Felicity Conditions for Human Skill Acquisition: Validating an AI (Artificial Intelligence)-Based Theory.
XEROX PALO ALTO RESEARCH CENTER CA COGNITIVE AND INSTRUCTIONAL SCIENCES GROUP
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A theory of how people learn certain procedural skills is presented. It is based on the idea that the teaching and learning that goes on in a classroom is like an ordinary conversation. The speaker teacher compresses a non-linear knowledge structure the target procedure into a linear sequence of utterances lessons. The listener student constructs a knowledge structure the learned procedure from the utterance sequence lesson sequence. In recent years, linguists have discovered that speakers unknowingly obey certain constraints on the sequential form of their utterances. Apparently, these tacit conventions, called felicity conditions or conversational postulates, help listeners construct an appropriate knowledge structure from the utterance sequence. The analogy between conversations and classrooms suggests that there might be felicity conditions on lesson sequences that help students learn procedures. This research has shown that there are. For the particular kind of skill acquisition studied here, three felicity conditions were discovered. They are the central hypotheses in the learning theory. The theory has been embedded in a model, a large computer program that uses artificial intelligence AI techniques. The models performance has been compared to data from several thousand students learning ordinary mathematical procedures subtracting multidigit numbers, adding fractions and solving simple algebraic equations. A key criterion for the theory is that the set of procedures that the model learns should exactly match the set of procedure that students actually acquire, including their buggy procedures. Author