This paper argues that an important design principle for building expert systems is to represent all control knowledge abstractly and separately from the domain knowledge upon which it operates. Abstract control knowledge is defined as the specifications of when and how a program is to carry out its operations, such as pursuing a goal, focusing, acquiring data, and making inferences; domain knowledge is defined as the facts and relations of a knowledge base, such as a knowledge base of medical information. It is noted that a body of abstract control knowledge provides a generic framework for constructing knowledge bases for related problems in other domains, and also provides a useful starting point for studying the nature of strategies. The idea of separating control and domain knowledge is illustrated by discussing knowledge representation on three intelligent computer-aided diagnostic consultation systems, MYCIN, NEOMYCIN, and CENTAUR. The scientific, engineering, and practical benefits of separating control and domain knowledge are outlined and the difficulty of attaining this ideal design is considered. Also provided are a 19-item bibliography and a list of names and addresses of government and private sector research/information centers and personnel concerned with computer-aided instruction. (ESR)