Educational Technology Research and Development

, Volume 53, Issue 3, pp 83–93 | Cite as

Rapid dynamic assessment of expertise to improve the efficiency of adaptive e-learning

  • Slava KalyugaEmail author
  • John Sweller
Special Issue


In this article we suggest a method of evaluating learner experties based on assessment of the content of working memory and the extent to which cognitive load has been reduced by knowledge retrieved from long-term memory. The method was tested in an experiment with an elementary algebra tutor using a yoked control design. In the learner-adapted experimental group, instruction was dynamically tailored to changing levels of expertise using rapid tests of knowledge combined with measures of cognitive load. In the nonadapted control group, each learner was exposed to exactly the same instructional procedures as those experienced by the learner's yoked participant. The experimental group demonstrated higher knowledge and cognitive efficiency gains than the control group.


Cognitive Load Rapid Diagnostic Test Central Executive Instructional Expla Cognitive Efficiency 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Baddeley, A.D. (1986).Working memory. New York: Oxford University Press.Google Scholar
  2. Blessing, S.B., & Anderson, J.R. (1996). How people learn to skip steps.Journal of Experimental Psychology: Learning, Memory, and Cognition, 22, 576–598.CrossRefGoogle Scholar
  3. Camp, G., Paas, F., Rikers, R., & van Merriënboer, J.J.G. (2001). Dynamic problem selection in air traffic control training: A comparison between performance, mental effort, and mental efficiency.Computers in Human Behavior, 17, 575–595.CrossRefGoogle Scholar
  4. 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
  5. Ericsson K.A., & Kintsch, W. (1995). Long-term working memory.Psychological Review, 102, 211–245.CrossRefGoogle Scholar
  6. Kalyuga, S., Ayres, P., Chandler, P., & Sweller, J. (2003). Expertise reversal effect.Educational Psychologist 38, 23–31.CrossRefGoogle Scholar
  7. Kalyuga, S., Chandler, P., Tuovinen, J., & Sweller, J. (2001). When problem solving is superior to studying worked examples.Journal of Educational Psychology, 93, 579–588.CrossRefGoogle Scholar
  8. Kalyuga, S., & Sweller, J. (2004). Measuring knowledge to optimize cognitive load factors during instruction.Journal of Educational Psychology, 96, 558–568.CrossRefGoogle Scholar
  9. Kotovsky, K., Hayes, J.R., & Simon, H.A. (1985). Why are some problem hard? Evidence from Tower of Hanoi.Cognitive Psychology, 17, 248–294.CrossRefGoogle Scholar
  10. Larkin, J., McDermott, J., Simon, D., & Simon, H. (1980). Models of competence in solving physics problems.Cognitive Science, 4, 317–348.CrossRefGoogle Scholar
  11. Miller, G.A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information.Psychological Review, 63, 81–97.CrossRefGoogle Scholar
  12. Paas, F., Tuovinen, J.E., & van Merriënboer, J.J.G. (2005). A motivational perspective on the relation between mental effort and performance: Optimizing learners' involvement in instructional conditions. [This special issue].Educational Technology Research and Development, 53(3), 25–33.CrossRefGoogle Scholar
  13. Paas, F., & van Merriënboer, J.J.G. (1993). The efficiency of instructional conditions: An approach to combine mental-effort and performance measures.Human Factors, 35, 737–743.Google Scholar
  14. Renkl, A., & Atkinson, R.K. (2003). Structuring the transition from example study to problem solving in cognitive skills acquisition: A cognitive load perspective.Educational Psychologist, 38, 15–22.CrossRefGoogle Scholar
  15. Salden, R.J.C.M., Paas, F., Broers N.J., & van Merriënboer, J.J.G. (2004). Mental effort and performance as determinants for the dynamic selection of learning tasks in air traffic control training.Instructional Science, 32, 153–172.CrossRefGoogle Scholar
  16. Shiffrin, R., & Schneider, W. (1977). Controlled and automatic human information processing: II. Perceptual learning, automatic attending, and a general theory.Psychological Review, 84, 127–190.CrossRefGoogle Scholar
  17. Sweller, J. (1988). Cognitive load during problem solving: Effects on learning.Cognitive Science, 12, 257–285.CrossRefGoogle Scholar
  18. Sweller, J. (2003). Evolution of human cognitive architecture. In B. Ross (Ed.)The psychology of learning and motivation, Vol. 43, (pp. 215–266). San Diego, CA: Academic Press.Google Scholar
  19. Sweller, J., Mawer, R., & Ward, M. (1983). Development of expertise in mathematical problem solving.Journal of Experimental Psychology: General, 12, 639–661.CrossRefGoogle Scholar
  20. van Gog, T., Ericsson, K. A., Rikers, R.M.J.P., & Paas, F. (2005). Instructional design for advanced learners: Establishing connections between the theoretical frameworks of cognitive load and deliberate practice. [This special issue].Educational Technology Research and Development, 53(3), 73–81.CrossRefGoogle Scholar
  21. van Merriënboer, J.J.G. (1990). Strategies for programming instruction in high school: Program completion vs. program generation.Journal of Educational Computing Research, 6, 265–287.CrossRefGoogle Scholar
  22. van Merriënboer, J.J.G., Krammer, H.P.M., & Maaswinkel, R.M. (1994). Automating the planning and construction of programming assignments for teaching introductory computer programming. In R. D. Tennyson (Ed.).Automating instructional design, development, and delivey (NATO, ASI Series F, Vol. 119, pp. 61–77). Berlin, Germany: Springer Verlag.Google Scholar

Copyright information

© Association for Educational Communications and Technology 2005

Authors and Affiliations

  1. 1.Educational Assessment Australia at the University of New South WalesSydneyAustralia
  2. 2.School of EducationUniversity of New South WalesAustralia

Personalised recommendations