Abstract
Intelligent tutoring systems often emphasize learner control: They let the students decide when and how to use the system’s intelligent and unintelligent help facilities. This means that students must judge when help is needed and which form of help is appropriate. Data about students’ use of the help facilities of the PACT Geometry Tutor, a cognitive tutor for high school geometry, suggest that students do not always have these metacognitive skills. Students rarely used the tutor’s on-line Glossary of geometry knowledge. They tended to wait long before asking for hints, and tended to focus only on the most specific hints, ignoring the higher hint levels. This suggests that intelligent tutoring systems should support students in learning these skills, just as they support students in learning domain-specific skills and knowledge. Within the framework of cognitive tutors, this requires creating a cognitive model of the metacognitive help-seeking strategies, in the form of production rules. The tutor then can use the model to monitor students’ metacognitive strategies and provide feedback.
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References
Aleven, V., K. R. Koedinger, and K. Cross, 1999. Tutoring Answer Explanation Fosters Learning with Understanding. In Artificial Intelligence in Education, Proceedings of AIED-99, edited by S.P. Lajoie and M. Vivet, 199–206. Amsterdam: IOS Press.
Anderson, J. R., F. G. Conrad, and A. T. Corbett, 1989. Skill Acquisition and the LISP Tutor. Cognitive Science, 13, 467–505.
Anderson, J. R., A. T. Corbett, K. R. Koedinger, and R. Pelletier, 1995. Cognitive tutors: Lessons learned. The Journal of the Learning Sciences, 4, 167–207.
Burton, R. R., and J. S. Brown. An Investigation of Computer Coaching for Informal Learning Activities, 1982. In Intelligent Tutoring Systems, edited by D. H. Sleeman and J. S. Brown, New York: Academic Press.
Chi, M. T. H., M. Bassok, M. W. Lewis, P. Reimann, and R. Glaser, 1989. Self-Explanations: How Students Study and Use Examples in Learning to Solve Problems. Cognitive Science, 13, 145–182.
Conati, C., and K. VanLehn, 1999. Teaching Meta-Cognitive Skills: Implementation and Evaluation of a Tutoring System to Guide Self-Explanation While Learning from Examples. In Artificial Intelligence in Education, Proceedings of AIED-99, edited by S. P. Lajoie and M. Vivet, 297–304. Amsterdam: IOS Press.
Katz., S., A. Lesgold, E. Hughes, D. Peters, G. Eggan, M. Gordin, and L. Greenberg, 1998. Sherlock II: An Intelligent Tutoring System Built Upon the LRDC Tutor Framework. In Facilitating the Development and Use of Interactive Learning Environments, edited by C. P. Bloom and R. B. Loftin. Mahwah, NJ: Erlbaum.
McKendree, J., 1990. Effective Feedback Content for Tutoring Complex Skills. Human Computer Interaction, 5, 381–413.
NCTM, 1989. Curriculum and Evaluation Standards for School Mathematics. National Council of Teachers of Mathematics. Reston, VA: The Council.
Paolucci, M., Suthers, D., and A. Weiner, 1996. Automated Advice-Giving Strategies for Scientific Inquiry. In Proceedings of the Third International Conference on Intelligent Tutoring Systems (ITS’96), edited by C. Frasson, G. Gauthier, and A. Lesgold, 372–381. Barlin: Springer-Verlag.
Recker, M. M., and P. Pirolli, 1992. Student Strategies for Learning Programming from a Computational Environment. In Proceedings of the Second International Conference on Intelligent Tutoring Systems, ITS’ 92, edited by C. Frasson, G. Gauthier, and G. I. McCalla, 382–394. Barlin: Springer-Verlag.
Ritter, S., 1997. Communication, Cooperation and Competition among Multiple Tutor Agents. In Artificial Intelligence in Education, Proceedings of AI-ED 97 World Conference, edited by B. du Boulay and R. Mizoguchi, 31–38. Amsterdam: IOS Press.
Shute, V. J., and K. A. Cluck, 1996. Individual Differences in Patterns of Spontaneous Online Tool Use. The Journal of the Learning Sciences, 5(4), 329–355.
VanLehn, K., R. M. Jones, and M. T. Chi, 1992. A Model of the Self-Explanation Effect. The Journal of the Learning Sciences, 2(1), 1–59.
Wood, H. A., and D. J. Wood, in press. Help Seeking, Learning and Contingent Tutoring. To appear in Computers and Education (special edition, 2000).
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Aleven, V., Koedinger, K.R. (2000). Limitations of Student Control: Do Students Know when They Need Help?. In: Gauthier, G., Frasson, C., VanLehn, K. (eds) Intelligent Tutoring Systems. ITS 2000. Lecture Notes in Computer Science, vol 1839. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45108-0_33
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DOI: https://doi.org/10.1007/3-540-45108-0_33
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