Information-Rich Environments: Single-Sense, Multisensory, and Interactive

  • Delia NeumanEmail author


This chapter defines information-rich environments, explains the range of information objects that constitute such environments, and outlines the learning affordances these objects offer as identified by decades of research in environments that largely predate the Internet and the World Wide Web. Although research interest in such “traditional” environments has waned in recent years, understanding how the characteristics of various information formats can support learning in their own unique ways is prerequisite to exploiting the full learning potential of today’s information-rich environments. The chapter surveys the learning affordances of single-sense, multisensory, and stand-alone interactive information formats both to explore how these formats can support learning in their own right and to provide a foundation for considering how they can support learning in the more complex and interconnected venues available today. Concluding with a focus on interactivity—the primary learning affordance of the twenty-first century’s most compelling learning environments—the chapter ties information to learning across the full range of information-rich environments.


Information Object Cognitive Engagement Digital Game Motion Medium Instructional Medium 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Anderson, D. R., & Collins, P. A. (1988). The impact on children’s education: Television’s influence on cognitive development. Washington, DC: U.S. Department of Education, Office of Educational Research and Improvement. (ERIC Document Reproduction Service No. ED 295 271)Google Scholar
  2. Anderson, L.W., & Krathwohl, D. R. (Eds.) (2001). A taxonomy for learning, teaching, and assessing: A revision of Bloom’s Taxonomy of Educational Objectives. New York: Addison Wesley Longman.Google Scholar
  3. Anglin, G. J., Vaez, H, & Cunningham, K. L. (2004). Visual representations and learning: The role of static and animated graphics. In D. H. Jonassen (Ed.), Handbook of research on educational communications and technology (2nd ed.). (pp. 865–916). Mahwah, NJ: Lawrence Erlbaum.Google Scholar
  4. Barron, A. E. (2004). Audio instruction. In D. H. Jonassen, (Ed.), Handbook of research on educational communications and technology (2nd ed.). (pp. 949–978). Mahwah, NJ: Lawrence Erlbaum.Google Scholar
  5. Bishop, M. J., Amankwatia, T. B., & Cates, W. M. (2008). Sound’s use in instructional software to enhance learning: A theory-to-practice content analysis. Educational Technology Research and Development, 56(4), 467–486.CrossRefGoogle Scholar
  6. Bransford, J.D., Brown, A. L., & Cocking, R. R. (Eds.), How people learn: Brain, mind experience, and school. Washington, DC: National Academy Press.Google Scholar
  7. Clark, R. C. (1983). Reconsidering research on learning from media. Review of Educational Research, 53, 445–460.Google Scholar
  8. Cognition and Technology Group at Vanderbilt. (1991). Technology and the design of generative learning environments. Educational Technology, 31(5), 34–40.Google Scholar
  9. Fletcher, J. D., & Tobias, S. (2005). The multimedia principle. In R.E. Mayer (Ed.), The Cambridge handbook of multimedia learning. (pp. 117–134). Cambridge, MA: Cambridge University Press.Google Scholar
  10. Gee, J. P. (2003). What would a state of the art instructional video game look like? Innovate, 1(6). Available at
  11. Gee, J. P. (2005). What video games have to teach us about learning and literacy. New York: Palgrave Macmillan.Google Scholar
  12. Giannetti, L. (2010). Understanding movies. Boston: Allyn & Bacon.Google Scholar
  13. Gredler, M. E. (2004). Games and simulations and their relationships to learning. In D. H. Jonassen (Ed.), Handbook of research on educational communications and technology (2nd ed.). (pp. 571–581). Mahwah, NJ: Lawrence Erlbaum.Google Scholar
  14. Hannafin, M. J. (1992). Emerging technologies, ISD, and learning environments: Critical perspectives. Educational Technology Research and Development, 40(1), 49–63.CrossRefGoogle Scholar
  15. Hannafin, M. J., Hall, C., Land, S., & Hill, J. (1994). Learning in open-ended environments: Assumptions, methods, and implications. Educational Technology, 34(8), 48–55.Google Scholar
  16. Haystead, M. W., & Marzano, R. J. (2009). Meta-analytic synthesis of studies conducted at Marzano Research Laboratory on instructional strategies. Englewood, CO: Marzano Research Laboratory.Google Scholar
  17. Keegan, M. (1995). Scenario educational software: Design and development of discovery learning. Englewood Cliffs, NJ: Educational Technology Publications.Google Scholar
  18. Kozma, R. B. (1991). Learning with media. Review of Educational Research, 61, 179–211.Google Scholar
  19. Land, S., & Hannafin, M. J. (1996). A conceptual framework for the development of theories-in-action with open-ended learning environments. Educational Technology Research and Development, 44(3), 37–53.CrossRefGoogle Scholar
  20. Lipschultz, D. (January/February 2009). Gaming @ your library. American Libraries, pp. 41–43.Google Scholar
  21. Marchionini, G. (1995). Information seeking in electronic environments. Cambridge, MA: Cambridge University Press.CrossRefGoogle Scholar
  22. Mayer, R. E. (Ed.) (2005). The Cambridge handbook of multimedia learning. New York: Cambridge University Press.Google Scholar
  23. Nicholson, S. (January/February 2009) Library gaming census report. American Libraries, p. 44.Google Scholar
  24. Oliver, K., & Hannafin, M. J. (2001). Developing and refining mental models in open-ended learning environments: A case study. Educational Technology Research and Development, 49(4), 5–32.CrossRefGoogle Scholar
  25. Paivio, A. (1986). Mental representations: A dual coding approach. Oxford, UK. Oxford University Press.Google Scholar
  26. Paivio, A. (1991). Dual coding theory: Retrospect and current status. Canadian Journal of Psychology, 45, 255–287.CrossRefGoogle Scholar
  27. Park, I., & Hannafin, M. J. (1993). Empirically based guidelines for the design of interactive multimedia. Educational Technology Research and Development, 41(3), 63–85.CrossRefGoogle Scholar
  28. Perkins, D. (1991). Technology meets constructivism: Do they make a marriage? Educational Technology, 31(5), 18–23.Google Scholar
  29. Rich, M. (2008). Literacy debate: Online, R U really reading? The New York Times. Available at
  30. Rieber, L. P. (1992). Computer-based microworlds: A bridge between constructivism and direct instruction. Educational Technology Research and Development, 40(1), 93–106.CrossRefGoogle Scholar
  31. Rieber, L. P. (2004). Microworlds. In D. H. Jonassen (Ed.), Handbook of research on educational communications and technology (2nd ed.). (pp. 583–603). Mahwah, NJ: Lawrence Erlbaum.Google Scholar
  32. Roth, W. M., & Roychoudhury, A. (1993). The development of science process skills in authentic contexts. Journal of Research in Science Teaching, 30(2), 127–152.CrossRefGoogle Scholar
  33. Salomon, G. (1972). Can we affect cognitive skills through visual media? A hypothesis and initial findings. AV Communication Review, 20(4), 401–422.Google Scholar
  34. Salomon, G. (1974). Internalization of filmic schematic operations in interaction with learners’ aptitudes. Journal of Educational Psychology, 66, 499–511.CrossRefGoogle Scholar
  35. Salomon, G. (1979). Interaction of meaning, cognition, and learning. An exploration of how symbolic forms cultivate mental skills and affect knowledge acquisition. San Francisco: Jossey-Bass.Google Scholar
  36. Seels, B., Fullerton, K., Berry, L., Horn, L.J. (2004). Research on learning from television (Ch. 12). In D. H. Jonassen (Ed.), Handbook of research on educational communications and technology (2nd ed.). (pp. 249–334). Mahwah, NJ: Lawrence Erlbaum.Google Scholar
  37. Smaldino, S. E., Lowther, D., L., & Russell, J. D. (2008). Instructional technology and media for learning (9th ed.). Upper Saddle River, NJ: Pearson Prentice Hall.Google Scholar
  38. Spiro, R., & Jengh, J. (1990). Cognitive flexibility, random access instruction, and hypertext: Theory and technology for non-linear and multidimensional traversal of complex subject matter. In D. Nix & R. Spiro (Eds.). Cognition, education, and multimedia: Exploring ideas in high technology (pp. 163–205). Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  39. Spiro, R., Feltovich, P., Jacobson, M., & Coulson, R. (1991). Cognitive flexibility, constructivism, and hypertext: Random access instruction for advanced knowledge acquisition in ill-structured domains. Educational Technology, 31(5), 24–33.Google Scholar
  40. Squire, K., Jenkins, H., Holland, W., Miller, H., O’Driscoll, A., Tan, K. P., & Todd, K. (2003). Design principles of next-generation digital gaming for education. Educational technology, 43(5), 17–23.Google Scholar
  41. Streibel, M., Stewart, J., Koedinger, K., Collins, A., & Jungck, J. (1987). MENDEL: An intelligent computer tutoring system for genetics problem solving, conjecturing, and understanding. Machine-mediated Learning, 2(1 & 2), 129–159.Google Scholar
  42. Vygotsky, L. S. (1978). Mind in society: The development of the higher psychological processes. Cambridge, MA: Harvard University Press.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.College of Information Science and TechnologyDrexel UniversityPhiladelphiaUSA

Personalised recommendations