The minicomputer-based Computerized Diagnostic and Decision Training (CDDT) system described combines the principles of artificial intelligence, decision theory, and adaptive computer assisted instruction for training in electronic troubleshooting. The system incorporates an adaptive computer program which learns the student's diagnostic and decision value structure using a trainable network technique of pattern classification, compares this structure to that of an expert, and adapts the instructional sequence to eliminate discrepancies through the use of heuristic algorithms. An expected value model of decision making is the basis of the student and instructor models which, with the task simulator and adaptive instructions, form the core of the CDDT system. The instructor model also generates suggested actions in response to student requests for assistance. The student's task is to troubleshoot a complex circuit by making test measurements, replace the malfunctioning part, and make verification measurements. The student values of interest are those for information gained through the measurements, and for the replacement of circuit modules. Appendices describe the Dynamic Utility Adjustment, decisions in troubleshooting, and the student training sequence; a student handout with circuit diagrams describing the system is also included. (Author/CMV)