Clayton Lewis

Designing for usability: key principles and what designers think

This article is both theoretical and empirical. Theoretically, it describes three principles of system design which we believe must be followed to produce a useful and easy to use computer system. These principles are: early and continual focus on users; empirical measurement of usage; and iterative design whereby the system (simulated, prototype, and real) is modified, tested, modified again, tested again, and the cycle is repeated again and again. This approach is contrasted to other principled design approaches, for example, get it right the first time, reliance on design guidelines. Empirically, the article presents data which show that our design principles are not always intuitive to designers; identifies the arguments which designers often offer for not using these principles—and answers them; and provides an example in which our principles have been used successfully.

Cognitive walkthroughs: a method for theory-based evaluation of user interfaces

This paper presents a new methodology for performing theory-based evaluations of user interface designs early in the design cycle. The methodology is an adaptation of the design walkthrough techniques that have been used for many years in the software engineering community. Traditional walkthroughs involve hand simulation of sections of code to ensure that they implement specified functionality. The method we present involves hand simulation of the cognitive activities of a user, to ensure that the user can easily learn to perform tasks that the system is intended to support. The cognitive walkthrough methodology, described in detail, is based on a theory of learning by exploration presented in this paper. There is a summary of preliminary results of effectiveness and comparisons with other design methods.

Testing a walkthrough methodology for theory-based design of walk-up-and-use interfaces

The value of theoretical analyses in user interface design has been hotly debated. All sides agree that it is difficult to apply current theoretical models within the constraints of real-world development projects. We attack this problem in the context of bringing the theoretical ideas within a model of exploratory learning [19] to bear on the evaluation of alternative interfaces for walk-up-and-use systems. We derived a “cognitive walkthrough” procedure for systematically evaluating features of an interface in the context of the theory. Four people independently applied this procedure to four alternative interfaces for which we have empirical usability data. Consideration of the walkthrough sheds light on the consistency with which such a procedure can be applied as well as the accuracy of the results.

A problem-oriented classification of visualization techniques

Progress in scientific visualization could be accelerated if workers could more readily find visualization techniques relevant to a given problem. The authors describe an approach to this problem, based on a classification of visualization techniques, that is independent of particular application domains. A user breaks up a problem into subproblems, describes these subproblems in terms of the objects to be represented and the operations to be supported by a representation, locates applicable visualization techniques in a catalog, and combines these representations into a composite representation for the original problem. The catalog and its underlying classification provide a way for workers in different application disciplines to share methods.<<ETX>>

Do algorithm animations assist learning?: an empirical study and analysis

Algorithm animations are dynamic graphical illustrations of computer algorithms, and they are used as teaching aids to help explain how the algorithms work. Although many people believe that algorithm animations are useful this way, no empirical evidence has ever been presented supporting this belief. We have conducted an empirical study of a priority queue algorithm animation, and the studys results indicate that the animation only slightly assisted student understanding. In this article, we analyze those results and hypothesize why algorithm animations may not be as helpful as was initially hoped. We also develop guidelines for making algorithm animations more useful in the future.

Making usable, useful, productivity-enhancing computer applications

Almost a decade has passed since we started advocating a process of usability design. This article is a status report about the value of this process and, mainly, a description of new ideas for enhancing the use of the process

Designing for error

Publisher Summary This chapter describes the system design process that deals with errors in an effective manner. Several things can be done to manage errors. One is to try to devise systems that eliminate or minimize errors. Another is to try to make it easier to deal with error when it exists, first by providing clear indication of the problem and its possible causes and remedies, and second, by providing tools that make correction easier. Finally, because many errors—sometimes serious ones—go undetected for surprisingly long times, the system should provide the kind of information that helps the user understand the implications of the actions being followed. The errors can be divided into two major categories: (1) mistakes and (2) slips. The division occurs at the level of the intention. A person establishes an intention to act. If the intention is not appropriate, this is a mistake. If the action is not what was intended, this is a slip.

Interference with Real World Knowledge

Abstract Two experiments are described in which subjects studied made-up, fantasy facts about well-known persons and then were asked to verify actual facts about these persons. Reaction time to the actual facts was longer the more fantasy propositions studied about a person. Reaction time was also longer when the verification test involved a mixture of actual and fantasy facts rather than just actual facts. A mathematical version of the ACT model ( Anderson, 1976 ) was fit to the data. It provides a satisfactory fit, better than an alternate model. However, some of the parameter values estimated for the ACT model seemed unreasonable.

Why and how to learn why: Analysis-based generalization of procedures ☆

Max Wertheimer, in his classic Productive Thinking, linked understanding to transfer: Understanding is important because it provides the ability to generalize the solution of one problem to apply to another. Recent work in human and machine learning has led to the development of a new class of generalization mechanism, called here analysis-based generalization, which can be used to provide a concrete account of the linkage Wertheimer suggested: these mechanisms all, in different ways, use understanding of examples in the generalization process. In this paper I review this class of mechanism, and describe a method for causal attribution that can produce the analyses of examples that the generalization methods require, in the domain of simple procedures in human-computer interaction. This causal analysis method is linked with analysis-based generalization to form EXPL, an implemented model which is a concrete, though limited, instontiation of Wertheimer s scheme. EXPL constructs an understanding of an example procedure and generalizes it on the basis of that understanding. Results of an empirical study suggest that some of EXPLs attribution heuristics are used by people, and that while a subclass of analysis-based methods, called superstitious methods, seem to provide a more plausible account of peoples generalization under the conditions of the study than a contrasting class of rationalistic methods, at least some participants appear to use methods from both classes. The results also show that explanation-based methods, which rely on comprehensive domain theories, must be used in conjunction with a means for extending the domain theory. If thus enhanced, explanation-based methods are able to mimic the effects of other analysis-based methods, and can provide a good account of the data, though combinations of other methods must also be considered. Finally, I return to Wertheimer s ideas to argue that none of the current analysis-based generalization methods fully captures Wertheimer s notion of understanding. Proper choice among different possible analyses of an example is crucial for Wertheimer, but I argue that this problem may be beyond the reach of learning systems.

Spreadsheet-based interactive graphics: from prototype to tool

The NoPumpG prototype [7,8] suggested that the spreadsheet model of computation could simplify the creation of some types of interactive graphical application when compared with other approaches. We report here experience in developing an enhanced follow-on system, NoPumpII, and describe three applications developed using it. We conclude that (1) the potential advantages of the spreadsheet model are realized in this application experience, (2) revisions to the prototype design have permitted an increase in the complexity and scale of applications, and (3) there remain limitations in the current design which, if redressed, would further enlarge the scope of application. More generally we conclude that alternative computational models are an important area of exploration for HCI research.