Task-Action Grammars: A Model of the Mental Representation of Task Languages

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Abstract
A formal model of the mental representation of task languages is presented. The model is a metalanguage for defining task-action grammars (TAG): generative grammars that rewrite simple tasks into action specifications. Important features of the model are (a) Identification of the "simple-tasks" that users can perform routinely and that require no control structure; (b) Representation of simple-tasks by collections of semantic components reflecting a categorization of the task world; (c) Marking of tokens in rewrite rules with the semantic features of the task world to supply selection restrictions on the rewriting of simple-tasks into action specifications. This device allows the representation of family resemblances between individual task-action mappings. Simple complexity metrics over task-action grammars make predictions about the relative learnability of different task language designs. Some empirical support for these predictions is derived from the existing empirical literature on command language ...

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