Policy Capturing and Fuzzy Logic: A Better Approach to Representing Judgment Data?

Abstract

At the 45^th annual meeting of HFES, we conducted an alternative format session in which fuzzy logic was introduced as an alternative approach to analyzing judgment data and representing decision-making policies (see Buff et al., 2001). During the alternative format session, usability judgments were collected on-site for Advanced Distance Learning (ADL) applications. These data provided the basis for an empirical assessment of the value added of one modeling technique, fuzzy logic, over the more traditional approach to analyzing policy capturing data, multiple linear regression. This paper describes the results of an empirical assessment of the two modeling techniques. For a discussion of the empirical results of the impact of the different usability dimensions on the learning effectiveness of ADL applications, see Holness, Pharmer, and Buff (2002).