Teaching and Learning ``meet'' in the teaching and learning environment. Building a good learning environment means taking into account both the psychologist's and the instructionalist's perspectives.

Advanced Research on Learning Environments (mostly in the field of artificial intelligence and education, see [Wenger, 1987]) can give us some insights on how to build a good learning and teaching environment. An Advanced Learning Environment 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 course-ware 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. Learning is also increased when two or more learners work together on a problem. This assistance or co-learner function may be provided by humans or by some system components. In our flight simulator example, the future pilot would gain from discussing his actions with an experienced pilot. In advanced experimental learning environments, 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, (2) a reflective architecture that shows the students what he is doing or even helps him to actively structure his cognitive activities, (3) one or more agents that assist the learner in his task and monitor his learning and maybe (4) a co-learner.

Advanced Learning environments are difficult to implement and currently they are not cost effective. However, ideas from this type of research have to be taken seriously and a very important lesson is that new media should be used in a creative way. There is not much point in investing time and money into computer technology that replicates what can be done as well with traditional means. Now lets look at a few postulates that can be found in such research:

• The Learner must be active (again and always: people don't learn by browsing hypertext and by answering questions!)
• A learning environment should be designed to be as powerful as dedicated working environments. It must be rich and complex reflecting the essential properties of what has to be learned.
• The environment must be structured. If the richness of a learning environment is a quality, its complexity may reduce learning. It must provide optimal learning conditions as a function of the learner's stage of knowledge.
• Learning environments should be designed as hierarchical knowledge base generators
• Learning environments should present knowledge as a communication system. A learner must interact with agents, tutors.

Of course, such an environment is difficult to implement on the computer and even more over the network. But educational setups can be constructed with those principles in mind! Now let's have a more ``distant'' look at the concept of ``learning environment''.

In discussing the role of technological support in education, [Sandberg, 1994, 225,] identifies the components of a (technologically rich) learning environment. These components must all be there in order to optimize learning. However, they can be ``implemented'' in many different ways. Each component has functionalities that we should insure:

1. ``Teacher'' component: Its role is to provide something between loose guidance and direct instruction. It can be a human agent (present or distant), an intelligent agent, instructions like some text books provide, etc. This component provides information from the syllabus to the task level.
2. ``Monitor component: Ensures that something is learned. A role taken by either the human teacher, the learner (self-control) or by some program.
3. ``Fellow learners'' component: Improves the learning process (some research tries to implement artificial ones).
4. ``Learning material'': Contains what has to be learned in a very broad sense (knowing what, knowing how). It can be computational in various ways (exploratory hypertext, lesson and task oriented hypertext, simulation software, task solving environments, etc.).
5. ``External information sources'': All kinds of information which is not directly stored in the learning material (e.g. additional material, handbooks, manuals, etc.).
6. ``Tools'': Everything which may help the learning process other then the learning material (e.g. calculators, communication software, etc.)
7. ``School'' [a category we added]: Something that provides a curriculum.