LEARNING STRATEGIES AND TEACHING STRATEGIES.
Final scientific rept. 1 Sep 66-30 Nov 68,
SYSTEM RESEARCH LTD RICHMOND (ENGLAND)
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Results are reported of human learning experiments and computer simulations. Experiments focused on a how a subject directs his attention and explores the problem environment created by the task to be learned, and b how the subjects learning process can be facilitated by conversational, or partially cooperative, teaching systems, in practice, CAI systems. In all experiments, the subject interacted with an automaton responsible for controlling the experimental environment. Under some conditions, the automaton was a procedural device and imposed behavioral constraints that represented rules of the task but permitted the subject freedom, particularly in his choice of a strategy. Under other conditions, the automaton was a simple adaptive teaching machine or a conversational machine. The simulation incorporated subprograms representing the subject and automaton respectively. The gross action of the metasystem is explained in terms of the theory of self-organizing systems. Different subjects exhibited different strategies for learning the same skill the strategies may or may not be able to be fitted to aspects of mental organization of which the subject is often imperfectly aware. Results show that an adaptive metasystem is a better instructional instrument for the skill studied than either the attention-directing process in a free learning subject or a more restricted, single-strategy teaching system. The computer simulation of the learning process in the subject is a psychologically oriented artificial intelligence program, not a stochastic model. It is heterarchic in that its structure involves several separable but interacting hierarchic systems. Author