Abstract
Successful learning though exploration in open learning environments has been shown to depend on whether students possess the necessary meta-cognitive skills, including systematic exploration, hypothesis generation and hypothesis testing. We argue that an additional meta-cognitive skill crucial for effective learning through exploration is self-explanation: spontaneously explaining to oneself available instructional material in terms of the underlying domain knowledge. In this paper, we describe how we have expanded the student model of ACE, an open learning environment for mathematical functions, to track a learner’s self-explanation behaviour and how we use this model to improve the effectiveness of a student’s exploration.
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References
Aleven, V., Koedinger, K.R.: An Effective Meta-cognitive Strategy: Learning by Doing and Explaining with a Computer-Based Cognitive Tutor. Cognitive Science 26(2), 147–179 (2002)
Bielaczyc, K., Pirolli, P., Brown, A.L.: Training in Self-Explanation and Self- Regulation Strategies: Investigating the Effects of Knowledge Acquisition Activities on Problem-Solving. Cognition and Instruction 13(2), 221–252 (1995)
Bunt, A., Conati, C.: Probabilistic Student Modelling to Improve Exploratory Behaviour. Journal of User Modeling and User-Adapted Interaction 13(3), 269–309 (2003)
Bunt, A., Conati, C., Huggett, M., Muldner, K.: On Improving the Effectiveness of Open Learning Environments through Tailored Support for Exploration. In: AIED 2001, 10th World Conference of Artificial Intelligence and Education, San Antonio, TX (2001)
Chi, M.T.H.: Self-Explaining Expository Texts: The Dual Processes of Generating Inferences and Repairing Mental Models. In: Advances in Instructional Psychology, pp. 161–237 (2000)
Chi, M.T.H., Bassok, M., Lewis, M., Reimann, P., Glaser, R.: Self-Explanations: How Students Study and Use Examples in Learning to Solve Problems. Cognitive Science, 1989 15, 145–182 (1989)
Conati, C., Larkin, J., Van Lehn, K.: A Computer Framework to Support Self- Explanation. In: Proceedings of the Eighth World Conference of Artificial Intelligence in Education (1997)
Conati, C., VanLehn, K.: Toward Computer-based Support of Meta-cognitive Skills: A Computational Framework to Coach Self-Explanation. International Journal of Artificial Intelligence in Education 11 (2000)
Conati, C., VanLehn, K.: Providing Adaptive Support to the Understanding of Instructional Material. In: IUI 2001, International Conference on Intelligent User Interfaces, Santa Fe, NM, USA (2001)
Mitrovic, A.: Supporting Self-Explanation in a Data Normalization Tutor. In: Supplementary proceedings, AIED 2003 (2003)
Shute, V.J., Glaser, R.: A Large-Scale Evaluation of an Intelligent Discovery World. Interactive Learning Environments 1, 51–76 (1990)
van Joolingen, W.R., de Jong, T.: Supporting Hypothesis Generation by Learners Exploring an Interactive Computer Simulation. Instructional Science 20, 389–404 (1991)
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Bunt, A., Conati, C., Muldner, K. (2004). Scaffolding Self-Explanation to Improve Learning in Exploratory Learning Environments.. In: Lester, J.C., Vicari, R.M., Paraguaçu, F. (eds) Intelligent Tutoring Systems. ITS 2004. Lecture Notes in Computer Science, vol 3220. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30139-4_62
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DOI: https://doi.org/10.1007/978-3-540-30139-4_62
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22948-3
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