Investigating Through Concept Mapping Pre-service Teachers’ Thinking Progression About “e-Learning” and Its Integration into Teaching

Chapter

Abstract

The chapter reports on a study that aimed to investigate the thinking progression and understanding of second year undergraduate pre-service teachers about the concept of “e-learning” before and after the completion of the course Introduction of e-learning. It sought to understand what the students selected as keywords that were associated with e-learning for their pre-course concept maps and how they shifted them in the post-course concept maps to demonstrate their understanding of e-learning and in particular its integration into teaching and learning. A framework for e-learning in the context of teacher education and pre-service teachers’ preparation for ICT integration into professional teaching is developed that forms the basis for the qualitative analysis of the concept maps. The study takes a case-study approach where growth (or non-growth) in thinking between pre- and post-course concept maps was studied in more detail for nine cases, three in each of the high-, middle- and low-scoring groups. The chapter presents and discusses the variations in the students’ thinking as demonstrated by their concept maps, and discusses the benefits and limitations of using concept maps in capturing pre-service teachers’ understanding of e-learning and its integration into their professional teaching.

Keywords

Undergraduate pre-service teachers Pre- and post-concept maps Conceptual understanding e-Learning and integration into teaching and learning 

References

  1. Akinsanya, C., & Williams, M. (2004). Concept mapping for meaningful learning. Nurse Education Today, 24, 41–46.CrossRefGoogle Scholar
  2. Anderson, J. (2005). IT, e-learning and teacher development. International Education Journal, 5(5), 1–14.Google Scholar
  3. Ausubel, D. P. (1968). Educational psychology, a cognitive view. New York, NY: Holt, Rinehart and Winston.Google Scholar
  4. Bruner, J. (1966). Toward a theory of instruction. Cambridge, MA: Harvard University Press.Google Scholar
  5. Gardner, H. (1999). Intelligence reframed: Multiple intelligences for the 21st century. New York, NY: Basic Books.Google Scholar
  6. Hershey, P. A., & Idea Group Publishing New London Group. (1996). A pedagogy of multiliteracies: Designing social futures. Harvard Educational Review, 66(1), 60–92.Google Scholar
  7. Hui, S. K., Huang, Y., & George, E. I. (2008). Model-based analysis of concept maps. Bayesian Analysis 3(3), 479–512.Google Scholar
  8. Jones, A. (2003). ICT and future teachers: Are we preparing for e-learning? Paper presented at the IFIP Working Groups 3.1 and 3.3 Working Conference: ICT and the Teacher of the Future, The University of Melbourne, Australia, 27–31 January, 2003.Google Scholar
  9. Koc, M. (2012). Pedagogical knowledge representation through concept mapping as a study and collaboration tool in teacher education. Australasian Journal of Educational Technology, 28(4), 656–670.Google Scholar
  10. McMahon, M., & Pospisil, R. (2005). Laptops for a digital lifestyle: Millennial students and wireless mobile technologies. In H. Goss (Ed.), ASCILITE 2005 Balance, Fidelity, Mobility: maintaining the momentum? Proceedings of the 22nd annual conference of the Australasian Society for Computers in Learning in Tertiary Education (Vol. 2, pp. 421–431). Brisbane: ASCILITE.Google Scholar
  11. Ministry of Education. (2002). Digital Horizons: learning through ICT. New Zealand: Ministry of Education.Google Scholar
  12. Ng, W., & Hanewald, R. (2010). Concept maps as a tool for promoting online collaborative learning in virtual teams with pre-service teachers in Marriott, R. & Torres, P. (Eds), Handbook of Research on Collaborative Learning using Concept Mapping (pp. 81–99). Hershey, PA, USA: IGI Global Publishing.Google Scholar
  13. Ng, W., (2012). Empowering scientific literacy through digital literacy and multiliteracies. New York, NY: Nova.Google Scholar
  14. Nichols, M. (2003). A theory for eLearning. Educational Technology & Society, 6(2), 1–10.Google Scholar
  15. Nixon, H., Atkinson, S., & Beavis, C. (2006). New media pathways: Navigating the links between home, school and the workplace in Tan, L.W.H. and Subramaniam, R. (Eds.), Handbook of Research on Literacy in Technology at the K1-2 Level (pp. 118–136). Hershey, PA: Idea Group Publishing.Google Scholar
  16. Novak, J. D., & Cañas, A. J. (2006). The origins of the concept mapping tool and the continuing evolution of the tool. Information Visualization, 5, 175–184.CrossRefGoogle Scholar
  17. Novak, J. D., & Gowin, D. B. (1984). Learning how to learn. New York, NY: Cambridge University Press.CrossRefGoogle Scholar
  18. Oblinger, D. G. (2003). Boomers & gen-Xers, millennials: Understanding the “new students”. EDUCAUSE Review, 38(4), 37–47.Google Scholar
  19. Oblinger, D. G., & Oblinger, J. L. (Eds.). (2005). Educating the next generation. Washington, DC: EDUCAUSE.Google Scholar
  20. Papert, S. (1980). Mindstorms. New York, NY: Basic Books.Google Scholar
  21. Piaget, J. (1972). Psychology and epistemology: Towards a theory of knowledge. London: Penguin University Books.Google Scholar
  22. Prensky, M. (2001). Digital Natives, Digital Immigrants. On the Horizon, 9(5). Retrieved July 12, 2012 from http://www.marcprensky.com/writing/prensky-digital natives, digital immigrants-part1.pdf.
  23. Retrieved July 29, 2012, from http://crpit.com/confpapers/CRPITV23Jones.pdf.
  24. Schaal, S., Bogner, F. X., & Girwidz, R. (2010). Concept mapping assessment of media assisted learning in interdisciplinary science education. Research in Science Education, 40, 339–352.CrossRefGoogle Scholar
  25. Shulman, L. S. (1986). Those who understand: Knowledge growth in teaching. Educational Researcher, 15(2), 4–14.CrossRefGoogle Scholar
  26. Shulman, L. S. (1987). Knowledge and teaching: Foundations of the new reform. Harvard Educational Review, 51, 1–22.Google Scholar
  27. So, H. J., & Kim, B. (2009). Learning about problem based learning: Student teachers integrating technology, pedagogy and content knowledge. Australasian Journal of Educational Technology, 25(1), 101–116.Google Scholar
  28. Sun, P.-C., Tsai, R. J., Finger, G., Chen, Y.-Y., & Yeh, D. M. (2008). What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction. Computers & Education, 50, 1183–1202.CrossRefGoogle Scholar
  29. Vygotsky, L. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press.Google Scholar
  30. Wan, Z., Wang, Y., & Haggerty, N. (2008). Why people benefit from e-learning differently: The effects of psychological processes on e-Learning outcomes. Information & Management, 45(8), 513–521.CrossRefGoogle Scholar
  31. Wright, N. (2010). e-Learning and implications for New Zealand schools: A literature review. New Zealand: Ministry of education. Retrieved August 2, 2012, from http://www.educationcounts.govt.nz/_data/assets/pdf_file/0006/77667/948_ELearnLitReview.pdf.

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.School of EducationUniversity of New South Wales (UNSW)SydneyAustralia

Personalised recommendations