Abstract
A cardinal aim of computer-assisted learning should be to devise methods which optimize its techniques of instruction, and these require a precise representation of tasks. and learners, a set of teaching operations and means-ends guidance rules. An analysis of diagnostic tasks analogous to those carried out in medicine, points to ways in which computer programs can generate tasks to fit a particular learner's competence. Such methods can also give adaptive help in teaching, but there is a need for much experiment before satisfactory means-ends guidance rules can be formulated. For this purpose a computer-controlled diagnostic game was developed in which students attempted to classify patterns of symbols which represented sets of “attribute states” of various “diseases”. The characteristics of this game, and some analyses of student performances and some measures of task difficulty are described. Preliminary results of having the computer match student performances to its own diagnostic strategies are also outlined, and the development of these to control adaptive teaching is discussed.
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