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The Knowledge Associates for Novel Intelligence (KANI) project is developing a system of automated “associates” to actively support and participate in the information analysis task. The primary goal of KANI is to use automatically extracted information in a reasoning system that draws on the strengths of both a human analyst and automated reasoning. The interface between the two agents is a key element in achieving this goal. The KANI interface seeks to support a visual dialogue with mixed-initiative manipulation of information and reasoning components. The interface must achieve mutual understanding between the analyst and KANI of the other's actions. Toward this mutual understanding, KANI allows the analyst to work at multiple levels of abstraction over the reasoning process, links the information presented across these levels to make use of interaction context, and provides querying facilities to allow exploration and explanation.

We propose a method (APHID) that assists an instructional designer to define format, structure and sequence within an instructional hypermedia application. Our method uses concept maps and instructional patterns, as well as data, navigation, and presentation models to support partial automation for creating instructional hypermedia.

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