Studying the Effects of Personalized Language and Worked Examples in the Context of a Web-Based Intelligent Tutor

  • Bruce M. McLaren
  • Sung-Joo Lim
  • France Gagnon
  • David Yaron
  • Kenneth R. Koedinger
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4053)


Previous studies have demonstrated the learning benefit of personalized language and worked examples. However, previous investigators have primarily been interested in how these interventions support students as they problem solve with no other cognitive support. We hypothesized that personalized language added to a web-based intelligent tutor and worked examples provided as complements to the tutor would improve student (e-)learning. However, in a 2 x 2 factorial study, we found that personalization and worked examples had no significant effects on learning. On the other hand, there was a significant difference between the pretest and posttest across all conditions, suggesting that the online intelligent tutor present in all conditions did make a difference in learning. We conjecture why personalization and, especially, the worked examples did not have the hypothesized effect in this preliminary experiment, and discuss a new study we have begun to further investigate these effects.


Cognitive Load Intelligent Tutoring System Expert Model Authoring Tool Cognitive Tutor 
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. 1.
    Clark, R.C., Mayer, R.E.: e-Learning and the Science of Instruction, Jossey-Bass/Pfeiffer (2003)Google Scholar
  2. 2.
    Murray, T., Ainsworth, S., Blessing, S. (eds.): Authoring Tools for Advanced Technology Learning Environments: Toward Cost-Effective, Adaptive, Interactive, and Intelligent Educational Software. Kluwer Academic Publishers, Dordrecht (2003)Google Scholar
  3. 3.
    Koedinger, K.R., Aleven, V., Heffernan, N.T., McLaren, B.M., Hockenberry, M.: Opening the Door to Non-programmers: Authoring Intelligent Tutor Behavior by Demonstration. In: Lester, J.C., Vicari, R.M., Paraguaçu, F. (eds.) ITS 2004. LNCS, vol. 3220, pp. 162–174. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  4. 4.
    Koedinger, K.R., Anderson, J.R., Hadley, W.H., Mark, M.A.: Intelligent tutoring goes to school in the big city. Int’l. Journal of Artificial Intelligence in Education 8, 30–43 (1997)Google Scholar
  5. 5.
    Beck, I., McKeown, M.G., Sandora, C., Kucan, L., Worthy, J.: Questioning the author: A year long classroom implementation to engage students in text. Elementary School Journal 96, 385–414 (1996)CrossRefGoogle Scholar
  6. 6.
    Moreno, R., Mayer, R.E.: Engaging students in active learning: The case for personalized multimedia messages. Journal of Ed. Psych. 93, 724–733 (2000)CrossRefGoogle Scholar
  7. 7.
    Kolb, D.A.: Experiential Learning - Experience as the Source of Learning and Development. Prentice-Hall, New Jersey (1984)Google Scholar
  8. 8.
    Sweller, J.: Cognitive load theory, learning difficulty and instructional design. Learning and Instruction 4, 295–312 (1994)CrossRefGoogle Scholar
  9. 9.
    Paas, F.G.W.C.: Training strategies for attaining transfer of problem-solving skill in statistics: A cognitive load approach. Journal of Ed. Psych. 84, 429–434 (1992)CrossRefGoogle Scholar
  10. 10.
    Renkl, A.: Learning from Worked-Out Examples: A Study on Individual Differences. Cognitive Science 21, 1–29 (1997)CrossRefGoogle Scholar
  11. 11.
    Trafton, J.G., Reiser, B.J.: The contributions of studying examples and solving problems to skill acquisition. In: Polson, M. (ed.) Proceedings of the 15th Annual Conference of the Cognitive Science Society, pp. 1017–1022 (1993)Google Scholar
  12. 12.
    Gott, S.P., Lesgold, A., Kane, R.S.: Tutoring for Transfer of Technical Competence. In: Wilson, B.G. (ed.) Constructivist Learning Environments, pp. 33–48. Educational Technology Publications, Englewood Cliffs (1996)Google Scholar
  13. 13.
    Aleven, V., Ashley, K.D.: Teaching Case-Based Argumentation Through a Model and Examples: Empirical Evaluation of an Intelligent Learning Environment. In: Proceedings of AIED 1997, pp. 87–94 (1997)Google Scholar
  14. 14.
    Conati, C., Van Lehn, K.: Toward Computer-Based Support of Meta-Cognitive Skills: a Computational Framework to Coach Self-Explanation. Int’l. Journal of Artificial Intelligence in Education 11, 398–415 (2000)Google Scholar
  15. 15.
    Mathan, S.A., Koedinger, K.R.: An Empirical Assessment of Comprehension Fostering Features in an Intelligent Tutoring System. In: Cerri, S.A., Gouardéres, G., Paraguaçu, F. (eds.) ITS 2002. LNCS, vol. 2363, pp. 330–343. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  16. 16.
    Mathan, S.: Recasting the Feedback Debate: Benefits of Tutoring Error Detection and Correction Skills. Ph.D. Dissertation, Carnegie Mellon Univ., Pitts., PA (2003)Google Scholar
  17. 17.
    Bonate, P.L.: Analysis of Pretest-Posttest Designs. Chapman & Hall/CRC, Boca Raton (2000)CrossRefGoogle Scholar
  18. 18.
    Kalyuga, S., Chandler, P., Tuovinen, J., Sweller, J.: When problem solving is superior to studying worked examples. Journal of Ed. Psych. 93, 579–588 (2001)CrossRefGoogle Scholar
  19. 19.
    Chi, M.T.H., Bassok, M., Lewis, M.W., Reimann, P., Glaser, R.: Self-Explanations: How Students Study and Use Examples in Learning to Solve Problems. Cognitive Science 13, 145–182 (1989)CrossRefGoogle Scholar
  20. 20.
    Mayer, R.E., Johnson, L., Shaw, E., Sahiba, S.: Constructing computer-based tutors that are socially sensitive: Politeness in educational software. International Journal of Human Computer Studies 64, 36–42 (2006)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Bruce M. McLaren
    • 1
  • Sung-Joo Lim
    • 1
  • France Gagnon
    • 2
  • David Yaron
    • 3
  • Kenneth R. Koedinger
    • 1
  1. 1.Human-Computer Interaction InstituteCarnegie Mellon UniversityPittsburghUnited States
  2. 2.Faculty of EducationUniversity of British ColumbiaVancouver
  3. 3.Chemistry DepartmentCarnegie Mellon UniversityPittsburghUnited States

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