Abstract
Intelligent tutoring systems provide customized instruction or feedback to learners, without intervention from a human teacher. This feature causes that intelligent tutoring systems attract attention because they allow learning everywhere, every time and the cost of courses is cheaper than traditional in-class learning. In this work we propose a formal framework for building intelligent tutoring systems. The particular elements of those systems such as: learner profile, domain model, methods for determination and modification of a learning scenario and for computer adaptive tests are presented. Additionally, we describe an application of rough classification in e-learning systems. The conducted experiments and analysis demonstrate that the personalization has a significant influence on a learning process and the probability of passing all lessons from the learning scenario is greater if the opening learning scenario is selected using a worked-out methods than chosen in a random way. The obtained results proof the correctness of our assumptions and have significant implications for development of intelligent tutoring systems.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Brusilovsky, P., Schwarz, E., Weber, G.: ELM-ART: An intelligent tutoring system on World Wide Web. In: Lesgold, A.M., Frasson, C., Gauthier, G. (eds.) ITS 1996. LNCS, vol. 1086, pp. 261–269. Springer, Heidelberg (1996)
Gamboa, H., Fred, A.: Designing intelligent tutoring systems: A Bayesian approach. In: Proceedings of ICEIS 2001, Setubal, Portugal, July 7–10 (2001)
Jeremic, Z., Jovanovic, J., Gasevic, D.: Evaluating an intelligent tutoring system for design patterns: The DEPTHS experience. Journal of Educational Technology & Society 12(2), 111–130 (2009)
Kelly, D., Tangney, B.: Incorporating learning characteristics into an intelligent tutor. In: Cerri, S.A., Gouardéres, G., Paraguaçu, F. (eds.) ITS 2002. LNCS, vol. 2363, pp. 729–739. Springer, Heidelberg (2002)
Kelly, D., Tangney, B.: Predicting learning characteristics in a multiple intelligence based tutoring system. In: Lester, J.C., Vicari, R.M., Paraguaçu, F. (eds.) ITS 2004. LNCS, vol. 3220, pp. 678–688. Springer, Heidelberg (2004)
Kozierkiewicz, A.: Determination of opening learning scenarios in intelligent tutoring systems. In: Siemiński, A., Zgrzywa, A., Choroś, K. (eds.) New trend in Multimedia and Network Information Systems. IOS Press, Amsterdam (2008)
Kozierkiewicz-Hetmańska, A.: A conception for modification of learning scenario in an intelligent E-learning system. In: Nguyen, N.T., Kowalczyk, R., Chen, S.-M. (eds.) ICCCI 2009. LNCS (LNAI), vol. 5796, pp. 87–96. Springer, Heidelberg (2009)
Kozierkiewicz-Hetmańska, A., Nguyen, N.T.: A computer adaptive testing method for intelligent tutoring systems. In: Setchi, R., Jordanov, I., Howlett, R.J., Jain, L.C. (eds.) KES 2010, Part I. LNCS, vol. 6276, pp. 281–289. Springer, Heidelberg (2010)
Kozierkiewicz-Hetmańska, A., Nguyen, N.T.: A method for scenario modification in intelligent E-learning systems using graph-based structure of knowledge. In: Nguyen, N.T., Katarzyniak, R., Chen, S.-M. (eds.) Advances in Intelligent Information and Database Systems. SCI, vol. 283, pp. 169–179. Springer, Heidelberg (2010)
Kozierkiewicz-Hetmanska, A., Nguyen, N.T.: A method for learning scenario determination and modification in intelligent tutoring system. International Journal Applied of Mathematics and Computer Science 21(1) (2011)
Kozierkiewicz-Hetmanska, A.: A Method for Scenario Recommendation in Intelligent E- learning System. Cybernetics and Systems 42, 82–99 (2011)
Kozierkiewicz-Hetmanska, A.: Evaluation of an intelligent tutoring system incorporating learning profile to determine learning scenario. In: Jezic, G., Kusek, M., Nguyen, N.-T., Howlett, R.J., Jain, L.C. (eds.) KES-AMSTA 2012. LNCS, vol. 7327, pp. 44–53. Springer, Heidelberg (2012)
Kozierkiewicz-Hetmańska, A.: Evaluating the effectiveness of intelligent tutoring system offering personalized learning scenario. In: Pan, J.-S., Chen, S.-M., Nguyen, N.T. (eds.) ACIIDS 2012, Part I. LNCS, vol. 7196, pp. 310–319. Springer, Heidelberg (2012)
Kukla, E.E., Nguyen, N.T., Danilowicz, C., Sobecki, J., Lenar, M.: A model conception for optimal scenario determination in an intelligent learning system. ITSE—International Journal of Interactive Technology and Smart Education 1(3), 171–184 (2004)
Kwasnicka, H., Szul, D., Markowska-Kaczmar, U., Myszkowski, P.: Learning Assistant – Personalizing learning paths in elearning environments. In: 7th Computer Information Systems and Industrial Management Applications. IEEE (2008)
Nguyen, N.T.: A Method for Ontology Conflict Resolution and Integration on Relation Level. Cybernetics and Systems 38(8), 781–797 (2007)
Nguyen, N.T.: Advanced Methods for Inconsistent Knowledge Management. Springer, London (2008)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer International Publishing Switzerland
About this paper
Cite this paper
Kozierkiewicz-Hetmańska, A., Nguyen, N.T. (2013). A Framework for Building Intelligent Tutoring Systems. In: Nguyen, N., van Do, T., le Thi, H. (eds) Advanced Computational Methods for Knowledge Engineering. Studies in Computational Intelligence, vol 479. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00293-4_19
Download citation
DOI: https://doi.org/10.1007/978-3-319-00293-4_19
Publisher Name: Springer, Heidelberg
Print ISBN: 978-3-319-00292-7
Online ISBN: 978-3-319-00293-4
eBook Packages: EngineeringEngineering (R0)