A framework for testing the learning of cognition-based human-computer interfaces

Abstract

<p>Successful implementation of Information Systems requires user acceptance. The old approach of adapting users to the system is no longer acceptable as more middle and senior professionals and managers are becoming system users. Due to the increasing people cost component of systems implementation, there has been a recognition that the human-computer interface must be easier to learn to use and recall for the individual who is both a novice and discretionary computer user. From the cognitive psychology literature, various principles can be applied to the interface design to improve learning and recall. These principles can be used by interface designers to improve the usability of the human-computer interface. Models of human-computer interaction have been devised by other researchers. However, to date there has been little available in the way of satisfactory methodologies or tools to allow designers to measure practically how an interface implementation performs with respect to both learnability and subsequent recall. This thesis develops a framework for testing human-computer interface learning. The framework differs from previous attempts in that it defines a new criteria for quantifying human-computer learning and recall, as well as providing a simple and effective tool for use by designers to determine such learnability metrics during the design process. In order to demonstrate the usefulness of the framework, it is used to experimentally test an original prototype interface design which attempts to improve human learning speed and memory retention using elaborative learning techniques and the "generation effect". The framework was able to measure significant differences between interfaces with respect to recall performance, and has demonstrated its utility as a contribution to the field of interface usability evaluation.</p>