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Understanding and Identifying Cognitive Load in Networked Learning

  • Benjamin A. Kehrwald
  • Brendan P. Bentley
Chapter
  • 9 Downloads
Part of the Research in Networked Learning book series (RINL)

Abstract

This chapter explores cognitive load theory (CLT) in the context of networked learning (NL). CLT supports NL practitioners’ efforts to understand and eliminate barriers to learning in NL situations. The premise is that by recognising unnecessary cognitive load in NL, educators can improve learners’ abilities to acquire and develop schema and, in doing so, support learning in NL situations. The chapter is structured into three main sections. The first section provides the background to the exploration of CLT in the context of NL. It includes an overview of CLT and its development, an overview of NL and a definition of the problem. The second section explores common features of NL and identifies potential sources of cognitive load in NL situations. It is organised according to the key features of NL ‘architecture’: the learning environment, learning tasks and learner activity. The third section identifies a potential research agenda to guide further explorations of CLT in NL including: research into technical aspects of NL to improve the presentation of information and computer interfaces, research into the use of instructional design techniques sympathetic to CLT and specifically targeting NL and engagement tasks and research to understand learning to learn online in NL from a CLT perspective.

Keywords

Cognitive load theory Cognitive load Networked learning Online learning Online teaching 

References

  1. J.B. Arbaugh, Learning to learn online: a study of perceptual changes between multiple online courses. Internet High. Educ. 7(3), 169–182 (2004)CrossRefGoogle Scholar
  2. P. Ayers, Using subjective measures to detect variations of intrinsic cognitive load within problems. Learn. Instr. 16(5), 389–400 (2006)CrossRefGoogle Scholar
  3. P. Ayers, Can the isolated-elements strategy be improved by targeting points of high cognitive load for additional practice? Learn. Instr. 23, 115–124 (2013)Google Scholar
  4. J.S. Brown, P. Duguid, The Social Life of Information (Harvard Business School Press, Boston, 2000)Google Scholar
  5. R. Brunken, J.L. Plass, D. Leutner, Direct measurement of cognitive load in multimedia learning. Educ. Psychol. 38(1), 53–61 (2003)CrossRefGoogle Scholar
  6. R. Brünken, J.L. Plass, D. Leutner, Direct measurement of cognitive load in multimedia learning. Educ. Psychol. 38(1), 53–61 (2003)CrossRefGoogle Scholar
  7. M. Castells, The Information Age: Economy, Society and Culture, vol 1 (Blackwell, Oxford, 1996)Google Scholar
  8. P. Chandler, J. Sweller, Cognitive load theory and the format of instruction. Cogn. Instr. 8(4), 293–332 (1991).  https://doi.org/10.1207/s1532690xci0804_2CrossRefGoogle Scholar
  9. M. Collins, Z. Berge, Facilitating interaction in computer mediated online courses. FSU/AECT Distance Education Conference (1996), Retrieved from http://www.emoderators.com/moderators/flcc.html
  10. M. Daneman, P.A. Carpenter, Individual differences in working memory and reading. J. Verbal Learn. Verbal Behav. 19(4), 450–466 (1980)CrossRefGoogle Scholar
  11. T. De Jong, Cognitive load theory, educational research, and instructional design: some food for thought. Instr. Sci. 38(2), 105–134 (2010)CrossRefGoogle Scholar
  12. J. Dron, From transactional distance to transactional control, in Control and Constraint in E-learning: Choosing When to Choose, (Idea Group, Hershey, 2007), pp. 18–39CrossRefGoogle Scholar
  13. D.F. Feldon, Cognitive load and classroom teaching: the double-edged sword of automaticity. Educ. Psychol. 42(3), 123–137 (2007)CrossRefGoogle Scholar
  14. S. Fox, Studying networked learning: some implications from socially situated learning theory and actor network theory, in Networked Learning: Perspectives and Issues, ed. by C. Steeples, C. Jones, (Springer, London, 2002), pp. 77–91CrossRefGoogle Scholar
  15. D.R. Garrison, T. Anderson, W. Archer, Critical inquiry in a text-based environment: computer conferencing in higher education. Internet High. Educ. 2(2), 87–105 (2000)Google Scholar
  16. P. Goodyear, S. Banks, V. Hodgson, D. McConnell (eds.), Advances in Research on Networked Learning (Kluwer Academic, Dordrecht, 2004)Google Scholar
  17. N. Hammond, A. Trapp, C. Bennett, Small group teaching across the disciplines: setting the context for networked learning, in Networked Learning: Perspectives and Issues, ed. by C. Steeples, C. Jones, (Springer, London, 2002), pp. 243–252CrossRefGoogle Scholar
  18. C. Jones, M. Asensio, Designs for networked learning in higher education: a phenomenographic investigation of practitioners’ accounts of design, in Networked Learning: Perspectives and Issues, ed. by C. Steeples, C. Jones, (Springer, London, 2002), pp. 253–278CrossRefGoogle Scholar
  19. C. Jones, C. Steeples, Perspectives and issues in networked learning, in Networked Learning: Perspectives and Issues, ed. by C. Steeples, C. Jones, (Springer, London, 2002), pp. 1–14Google Scholar
  20. S. Kalyuga, T.-C. Liu, Guest Editorial: managing cognitive load in technology-based learning environments. Educ. Technol. Soc. 18(4), 1–8 (2015)Google Scholar
  21. S. Kalyuga, P. Chandler, J. Sweller, Managing split-attention and redundancy in multimedia instruction. Appl. Cogn. Psychol. 13(4), 351–371 (1999).  https://doi.org/10.1002/(sici)1099-0720(199908)13:4<351::aid-acp589>3.0.co;2-6CrossRefGoogle Scholar
  22. B.A. Kehrwald, Understanding social presence in text-based online learning environments. Distance Educ. 29(1), 89–106 (2008)CrossRefGoogle Scholar
  23. B.A. Kehrwald, Being online: social presence and subjectivity in online learning. Lond. Rev. Educ. 8(1), 39–50 (2010)CrossRefGoogle Scholar
  24. K. Kreijns, P.A. Kirschner, W. Jochems, H. Van Buuren, Determining sociability, social space, and social presence in (a)synchronous collaborative groups. Cyberpsychol. Behav. 7(2), 155–172 (2004)CrossRefGoogle Scholar
  25. R.E. Mayer, Rote versus meaningful learning. Theory Pract. 41(4), 226–232 (2002).  https://doi.org/10.2307/1477407CrossRefGoogle Scholar
  26. R.E. Mayer, R. Moreno, Nine ways to reduce cognitive load in multimedia learning. Educ. Psychol. 38(1), 43–52 (2003)CrossRefGoogle Scholar
  27. R.E. Mayer, R. Moreno, G.M. Pressley, A split-attention effect in multimedia learning: evidence for dual processing systems in working memory. J. Educ. Psychol. 90(2), 312–320 (1998)CrossRefGoogle Scholar
  28. M.G. Moore, Learner autonomy: the second dimension of independent learning. Convergence 5(2), 76–88 (1972)Google Scholar
  29. M.G. Moore, Towards a theory of independent learning and teaching. J. High. Educ. 44(9), 661–679 (1973)CrossRefGoogle Scholar
  30. R. Moreno, A. Valdez, Cognitive load and learning effects of having students organize pictures and words in multimedia environments: the role of student interactivity and feedback. Educ. Technol. Res. Dev. 53(3), 35–45 (2005)CrossRefGoogle Scholar
  31. G. Morrison, G. Anglin, Research on cognitive load theory: application to e-learning. Educ. Technol. Res. Dev. 53(3), 94–104 (2005)CrossRefGoogle Scholar
  32. S.Y. Mousavi, A. Renkl, J. Sweller, Cognitive load theory: instructional implications of the interaction between information structures and cognitive architecture. Instr. Sci. 32(1), 1–8 (2004)CrossRefGoogle Scholar
  33. E. Murphy, Recognising and promoting collaboration in an online asynchronous discussion. Br. J. Educ. Technol. 35(4), 421–431 (2004)CrossRefGoogle Scholar
  34. B.H. Ngu, S.F. Chung, A.S. Yeung, Cognitive load in algebra: element interactivity in solving equations. Educ. Psychol. 35(3), 271–293 (2015)CrossRefGoogle Scholar
  35. F. Paas, J.J.G. Van Merriënboer, Automation and schema acquisition in learning elementary computer programming: Implications for the design of practice. Comput. Hum. Behav. 6(3), 273–289 (1990)Google Scholar
  36. F. Paas, Training strategies for attaining transfer of problem-solving skill in statistics. J. Educ. Psychol. 84(4), 429–434 (1992)Google Scholar
  37. F. Paas, J.J.G. Van Merriënboer, The efficiency of instructional conditions—an approach to combine mental effort and performance-measures. Hum. Factors 35(4), 737–743 (1993)CrossRefGoogle Scholar
  38. F. Paas, A. Renkl, J. Sweller, Cognitive load theory and instructional design: recent developments. Educ. Psychol. 38(1), 1–4 (2003)CrossRefGoogle Scholar
  39. R.M. Palloff, K. Pratt, Building Learning Communities in Cyberspace: Effective Strategies for the Online Classroom (Jossey-Bass, San Francisco, 1999)Google Scholar
  40. R.M. Palloff, K. Pratt, Lessons from the Cyberspace Classroom: The Realities of Online Teaching (Jossey-Bass, San Francisco, 2001)Google Scholar
  41. J. Preece, Sociability and usability in online communities: determining and measuring success. Behav. Inform. Technol. 20(5), 347 (2001)CrossRefGoogle Scholar
  42. G. Riva, The sociocognitive psychology of computer-mediated communication: the present and future of technology-based interactions. Cyberpsychol. Behav. 5(6), 581–598 (2002)CrossRefGoogle Scholar
  43. C. Steeples, C. Jones, P. Goodyear, Beyond e-learning: a future for networked learning, in Networked Learning: Perspectives and Issues, ed. by C. Steeples, C. Jones, (Springer, London, 2002), pp. 323–342CrossRefGoogle Scholar
  44. J. Sweller, Cognitive load during problem solving: effects on learning. Cogn. Sci. 12(2), 257–285 (1988).  https://doi.org/10.1207/s15516709cog1202_4CrossRefGoogle Scholar
  45. J. Sweller, Cognitive load theory, learning difficulty and instructional design. Learn. Instr. 4(4), 295–312 (1994).  https://doi.org/10.1016/0959-4752(94)90003-5CrossRefGoogle Scholar
  46. J. Sweller, Element interactivity and intrinsic, extraneous, and germane cognitive load. Educ. Psychol. Rev. 22(2), 123–138 (2010).  https://doi.org/10.1007/s10648-010-9128-5CrossRefGoogle Scholar
  47. J. Sweller, P. Chandler, Why some material is difficult to learn. Cogn. Instr. 12(3), 185–233 (1994)CrossRefGoogle Scholar
  48. J. Sweller, J.J.G. Van Merriënboer, F. Paas, Cognitive architecture and instructional design. Educ. Psychol. Rev. 10(3), 251–296 (1998)CrossRefGoogle Scholar
  49. J. Sweller, P. Ayres, S. Kalyuga, Cognitive Load Theory (Springer, New York, 2011)CrossRefGoogle Scholar
  50. K. Trehan, M. Reynolds, Online collaborative assessment: power relations and ‘critical learning’, in Networked Learning: Perspectives and Issues, ed. by C. Steeples, C. Jones, (Springer, London, 2002), pp. 279–292CrossRefGoogle Scholar
  51. L.S. Vygotsky, Mind in Society (Harvard University Press, Cambridge, 1978)Google Scholar
  52. J. Zumbach, M. Mohraz, Cogntive load in hypermedia reading comprehension: influence of text type and linearity. Comput. Hum. Behav. 24(3), 875–887 (2008)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Benjamin A. Kehrwald
    • 1
  • Brendan P. Bentley
    • 2
  1. 1.Auckland University of TechnologyAucklandNew Zealand
  2. 2.University of AdelaideAdelaideAustralia

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