Methods of Approach At the outset it might be well to distinguish sharply between two general approaches to the problem of machine learning.

The editors have provided him with special introductory sections as a ing guide to a thorough understand of the reports.

Case-based reasoning is used extensively by people in A second driving force in the evolutionary history of CBR both expert and commonsense situations. It provides a was dissatisfaction with rule-based reasoning (expert systems wide range of advantages.

Empirical rule learning and analytic Most learning is based on experience, and this requires a learning methods have predominantly used the first path, representation for the experiential input given to the whereas connectionist systems have relied on the second.

Current research has succeeded in despite much work attempting to do so, human-- exploring a large number of domains and has explored machine communication is not yet sensitive to dialogue some nontraditional pedagogical strategies, such as partnering, context and to what is known or knowable about the student's mentoring, and scaffolding.

Paper presented at the IPN Symposium 7: Formalized Theories of Thinking and Learning and Their Implications for Science Instruction.

This chapter briefly outlines the difference between traditional instructional programs and ICAI. It then illustrates how GUIDON makes contributions in areas important to medical CAl: interacting with the student in a mixed-initiative dialogue (including the problems of feedback and realism), teaching problem-solving strategies, and assembling a computerbased curriculum. In evaluating GUIDON's performance, one can see the value in the basic idea of formalizing teaching knowledge in procedures that are separate from the knowledge to be taught. However, the program is inherently limited by the MYCIN knowledge base. The rule set is poorly structured, does not contain pathophysiological knowledge for justifying the diagnostic associations, and does not explicitly state the strategies for gathering information and focusing on hypotheses.

In this book we have presented experimental evidence at many levels of detail for a diverse set of hypotheses. As indicated by the chapter and section headings, the major themes of the MYCIN work have many variations. In this final chapter we will try to summarize the most important results of the work presented. This recapitulation of the lessons learned should not be taken as a substitute for details in the sections themselves. We provide here an abstraction of the details, but hope it also constitutes a useful set of lessons on which others can build. The three main sections of this chapter will reiterate the main goals that provide the context for the experimental work; discuss the experimental results from each of the major parts of the book; and summarize the key questions we have been asked, or have asked ourselves, about the lessons we have learned. If we were to try to summarize in one word why MYCIN works as well as it does, that word would be flexibility.

Effect of the Tutorial The tutorial experience had a small but significant effect on physicians' Demands and also produced a substantial increase in their knowledge about computing concepts. The results from the Demand-scale were of particular interest. Physicians apparently gained new insights from the tutorial into the potential use and capabilities of medical computing and increased their performance Demands accordingly. These opinions regarding the attributes of acceptable computing systems were surprisingly uniform across physician subgroups both before and after the tutorial. Our interpretation of this result is that physicians are serious about these Demands and that consultation systems are not likely to be clinically effective, regardless of the accuracy of their advice, until these capabilities have been incorporated.

Performance Level D-RULE578 IF: 1) The infection which requires therapy is meningitis, and 2) Organisms were not seen on the stain of the culture, and 3) The type of the infection is bacterial, and 4) The patient has been seriously burned THEN: There is suggestiv evidence (.5) that pseudomonas-aeruginosa is one of the organisms (other than those seen on cultures or smears) which might be causing the infection UPDATES: COVERFOR USES: (TREATINF ORGSEEN TYPE BURNED) Support Level MECHANISM-FRAME: BODY-INFRACTION.WOUNDS JUSTIFICATION: "For a very brief period of time after a severe burn the surface of the wound is sterile. Shortly thereafter, the area becomes colonized by a mixed flora in which gram-positive organisms predominate. By the 3rd post-burn day this bacterial population becomes dominated by gram-negative organisms. By the 5th day these organisms have invaded tissue well beneath the surface of the burn. The organisms most commonly isolated from burn patients are Pseudomonas, Klebsiella-Enterobacter, Staph., etc. Infection with Pseudomonas is frequently fatal." LITERATURE: MacMillan BG: Ecology of Bacteria Colonizing the Burned Patient Given Topical and System Gentamicin Therapy: a five-year study, J Infect Dis 124:278-286, 1971.