Instructional Science

, Volume 40, Issue 2, pp 325–349 | Cite as

The influence of perceived information overload on student participation and knowledge construction in computer-mediated communication



Computer-mediated communication (CMC) has been used widely to engage learners in academic discourse for knowledge construction. Due to the features of the task environment, one of the main problems caused by the medium is information overload (IO). Yet the literature is unclear about the impact of IO on student learning. This study therefore investigated the influence of online students’ perceived IO on their participation and knowledge construction in terms of cognitive and metacognitive processing as observed in online discussions via CMC. Interviews with students and computer conferencing transcripts were analyzed both qualitatively and quantitatively. The results indicated that students’ perceived IO might influence their participation and levels of cognitive processing in online discussions. However, the results suggest that IO did not affect every student because some seemed to have learned how to manage IO. The results further suggest the critical role of learners’ metacognitive competence regarding internal management of cognitive load.


Information overload Cognitive load theory Computer-mediated communication Online discussions Knowledge construction 


  1. Angeli, C., Valanides, N., & Bonk, C. J. (2003). Communication in a web-based conferencing system: The quality of computer-mediated interactions. British Journal of Educational Technology, 34(1), 31–43.CrossRefGoogle Scholar
  2. Angelova, M., & Riazantseva, A. (1999). If you don’t tell me, how can I know?: A case study of four international students learning to write the U.S. way. Written Communication, 16(4), 491–525.CrossRefGoogle Scholar
  3. Bannert, M. (2002). Managing cognitive load—recent trends in cognitive load theory. Learning and Instruction, 12, 139–146.CrossRefGoogle Scholar
  4. Bawden, D., Holtham, C., & Courtney, N. (1999). Perspectives on information overload. Aslib Proceedings, 51(8), 249–255.CrossRefGoogle Scholar
  5. Bellingham Public Schools. (1999). Staff use of technology: 1999-2000 Self-evaluation rubric. Retrieved June 30, 2005, from
  6. Berge, Z. L., & Collins, M. P. (1995). Computer-mediated communication and the online classroom: An introduction. In Z. L. Berge & M. P. Collins (Eds.), Computer-medicated communication and the online classroom (Vol. 1, pp. 1–10). Cresskill, NJ: Hampton.Google Scholar
  7. Burge, E. J. (1994). Learning in computer conferenced contexts: The learners’ perspective. Journal of Distance Education, 9(1), 19–43.Google Scholar
  8. Chen, C.-Y., Pedersen, S., & Murphy, K. L. (in press). Online learners’ perceived information overload in asynchronous computer-mediated communication. Research in Learning Technology, 19(2).Google Scholar
  9. Conklin, J. (1987). Hypertext: An introduction and survey. IEEE Computer, 20(9), 17–41.CrossRefGoogle Scholar
  10. Creswell, J. W. (1994). Research design: Qualitative & quantitative approaches. Thousand Oaks, CA: Sage.Google Scholar
  11. Darke, S. (1988). Anxiety and working memory capacity. Cognition and Emotion, 2(2), 145–154.CrossRefGoogle Scholar
  12. DeStefano, D., & LeFevre, J.-A. (2007). Cognitive load in hypertext reading: A review. Computers in Human Behavior, 23, 1616–1641.CrossRefGoogle Scholar
  13. Eastmond, D. V. (1994). Adult distance study through computer conferencing. Distance Education, 15(1), 128–152.CrossRefGoogle Scholar
  14. Eastmond, D. V. (1995). Alone but together: Adult distance study through computer conferencing. Cresskill, NJ: Hampton.Google Scholar
  15. Eisenberg, M. B., & Small, R. V. (1993). Information-based education: An investigation of the nature and role of information attributes in education. Information Processing and Management, 29(2), 263–275.CrossRefGoogle Scholar
  16. Erlich, Z., Erlich-Philip, I., & Gal-Ezer, J. (2005). Skills required for participating in CMC courses: An empirical study. Computers & Education, 44, 477–487.CrossRefGoogle Scholar
  17. Fournier, J. F. (1996). Information overload and technology education. Technology and Teacher Education Annual, 1996, 380–385.Google Scholar
  18. Greene, J. C., Caracelli, V. J., & Graham, W. F. (1989). Toward a conceptual framework for mixed-method evaluation designs. Educational Evaluation and Policy Analysis, 11(3), 255–274.Google Scholar
  19. Harasim, L. M. (1987). Teaching and learning on-line: Issues in computer-mediated graduate courses. Canadian Journal of Educational Communication, 16(2), 117–135.Google Scholar
  20. Harasim, L. M. (1990). Online education: An environment for collaboration and intellectual amplification. In L. M. Harasim (Ed.), Online education: Perspectives on a new environment (pp. 39–64). New York: Praeger.Google Scholar
  21. Harvell, T. (2000). Costs and benefits of incorporating the Internet into the traditional classroom. Unpublished doctoral dissertation, Texas A&M University, College Station, TX.Google Scholar
  22. Henri, F. (1992). Computer conferencing and content analysis. In A. R. Kaye (Ed.), Collaborative learning through computer conferencing: The Najaden papers (pp. 115–136). New York: Springer-Verlag.Google Scholar
  23. Hill, J. R., & Hannafin, M. J. (1997). Cognitive strategies and learning from the World Wide Web. Educational Technology Research and Development, 45(4), 37–64.CrossRefGoogle Scholar
  24. Hiltz, S. R., & Turoff, M. (1985). Structuring computer-mediated communication systems to avoid information overload. Communications of the Association for Computing Machinery, 28(7), 680–689.CrossRefGoogle Scholar
  25. Kear, K. L., & Heap, N. W. (2007). ‘Sorting the wheat from the chaff’: Investigating overload in educational discussion systems. Journal of Computer Assisted Learning, 23, 235–247.CrossRefGoogle Scholar
  26. Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Newbury Park, CA: Sage.Google Scholar
  27. Lindsay, P. H., & Norman, D. A. (1972). Human information processing. New York: Academic Press.Google Scholar
  28. Mason, R., & Kaye, T. (1990). Toward a new paradigm for distance education. In L. Harasim (Ed.), Online education: Perspectives on a new environment (pp. 15–38). New York: Praeger.Google Scholar
  29. Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity to process information. Psychological Review, 63, 79–81.CrossRefGoogle Scholar
  30. Moore, M. G. (2002). What does research say about the learners using computer-mediated communication in distance learning? American Journal of Distance Education, 16(2), 61–64.CrossRefGoogle Scholar
  31. Newman, D. R., Webb, B., & Cochrane, C. (1995). A content analysis method to measure critical thinking in face-to-face and computer supported group learning. Interpersonal Computing and Technology, 3(2), 56–77.Google Scholar
  32. Paas, F. G., & van Merriënboer, J. G. (1994). Instructional control of cognitive load in the training of complex cognitive tasks. Educational Psychology Review, 6(4), 351–371.CrossRefGoogle Scholar
  33. Paulo, H. F. (1999). Information overload in computer-mediated communication and education: Is there really too much information? Implication for distance education. Unpublished master’s thesis, University of Toronto, Toronto, Canada.Google Scholar
  34. Perkins, C., & Murphy, E. (2006). Identifying and measuring individual engagement in critical thinking in online discussions: An exploratory case study. Educational Technology & Society, 9(1), 298–307.Google Scholar
  35. Rouet, J.-F. (2009). Managing cognitive load during document-based learning. Learning and Instruction, 19, 445–450.CrossRefGoogle Scholar
  36. Schellens, T., & Valcke, M. (2006). Fostering knowledge construction in university students through asynchronous discussion groups. Computers & Education, 46(4), 349–370.CrossRefGoogle Scholar
  37. Schwan, S., Straub, D., & Hesse, F. W. (2002). Information management and learning in computer conferences: Coping with irrelevant and unconnected messages. Instructional Science, 30, 269–289.CrossRefGoogle Scholar
  38. Swash, G. (1998). UK business on the internet. New Library World, 99(1144), 238–242.CrossRefGoogle Scholar
  39. Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12, 257–285.CrossRefGoogle Scholar
  40. Sweller, J. (1994). Cognitive load theory, learning difficulty and instructional design. Learning and Instruction, 4, 295–312.CrossRefGoogle Scholar
  41. Sweller, J., van Merriënboer, J. G., & Paas, F. G. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251–296.CrossRefGoogle Scholar
  42. Tashakkori, A., & Teddlie, C. (1998). Mixed methodology: Combining qualitative and quantitative approaches. Thousand Oaks, CA: Sage.Google Scholar
  43. Trevino, L. K., Lengel, R. H., & Daft, R. L. (1987). Media symbolism, media richness, and media choice in organizations: A symbolic interactionist perspective. Communication Research, 15(5), 553–574.CrossRefGoogle Scholar
  44. Valcke, M. (2002). Cognitive load: Updating the theory? Learning and Instruction, 12, 147–154.CrossRefGoogle Scholar
  45. Vonderwell, S., & Zachariah, S. (2005). Factors that influence participation in online learning. Journal of Research on Technology in Education, 38(2), 213–230.Google Scholar
  46. Vrasidas, C., & McIsaac, M. S. (1999). Factors influencing interaction in an online course. American Journal of Distance Education, 13(3), 22–36.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Chun-Ying Chen
    • 1
  • Susan Pedersen
    • 2
  • Karen L. Murphy
    • 2
  1. 1.Center for General EducationNational Taichung University of EducationTaichungTaiwan
  2. 2.Department of Educational PsychologyTexas A&M UniversityCollege StationUSA

Personalised recommendations