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This paper presents the analytic hierarchy process (AHP) as a methodology for developing ratio scales from paired comparison data. The AHP offers several advantages over traditional psychophysical approaches for generating measurement scales. One advantage is its ability to readily quantify consistency in human judgments. Another is the ability of the AHP to provide useful empirical results in the event of a small sample of subjects and when the likelihood of obtaining meaningful statistical results may be restricted. Finally, the methodology requires no statistical assumptions regarding the distribution of human judgments. This paper demonstrates that the AHP can be applied to types of subjective data frequently acquired during human factors experimentation. In an empirical scenario, subjects performed paired comparison judgments on a set of five computer interfaces designed for an automated part recognition system. The objective was to rank these interfaces on the basis of users' perceptions regarding two interface characteristics: usability and learnability. Results of the analysis provide ratio scales for evaluating both interface usability and learnability.

A methodology for quantifying expert system usability is presented. Usability is considered from a designer's perspective: the designer must ultimately address any design Issues that may affect usability. A linear multivariate function for measuring usability is described. The function's independent variables represent user perceptions and performance. In an example a function of this form is developed and used to assign a usability score to a given expert system. The usefulness of the usability function as a design tool is also investigated.

Software developers are frequently required to evaluate the usability of produces they design. Limited resources often prevent them from performing a complete interface evaluation prior to product release. In these instances a relatively standard approach is to identify a few functionalities on which to focus evaluation efforts. This paper proposes a three-phased methodology for selecting this "short list" of functionalities. In Phase 1 a functional-level goals, operator., methods, selection rules (GOMS) model representing required user-system interaction tasks is developed. In Phase 2 functionalities are identified, which serve as candidates for evaluation. Task descriptions developed during the initial phase facilitate completion of Phase 2. In Phase 3 the functionality short list is derived. The methodology is applied to the Information Engineering FacilityTM, a computer-aided software engineering tool developed by Texas Instruments. Implications of implementing the methodology are discussed.