A strategy for developing automated assessment systems

Two basic issues underlying the design of automated assessment systems are discussed and the merits of formal as opposed to nonformal, and categorical as opposed to dimensional approaches are stressed. A two-stage strategy, designed to be of use to investigators in particular settings in developing automated assessment systems, is proposed. The first or classification stage is expected to yield viable sets of categories for different populations and is based on a classification algorithm developed by Carlson. The second or identification stage is expected to permit efficient identification of new cases as members of one of the categories obtained in the first stage. It is based on a sequential and Bayesian pattern recognition technique devised by Lasker.