A measure of indexing consistency is developed based on the concept of "fuzzy sets." It assigns a higher consistency value if indexers agree on the more important terms than if they agree on less important terms. Measuresof the quality of an indexer's work and exhaustivity of indexing are also proposed. Experimental data on indexing consistency is presented for certain categories of indexers; and consistency, quality, and exhaustivity values are compared and analyzed. The analysis of indexing exhaustivity leads to the conclusion that the increase of information as a result of group indexing is a process analogous to Bradford's law of information scattering, Lotka's law of scientific productivity, and Zipf's law of vocabulary distribution.

It is generally accepted that a course in discrete structures such as Course B3 in Curriculum 68 recommendations [1] is an important part of a Computer Science program. In many institutions a Discrete Structures course is offered in the Computer Science Department although it overlaps courses in the Mathematics Department [2,3,4]. In smaller schools the size of the student body and staff limitations make such a solution impractical. At Augusta College we have met the objective of early exposure to discrete mathematics with applications in computer science by offering a two-hour computer science course as a co-requisite to a three-hour mathematics course. While this approach is a compromise it does appear to have some merit.

No abstract