Instructional Science

, Volume 32, Issue 1–2, pp 99–113 | Cite as

Decreasing Cognitive Load for Novice Students: Effects of Explanatory versus Corrective Feedback in Discovery-Based Multimedia

  • Roxana Moreno


This paper examines one of the potentialroles that software agents may have inhelping students reduce working memoryload while learning from discovery-basedmultimedia environments: providingexplanatory feedback. Two studiesexamined the guided feedbackhypothesis according to which, discoverylearning environments that use explanatoryfeedback (EF) to guide novice students inthe process of meaning making promotedeeper learning than those that presentidentical materials using correctivefeedback (CF) alone. In both experiments,the EF group produced higher transferscores, rated the computer game as morehelpful, and gave comparable interest andmotivation ratings than the CF group. Mental load rating scales providedevidence in both experiments that EF waseffective due to reductions in cognitiveload. Results support the use of agentguidance in the form of EF for novicestudents who learn with discovery-basedmultimedia games.


Computer Game Cognitive Load Load Rating Software Agent Corrective Feedback 
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.


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  1. Anderson, R.C. & Pearson, P.D. (1984) A schema-theoretic view of basic processes in reading comprehension. In: P.D. Pearson, R. Barr, M.L. Kamil & P. Mosenthal (eds), Handbook of Reading Research, Vol. 1, pp. 255–291. White Plains, NY: Longman.Google Scholar
  2. Bradshaw, J.M. (ed) (1997) Software Agents. Cambridge, MA: MIT Press.Google Scholar
  3. Brown, A. & Campione, J. (1994) Guided discovery in a community of learners. In: K. McGilly (ed), Classroom Lessons: Integrating Cognitive Theory and Classroom Practice, pp. 229–270. Cambridge, MA: MIT Press.Google Scholar
  4. Bruner, J.S. (1961) The art of discovery, Harvard Educational Review 31: 21–32.Google Scholar
  5. Carlson, R.A., Lundy, D.H. & Schneider, W. (1992) Strategy guidance and memory aiding in learning a problem-solving skill, Human Factors 34: 129–145.Google Scholar
  6. Chall, J.S. (2000) The Academic Achievement Challenge. New York: Guilford Press.Google Scholar
  7. Chi, M., Glaser, R. & Rees, E. (1982) Expertise in problem solving. In: R. Sternberg (ed), Advances in the Psychology of Human Intelligence, pp. 7–75. Hillsdale, NJ: Erlbaum.Google Scholar
  8. Chi, M.T.H., Siler, S.A., Jeong, H., Yamauchi, T. & Hausmann, R.G. (2001) Learning from human tutoring, Cognitive Science 25: 471–533.Google Scholar
  9. Doctorow, M., Wittrock, M.C. & Marks, C. (1978) Generative processes in reading comprehension, Journal of Educational Psychology 70: 109–118.Google Scholar
  10. English, L.D. (ed) (1997) Mathematical Reasoning: Analogies, Metaphors, and Images. Mahwah, NJ: Erlbaum.Google Scholar
  11. Gagne, R.M. (1965) The Conditions of Learning. New York, NY: Holt.Google Scholar
  12. Goswami, U. (1992) Analogical Reasoning in Children. Hillsdale, NJ: Erlbaum.Google Scholar
  13. Halford, G.S. (1993) Children's Understanding: The Development of Mental Models. Hillsdale, NJ: Erlbaum.Google Scholar
  14. Hardiman, P., Pollatsek, A. & Weil, A. (1986) Learning to understand the balance beam, Cognition and Instruction 3: 1–30.Google Scholar
  15. Hiebert, J. & Carpenter, T.P. (1992) Learning and teaching with understanding. In: D.A. Grouws (ed), Handbook of Research on Mathematics Teaching and Learning, pp. 65–97. New York: Macmillan.Google Scholar
  16. Hogarth, R.M., Gibbs, B.J., McKenzie, C.R.M. & Marquis, M.A. (1991) Learning from feedback: Exactingness and incentives, Journal of Experimental Psychology: Learning, Memory, and Cognition 17: 734–752.Google Scholar
  17. Lester, J.C., Stone, B. & Stelling, G. (1999) Lifelike pedagogical agents for mixedinitiative problem solving in constructivist learning environments, User Modeling and User-Adapted Interaction 9: 1–44.Google Scholar
  18. Mayer, R.E. & Moreno, R. (2003) Nine ways to reduce cognitive load in multimedia learning, Educational Psychologist 38: 43–52.Google Scholar
  19. Mayer, R.E. & Moreno, R. (2002) Aids to computer-based multimedia learning, Learning and Instruction 12: 107–119.Google Scholar
  20. McKeough, A., Lupart, J. & Marini, A. (eds) (1995) Teaching for Transfer: Fostering Generalization in Learning. Mahwah, NJ: Erlbaum.Google Scholar
  21. Moreno, R. & Mayer, R.E. (in press) Personalized messages that promote science learning in virtual environments, Journal of Educational Psychology.Google Scholar
  22. Moreno, R. & Mayer, R.E. (2002) Verbal redundancy in multimedia learning: When reading helps listening, Journal of Educational Psychology 94: 156–163.Google Scholar
  23. Moreno, R. & Mayer, R.E. (2000) Engaging students in active learning: The case for personalized multimedia messages, Journal of Educational Psychology 92: 724–733.Google Scholar
  24. Moreno, R. & Mayer, R.E. (1999) Multimedia-supported metaphors for meaning making in mathematics, Cognition and Instruction 17: 215–248.Google Scholar
  25. Moreno, R., Mayer, R.E., Spires, H.A. & Lester, J.C. (2001) The case for social agency in computer-based teaching: Do students learn more deeply when they interact with animated pedagogical agents? Cognition and Instruction 19: 177–214.Google Scholar
  26. Paas, F. & Van Merriënboer J. (1993) The efficiency of instructional conditions: An approach to combine mental-effort and performance measures, Human Factors 35: 737–743.Google Scholar
  27. Paas, F., Renkl, A. & Sweller, J. (2003) Cognitive load theory and instructional design: Recent developments, Educational Psychologist 38: 1–4.Google Scholar
  28. Paas, F., Tuovinen, J.E., Tabbers, H. & Van Gerven, P.W.M. (2003) Cognitive load measurement as a means to advance cognitive theory, Educational Psychologist 38: 63–71.Google Scholar
  29. Paivio, A. (1986) Mental Representations: A Dual Coding Approach. Oxford, England: Oxford University Press.Google Scholar
  30. Peterson, P.L. (1979) Direct instruction reconsidered. In: P.L. Peterson & H.L. Walberg (eds), Research on Teaching: Concepts, Findings and Implications. Berkeley, CA: McCutchan.Google Scholar
  31. Pressley, M., Wood, E., Woloshyn, V., Martin, V., King, A. & Menke, D. (1992) Encouraging mindful use of prior knowledge: Attempting to construct explanatory answers facilitates learning, Educational Psychologist 27: 91–109.Google Scholar
  32. Roughead, W.G. & Scandura, J.M. (1968) What is learned in mathematical discovery, Journal of Educational Psychology 59: 283–289.Google Scholar
  33. Schauble, L. (1990) Belief revision in children: The role of prior knowledge and strategies for generating evidence, Journal of Experimental Child Psychology 49: 31–57.Google Scholar
  34. Singley, M.K. & Anderson, J.R. (1989) The Transfer of Cognitive Skill. Cambridge, MA: Harvard University Press.Google Scholar
  35. Sweller, J. (1999) Instructional Design in Technical Areas. Camberwell, Australia: ACER Press.Google Scholar
  36. Sweller, J., Van Merriënboer, J.J.G. & Paas, F.G.W.C. (1998) Cognitive architecture and instructional design, Educational Psychology Review 10: 251–296.Google Scholar
  37. Tuovinen, J.E. & Sweller, J. (1999) A comparison of cognitive load associated with discovery learning and worked examples, Journal of Educational Psychology 91: 334–341.Google Scholar
  38. Weinert, F. & Helmke, A. (1995) Interclassroom differences in instructional quality and interindividual differences in cognitive development, Educational Psychologist 30: 15–20.Google Scholar
  39. Wittrock, M.C. (1966) The learning by discovery hypothesis. In: L.S. Shulman & E.R. Keislar (eds), Learning by Discovery: A Critical Appraisal, pp. 33–75. Chicago: Rand McNally.Google Scholar

Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • Roxana Moreno
    • 1
  1. 1.Educational Psychology ProgramUniversity of New MexicoAlbuquerque

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