The research work reported here concerns the application of Artificial Intelligence techniques to learning environments. A learning environment is a category of educational software where the learner's task is not to answer a predefined serie of questions but to explore a complex world with the assistance of computational agents. We implemented MEMOLAB as an instance of such a learning environment. In MEMOLAB, the learner creates a psychology experiment and then asks the system to simulate the results. Our work has concentrated on two directions:
Direction 1: Providing optimal learning conditions. Two main qualities of an environment are its richness and its structure. By `richness', we mean the integration of various tools, for instance the connection between a hypertext, procedural tools (e.g. the simulation) and rule-based agents. The `structure' of a learning environment results from its segmentation into a sequence of microworlds. This sequence should ideally reflect a sequence of learning stages (in MEMOLAB, the neo-Piagetian theory of R. Case).
Direction 2: Providing the assistance of agents. In MEMOLAB, the learner creates experiments in interaction with an expert, i.e. an agent who is able to solve the same problems through the same interface. The degree of assistance provided by the expert is tuned by another agent, the tutor, which monitors the interaction. MEMOLAB includes several tutors corresponding to various teaching styles. These tutors are selected by their superior, called `the coach'.
The distribution of roles between the agents has been conceived in such a way that some agents (the tutors and the coach) are not directly concerned by the specific teaching domain and hence can be reused to build other learning environments. The set of domain-independent components constitute ETOILE, an Experimental TOolbox for Interactive Learning Environments. Its originality is that authors do not build a software application by writing questions and feedback, but by designing domain-specific agents that will interact with the agents provided by the toolbox. ETOILE is intended to be used by developers who are familiar with Common Lisp.
TECFA (Technologies de Formation et Apprentissage)
Faculté de Psychologie et des Sciences de l'Education
University of Geneva (Switzerland)
Address: 9, Route de Drize, CH-1227 Carouge (Switzerland)
Contact: P. Dillenbourg
Phone: (+41) 22.705.96.93
E-mail: pdillen@divsun.unige.ch