Abstract
Helping students’ improve their metacognitive and self-regulation skills holds the potential to improve students’ ability to learn independently. Yet, to date, there are relatively few success stories of helping students enhance their metacognitive skills using interactive learning environments. In this paper we describe the Self-Assessment Tutor, an intelligent tutoring system for improving the accuracy of the judgments students make regarding their own knowledge. A classroom evaluation of the Self-Assessment Tutor with 84 students found that students improved their ability to identify their strengths while working with the Self-Assessment Tutor. In addition, students transferred the improved self-assessment skills to corresponding sections in the Geometry Cognitive Tutor. However, students often failed to identify their knowledge deficits a-priori and failed to update their assessments following unsuccessful solution attempts. This study contributes to theories of Self-Assessment and provides support for the viability of improving metacognitive skills using intelligent tutoring systems.
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References
Azevedo, R., Moos, D., Greene, J., Winters, F., Cromley, J.: Why is externally-facilitated regulated learning more effective than self-regulated learning with hypermedia? Ed. Tech. Res. And Dev. 56(1), 45–72 (2008)
Aleven, V., Koedinger, K.R.: An effective metacognitive strategy: Learning by doing and explaining with a computer-based Cognitive Tutor. Cog. Sci. 26(2), 147–179 (2002)
Bunt, A., Conati, C., Muldner, K.: Scaffolding self-explanation to improve learning in exploratory learning environments. In: Lester, J.C., Vicari, R.M., Paraguaçu, F. (eds.) ITS 2004. LNCS, vol. 3220, pp. 656–667. Springer, Heidelberg (2004)
Roll, I., Aleven, V., Koedinger, K.R.: The Invention Lab: Using a Hybrid of Model Tracing and Constraint-Based Modeling to Offer Intelligent Support in Inquiry Environments. In: Aleven, V., Kay, J., Mostow, J. (eds.) ITS 2010. LNCS, vol. 6094, pp. 115–124. Springer, Heidelberg (2010)
Biswas, G., Roscoe, R., Jeong, H., Sucler, B.: Promoting self-regulated learning skills in agent-based learning environments. In: Proceedings of the 17th International Conference on Computers in Education (2009) (CDROM)
Roll, I., Aleven, V., McLaren, B.M., Koedinger, K.R.: Improving Students’ Help-Seeking Skills Using Metacognitive Feedback In An Intelligent Tutoring System. Learning and Instruction 21, 267–280 (2011)
Dunning, D., Heath, C., Suls, J.M.: Flawed Self Assessment. Psychological Science In The Public Interest 5(3), 69–106 (2004)
El Saadawi, G.M., Azevedo, R., Castine, M., Payne, V., Medvedeva, O., Tseytlin, E., Legowski, E., Jukic, D., Crowley, R.S.: Factors affecting feeling-of-knowing in a medical intelligent tutoring system: the role of immediate feedback as a metacognitive scaffold. Adv. Health. Sci. Educ. Theory. Pract. (2009)
Nelson-Le Gall, S., Kratzer, L., Jones, E., DeCooke, P.: Children’s self-assessment of performance and task-related help seeking. J. Exp. Child. Psychol. 49, 245–263 (1990)
Gama, C.: Metacognition in interactive learning environments: The reflection assistant model. In: Lester, J.C., Vicari, R.M., Paraguaçu, F. (eds.) ITS 2004. LNCS, vol. 3220, pp. 668–677. Springer, Heidelberg (2004)
Bull, s., Kay, j.: Student Models that Invite the Learner. The SMILI Open Learner Modelling Framework. Int. J. of Art. Int. in Ed. 17(2), 89–120 (2007)
Kruger, J., Dunning, D.: Unskilled and Unaware of It: How Difficulties in Recognizing One’s Own Incompetence Lead to Inflated Self-Assessments. J. of Personality and Soc. Psychol. 77(6), 1121–1134 (1999)
Reder, L.M., Ritter, F.E.: What Determines Initial Feeling of Knowing? Familiarity With Question Terms. J. Exp. Psychol. Learn. Mem. Cogn. (3), 435–451 (1992)
VanLehn, K.: The behavior of tutoring systems. Int. J of AI in Ed. 16(3), 227–265
Roll, I., Aleven, V., McLaren, B.M., Koedinger, K.R.: Designing for metacognition - applying cognitive tutor principles to the tutoring of help seeking. Metacognition and Learning 2(2), 125–140 (2007)
Mathan, S.A., Koedinger, K.R.: Fostering the Intelligent Novice: Learning from errors with metacognitive tutoring. Ed. Psychol. 40(4), 257–265 (2005)
Aleven, V., McLaren, B.M., Sewall, J., Koedinger, K.R.: A new paradigm for intelligent tutoring systems: Example-tracing tutors. Int. J. of AI In ED. 19(2), 105–154 (2008)
Roll, I., Aleven, V., McLaren, B.M., Koedinger, K.R.: Can help seeking be tutored? Searching for the secret sauce of metacognitive tutoring. In: Luckin, R., Koedinger, K.R., Greer, J. (eds.) Proceedings of the International Conference on Artificial Intelligence in Education, pp. 203–210. IOS Press, Amsterdam (2007)
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Roll, I., Aleven, V., McLaren, B.M., Koedinger, K.R. (2011). Metacognitive Practice Makes Perfect: Improving Students’ Self-Assessment Skills with an Intelligent Tutoring System. In: Biswas, G., Bull, S., Kay, J., Mitrovic, A. (eds) Artificial Intelligence in Education. AIED 2011. Lecture Notes in Computer Science(), vol 6738. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21869-9_38
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