Abstract
Open learning environments often involve simulation where learners can experiment with different aspects and parameters of a given phenomenon to observe the effects of these changes. These are desirable in virtual laboratories. However, an important limitation of open learning environments is the effectiveness for learning, because it strongly depends on the learner ability to explore adequately. We have developed a semi-open learning environment for a virtual robotics laboratory based on simulation, to learn through free exploration, but with specific performance criteria that guide the learning process. We proposed a generic architecture for this environment, in which the key element is an intelligent tutoring system coupled to a virtual laboratory. The tutor module combines the performance and exploration behaviour of a student in several experiments, to decide the best way to guide his/her. We present an evaluation with an initial group of 20 students. The results show how this semi-open leraning environment can help to accelerate and improve the learning process.
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
Bunt, A., Conati, C.: Probabilistic StudentModelling to Improve Exploratory Behaviour. Journal of User Modeling and User-Adapted Interaction 13(3), 269–309 (2003)
Friedman, N., Getoor, L., Koller, D.: Learning Probabilistic Relational Models. In: Proceedings of the 16th International Joint Conference on Artificial Intelligence (IJCAI), Stockholm, Sweden, pp. 1300–1307 (1999)
Noguez, J., Sucar, L.E., Ramos, F.: A probabilistic relational model for virtual laboratories. In: Hoppe, U., Verdejo, F., Kay, J. (eds.) International Conference on Artificial Intelligence in Education, Sydney Australia, vol. 11, pp. 533–534. IOS Press, Amsterdam (2003)
Noguez, J., Sucar, L.E.: A Probabilistic Relational Student Model for Virtual Laboratories. In: To be published in Encuentro Internacional de Ciencias de la Computación. 26-30 de septiembre. Puebla, México (2005)
Pearl, J.: Probabilistic Reasoning in Intelligent Systems. Morgan Kaufmann, San Mateo (1988)
Richard, L., Gourderes, G.: An agent-Operated Simulation-Base Training System –Presentation of the CMOS Project. In: A. I., In S.P. Lajoie and M. Vivet. Artificial Intelligence in Education, pp. 343–351. IO Press (1999)
Russel, S., Norvig, G.: Artificial Intelligence, pp. 513–519. Prentice-Hall, Englewood Cliffs (1996)
Self, J.: The Role of Student Models in Learning Environments. Lancaster University, Technical Report No. 194 (1994)
Shute, V., Glaser, R.: A Large Scale Evaluation of an Intelligent Discovery World. Smithtown. Interactive Learning Environments 1, 55–77 (1990)
Sucar, L.E., Noguez, J.: Project oriented learning for basic robotics using virtual laboratories and intelligent tutors. In: To be published in 35th ASEE/IEEE Frontiers in Education Conference, Indianapolis, IN, USA, October 19-22 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Noguez, J., Sucar, L.E. (2005). A Semi-open Learning Environment for Virtual Laboratories. In: Gelbukh, A., de Albornoz, Á., Terashima-Marín, H. (eds) MICAI 2005: Advances in Artificial Intelligence. MICAI 2005. Lecture Notes in Computer Science(), vol 3789. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11579427_120
Download citation
DOI: https://doi.org/10.1007/11579427_120
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29896-0
Online ISBN: 978-3-540-31653-4
eBook Packages: Computer ScienceComputer Science (R0)