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A framework model for the design and implementation of computer assisted learning (CAL) programs is described. The model is flexible enough to accept most domains and can deliver knowledge in a simulated form, similar to that of a teacher in a classroom. A major feature of the model is its division into four submodels: the knowledge base, the dialogue, the plan, and the task specification. The knowledge base has been considered as two classes of knowledge: structural and functional. The construction of the dialogue submodel as a tree structure co‐ordinates domain specific reasoning with the plan submodel which generates a wide range of possible formats for user response.

Describes a method of construction and representation of scientific knowledge, as a hierarchical information structure, using the propositional form of semanti‐net formulism. The method can be used for developing knowledge‐based systems and, in particular, Computer‐Assisted Learning (CAL) programs. The method is theoretically based on issues taken from both psychology and computer sciences, and particularly the cognitive aspects of memory organization and the conversation and comprehension processes. Scientific knowledge is regarded as being made up of three types of information: definitions, methods and procedures. Each type consists of information represented by separate and meaningful properties, together with their relationships and the processes that may occur in using this information during comprehension and conversation.