Intelligent learning environment: Difference between revisions

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# one or more agents that assist the learner in his task and monitor his learning.}}
# one or more agents that assist the learner in his task and monitor his learning.}}


Wenger (1987) points out three types of knowledge crucial to intelligent tutoring within an ILE:  
Wenger (1987) points out three types of knowledge important to intelligent tutoring, and by extension also crucial to an effective ILE:  
* knowledge about domain
* knowledge about domain
* knowledge about tutoring
* knowledge about tutoring
* knowledge about the student and [Open learner model | student model]
* knowledge about the student and [[Open learner model | student model]]


See also [[intelligent tutoring system]]s, [[artificial intelligence and education]], [[adapative hypertext]], [[computer-supported collaborative learning]]
See also [[intelligent tutoring system]]s, [[artificial intelligence and education]], [[adapative hypertext]], [[computer-supported collaborative learning]]

Revision as of 10:37, 22 December 2006

Draft

Definition

Intelligent learning environments are based on various combinations of principles from microworlds, intelligent tutoring systems, cognitive tools and CSCL.

P.Dillenbourg et al. ([1]) offer this definition

The term `intelligent learning environment' (ILE) refers to a category of educational software in which the learner is `put' into a problem solving situation. A learning environment is quite different from traditional courseware based on a sequence of questions, answers and feedback. The best known example of a learning environment is a flight simulator: the learner does not answer questions about how to pilot an aircraft, he learns how to behave like a "real" pilot in a rich flying context...

In summary, we use the word `intelligent learning environment' for learning environments which include

  1. a problem solving situation and
  2. one or more agents that assist the learner in his task and monitor his learning.

Wenger (1987) points out three types of knowledge important to intelligent tutoring, and by extension also crucial to an effective ILE:

  • knowledge about domain
  • knowledge about tutoring
  • knowledge about the student and student model

See also intelligent tutoring systems, artificial intelligence and education, adapative hypertext, computer-supported collaborative learning

References

  • Dillenbourg. P., Hilario, M., Mendelsohn, B. Schneider, D., Borcic, B. Report from the project "Les systèmes explorateurs intelligents". Intelligent Learning Environments . FP23 Program; Project No. 4023-2701 [2]
  • Wenger, E. 1987. Artificial intelligence and tutoring systems. Computational approaches to the communication of knowledge. Los Altos: Morgan Kaufmann.