Abstract
This paper describes the implementation and evaluation of a new system to guide exploratory learning in arbitrary task-based domains. The system employs a knowledge representation borrowed from the field of automated planning to represent both the exploratory environment and the student’s model of the tasks in the environment.
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
Fikes, R., Nilsson, N.: STRIPS: A new approach to the application of theorem proving to problem solving. Artificial Intellligence 2(3/4) (1971)
de Jong, T., van Joolingen, W.: Scientific discovery learning with computer simulations of conceptual domains. Review of Educational Research 68(2), 179–201 (1998)
Kirschner, P., Sweller, J., Clark, R.: Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist 41(2), 75–86 (2006)
Mayer, R.: Should there be a three-strikes rule against pure discovery learning. American Psychologist 59(1), 14–19 (2004)
Puntambekar, S., Hubscher, R.: Tools for Scaffolding Students in a Complex Learning Environment: What Have We Gained and What Have We Missed? Educational Psychologist 40(1), 1–12 (2005)
Quintana, C., Reiser, B., Davis, E., Krajcik, J., Fretz, E., Duncan, R., Kyza, E., Edelson, D., Soloway, E.: A Scaffolding Design Framework for Software to Support Science Inquiry. The Journal of the Learning Sciences 13(3), 337–386 (2004)
Rickel, J., Johnson, W.: Animated agents for procedural training in virtual reality: Perception, cognition, and motor control. Applied Artificial Intelligence 13(4-5), 343–382 (1999)
Rowe, J., Mott, B., McQuiggan, S., Robison, J., Leed, S., Lester, J.: Crystal Island: A Narrative-Centered Learning Environment for Eighth Grade Microbiology. In: 14th International Conference on AI in Education Workshops Proceedings, p. 11 (2009)
Swartout, W., Hill, R., Gratch, J., Johnson, W., Kyriakakis, C., LaBore, C., Lindheim, R., Marsella, S., Miraglia, D., Moore, B., et al.: Toward the Holodeck: Integrating Graphics, Sound, Character and Story. Defense Technical Information Center (2006)
Thomas, J.M., Young, R.M.: Annie: Automated generation of adaptive learner guidance for fun serious games. IEEE Transactions on Learning Technologies 3, 329–343 (2010)
Thomas, J., Young, R.: Using Task-Based Modeling to Generate Scaffolding in Narrative-Guided Exploratory Learning Environments. In: Proceedings of the 14th International Conference on Artificial Intelligence in Education (2009)
Van Joolingen, W., De Jong, T., Dimitrakopoulou, A.: Issues in computer supported inquiry learning in science. Journal of Computer Assisted Learning 23(2), 111–119 (2007)
VanLehn, K.: The Behavior of Tutoring Systems. International Journal of Artificial Intelligence in Education 16(3), 227–265 (2006)
Young, R., Pollack, M., Moore, J.: Decomposition and causality in partial-order planning. In: Proceedings of the Second International Conference on AI and Planning Systems, vol. 48 (1994)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Thomas, J.M., Young, R.M. (2011). Dynamic Guidance for Task-Based Exploratory Learning. 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_48
Download citation
DOI: https://doi.org/10.1007/978-3-642-21869-9_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21868-2
Online ISBN: 978-3-642-21869-9
eBook Packages: Computer ScienceComputer Science (R0)