Categorical menu layouts are currently designed according to conventions and opinions, rather than by employing formal techniques. In this paper we describe a formal methodology for categorically organizing menus. We go on to show how color-coding can be applied to these layouts either to emphasize organization or to provide additional information. The results of a controlled study comparing layouts based on frequency of co-occurrence and similarity show that the formal menu-layout methodology is effective. However, the use of color-coding to identify categories is not supported. Potential reasons for this failure are discussed.

Article Free Access Share on The mirage rapid interface prototyping system Authors: James E. McDonald Computing Research Lab, New Mexico State University, Box 30001/3CRL, Las Cruces, New Mexico and Digital Subsystems II, Sandia National Laboratories, P.O. Box 5800, Albuquerque, New Mexico Computing Research Lab, New Mexico State University, Box 30001/3CRL, Las Cruces, New Mexico and Digital Subsystems II, Sandia National Laboratories, P.O. Box 5800, Albuquerque, New MexicoView Profile , Paul D. J. Vandenberg Computing Research Lab, New Mexico State University, Box 30001/3CRL, Las Cruces, New Mexico and Digital Subsystems II, Sandia National Laboratories, P.O. Box 5800, Albuquerque, New Mexico Computing Research Lab, New Mexico State University, Box 30001/3CRL, Las Cruces, New Mexico and Digital Subsystems II, Sandia National Laboratories, P.O. Box 5800, Albuquerque, New MexicoView Profile , Melissa J. Smartt Computing Research Lab, New Mexico State University, Box 30001/3CRL, Las Cruces, New Mexico and Digital Subsystems II, Sandia National Laboratories, P.O. Box 5800, Albuquerque, New Mexico Computing Research Lab, New Mexico State University, Box 30001/3CRL, Las Cruces, New Mexico and Digital Subsystems II, Sandia National Laboratories, P.O. Box 5800, Albuquerque, New MexicoView Profile Authors Info & Claims UIST '88: Proceedings of the 1st annual ACM SIGGRAPH symposium on User Interface SoftwareJanuary 1988Pages 77–84https://doi.org/10.1145/62402.62414Published:03 January 1988Publication History 1citation457DownloadsMetricsTotal Citations1Total Downloads457Last 12 Months43Last 6 weeks4 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Publisher SiteeReaderPDF

In this paper we propose a formal interface design methodology based on user knowledge. The general methodology consists of 1) obtaining distance estimates for pairs of system units (objects, actions, concepts), 2) transforming the distance estimates using scaling techniques (e.g., Pathfinder network analysis), and 3) organizing the system interface based on the scaling solution. Thus, the organization of the system is based on the cognitive models of users rather than the intuitions of designers. As an example, we discuss the application of our methodology to the design of a network-based indexing aid for the UNIX on-line documentation system (MAN).

The process of eliciting knowledge from human experts and representing that knowledge in an expert or knowledge-based system suffers from numerous problems. Not only is this process time-consuming and tedious, but the weak knowledge acquisition methods typically used (i.e., interviews and protocol analysis) are inadequate for eliciting tacit knowledge and may, in fact, lead to inaccuracies in the knowledge base. In addition, the intended knowledge representation scheme guides the acquisition of knowledge resulting in a representation-driven knowledge base as opposed to one that is knowledge-driven. In this paper, a formal methodology is proposed that employs techniques from the field of cognitive psychology to uncover expert knowledge as well as an appropriate representation of that knowledge. The advantages of such a methodology are discussed, as well as results from studies concerning the elicitation of concepts from experts and the assignment of labels to links in empirically derived semantic networks.