Who would you rather have decide what's wrong with your sick child? A first-time doctor who had passed a written test about disease treatment, or a first-time doctor who had done several hundred similar realistic diagnoses in a ``diagnosis simulator?''
One can see intuitively that for many domains, students should be working in environments where students are performing the same tasks as they would have if they were experts instead of students. This approach to learning environments, called authentic environments, has been suggested in literature as early as the start of the 20th century [Farnham-Diggory 1992].
Naturally, throwing students into authentic environments without any
help wouldn't necessarily be a good learning
experience--for example, one needs to have access to information
about medicine when learning how to be a doctor. Students need
frequent help, such as asking questions to experts (a sort of apprenticeship arrangement [Collins, Brown, and Newman 1989]). They also need
tasks where they will encounter new and interesting problems. In our
diagnosis simulator, one would like students to run into a large
number of different cases, so that any real-life diagnosis they
have to do is likely to be just like a diagnosis they have done in
simulation [Kolodner and Jona 1991].
Computers have the potential to be platforms for this kind of learning environment. Computers are reactive, infinitely patient, provide fast access to knowledge, and can (with hard work by the designer) bring joy and interest to a student.
One kind of software that fits the description above is called a ``Goal Based Scenario'' (GBS) [Schank et al. 1993]. In a GBS, students are put in the role of someone who has a task that they need to accomplish and an authentic simulated environment in which to work. Students have access to experts at every step of their work. Our ``diagnosis simulator'' is a kind of GBS--students are put in the role of a real doc