Abstract
Nowadays, it has been an important issue to adaptively recommend learning strategies for every learner in intelligent tutoring systems (ITS) that covers various areas and subjects. In this paper, three models for learners, learning strategies and learning strategy-oriented services are proposed. The C4.5 decision tree algorithm is adopted to construct a learning strategy tree which contain popular learning strategies used in ITS. Based on those models and the learning strategy decision tree, a learning strategy recommendation agent is proposed in our learning strategy recommendation system (BIT-LSS) to adaptively recommend learning strategies for learners. Questionnaire surveys and experiments are conducted to demonstrate the efficiency of the learning strategy recommendation agent in BIT-LSS.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Ma, J., Shaw, E., Kim, J.: Computational Workflows for Assessing Student Learning. In: Aleven, V., Kay, J., Mostow, J. (eds.) ITS 2010. LNCS, vol. 6095, pp. 188–197. Springer, Heidelberg (2010)
Chi, M.T.H., Roy, M.: How Adaptive Is an Expert Human Tutor? In: Aleven, V., Kay, J., Mostow, J. (eds.) ITS 2010, Part II. LNCS, vol. 6094, pp. 401–412. Springer, Heidelberg (2010)
Selçuk, G.S., Çalişkan, S., Erol, M.: Learning Strategies of Physics Teacher Candidates: Relationships with Physics Achievement and Class Level. In: Sixth International Conference of the Balkan Physical Union, pp. 511–512 (2007)
Glória Curilem, S., de Azevedo, F.M., Barbosa, A.R.: Adaptive Interface Methodology for Intelligent Tutoring Systems. In: Lester, J.C., Vicari, R.M., Paraguaçu, F. (eds.) ITS 2004. LNCS, vol. 3220, pp. 741–750. Springer, Heidelberg (2004)
Linton, F.: Learning to Learn from an ITS. In: du Boulay, B., Mizoguchi, R. (eds.) Artificial Intelligence in Education. IOS Press, Amsterdam (1997)
Bull, S.: Individualized Recommendations for Learning Strategy Use. In: Gauthier, G., VanLehn, K., Frasson, C. (eds.) ITS 2000. LNCS, vol. 1839, pp. 594–603. Springer, Heidelberg (2000)
Lulis, E., Evens, M.W., Michael, J.A.: Implementing Analogies in an Electronic Tutoring System. In: Lester, J.C., Vicari, R.M., Paraguaçu, F. (eds.) ITS 2004. LNCS, vol. 3220, pp. 751–761. Springer, Heidelberg (2004)
Hashemi, M.: The Impact of Gender on Language Learning Strategies of Iranian Learners. International Journal of Academic Research, Part I, 280–285 (2011)
Arroyo, I., Woolf, B.P., Royer, J.M., Tai, M., English, S.: Improving Math Learning through Intelligent Tutoring and Basic Skills Training. In: Aleven, V., Kay, J., Mostow, J. (eds.) ITS 2010. LNCS, vol. 6094, pp. 423–432. Springer, Heidelberg (2010)
Rubin, J.: What the ’Good Language Learner’ Can Teach Us. TESOL Quarterly 9(1) (1975)
Zhang, W.S.: Research on Learning Strategy-Oriented Service model in E-Learning. Beijing Institute of Technology (2012)
Scarcella, R., Oxford, R.: The Tapestry of Language Learning: The Individual in the Communicative Classroom, p. 63. Heinle & Heinle, Boston (1992)
Oxford, R.L.: Language Learning Styles and Strategies: an Overview. In: GALA 2003, pp. 1–25 (2003)
Hu, J.L., Deng, J.B., Sui, M.X.: A new approach for decision tree based on principal component analysis. In: 2009 International Conference on Computational Intelligence and Software Engineering, pp. 1–4 (2009)
Quinlan, J.R.: C4.5: Programs for machine learning. Morgan Kauffman publishers (1993)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Niu, Z., Gu, P., Zhang, W., Chen, W. (2012). Learning Strategy Recommendation Agent. In: Uden, L., Corchado RodrÃguez, E., De Paz Santana, J., De la Prieta, F. (eds) Workshop on Learning Technology for Education in Cloud (LTEC'12). Advances in Intelligent Systems and Computing, vol 173. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30859-8_19
Download citation
DOI: https://doi.org/10.1007/978-3-642-30859-8_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-30858-1
Online ISBN: 978-3-642-30859-8
eBook Packages: EngineeringEngineering (R0)