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. Experience with learning environments (like LOGO) showed that those systems gain efficiency if the learner is not left on his own but receives some assistance. This assistance may be provided by a human tutor or by some system components. In our flight simulator example, the future pilot would gain from discussing his actions with an experienced pilot. The implementation of these agents is based on artificial intelligence techniques.
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.
This research project had two main purposes:
- to develop a particular learning environment that illustrates the application of artificial intelligence techniques to intelligent learning environments;
- to develop tools for building similar learning environments, intended to be used by other research teams.
Two software packages have been implemented to reach these goals:
- MEMOLAB is a particular learning environment for the acquisition of basic methodological skills in experimental psychology.
- ETOILE (Experimental Toolbox for Interactive Learning Environments) is a toolbox that enables advanced programmers to build an ILE in another domain, but based on the same principles and architecture as MEMOLAB.
These two systems are described in this report.