkaraTurkey

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