Studying the Effects of Personalized Language and Worked Examples in the Context of a Web-Based Intelligent Tutor
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.
KeywordsCognitive Load Intelligent Tutoring System Expert Model Authoring Tool Cognitive Tutor
Unable to display preview. Download preview PDF.
- 1.Clark, R.C., Mayer, R.E.: e-Learning and the Science of Instruction, Jossey-Bass/Pfeiffer (2003)Google Scholar
- 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.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.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
- 7.Kolb, D.A.: Experiential Learning - Experience as the Source of Learning and Development. Prentice-Hall, New Jersey (1984)Google Scholar
- 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.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.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.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
- 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