An intelligent human-computer interface for provision of on-line help

Some user interfaces, such as that of Unix(1) are difficult fur novices to use, and this paper suggests a possible solution to such problems. The resu lts of a study of Unix users enabled the development of a taxonomy of error types so that users' errors can be classified. This information is encapsu lated as production rules within a knowledge base and forms the basis for t he design and development of an intelligent interface to Unix. The prototyp e makes inferences about users' mental models and uses these to select appr opriate tutorial advice. Performance of users of the prototype intelligent interface was compared with that of users of the usual Unix interface. The prototype users were found to make fewer errors, exhibit fewer misconceptio ns and take less time to complete a standard set of tasks.