Demonstration of a Methodology for Classifying Naval Training Courses.

摘要

Navy enlisted technical training courses (numbering in the thousands) are grouped into two broad categories--'A' and 'C' courses. The apparent basis for these categories lies in the purpose for which the courses are conducted: 'A' courses typically are designed to teach occupationally oriented, entry level skills and knowledge to first-term enlistees; 'C' courses are designed to teach advanced or system-specific knowledge and skills. The courses within each category vary on many dimensions, e.g., length, cost, kinds of skills trained, annual input of trainees. This study examines ways of determining homogeneous subgroups of courses within the 'A' and 'C' distinction. Groups of courses that are homogeneous in terms of a common set of variables permit more specific generalizations or inferences to be made about them. A method is demonstrated for finding homogeneous groups of courses within the broader categories. A computer based clustering algorithm was employed on data from a sample of over 400 Navy enlisted technical training 'A' and 'C' courses. The clustering program demonstrated its utility by sorting technical training courses into several groups on the basis of 'common' course characteristics. Several possible applications and benefits of the clustering methodology are discussed.