To understand the role of a human in a task, one frequently performs thorough task analyses. In contrast, mathematical and computer models are constructed infrequently and incompletely, perhaps because the perceived benefit of a model does not exceed the perceived cost of constructing it. We propose that task analyses often contain most of the information needed to construct a working model of a task, which can then be used to investigate task completion time. Some task analysis techniques, such as CPMGOMS (John, 1990; John & Gray, 1992), are so well developed as techniques that they directly result in computer models. Other techniques, such as hierarchical task analysis, produce detailed diagrams of operations and their relations but usually stop short of making predictions about task completion time. More can be accomplished with a little extra effort, because much of the work in making a model has already been done when a task analysis is completed.
Kieras and Meyer (2000) noted that there is great difficulty in using cognitive modeling in human factors to make predictions. Specifically, in basic cognitive modeling research, a model is tuned to fit data from successive experiments in an iterative process, but for engineering applications the current version of the model must make useful predictions about performance of a target system, which may not be built yet. This led Kieras and Meyer to say, "What is missing, and badly needed, is a demonstration that one can start with a conventional task analysis such as HTA [hierarchical task analysis] and then proceed systematically to a usefully accurate computational cognitive model, with no 'hand-waving' in between" (Kieras & Meyer, 2000, p. 258). In the present study, we propose a method that does just this. We show how a conventional task analysis can readily be extended, leading to the construction of a model suitable for computing the task completion time.
Task analysis refers to a set of techniques for describing and evaluating the actions that people engage in for satisfactory performance of a task. According to Kirwan and Ainsworth (1992), "Task analysis can be defined as the study of what an operator (or team of operators) is required to do, in terms of actions and/or cognitive processes, to achieve a system goal" (p. 1). Task analysis is used, among other things, to allocate functions to humans and machines, to specify characteristics of personnel, to design the task and interfaces, and to determine training requirements.
The result of a task analysis is a detailed description of all aspects of the task, based on observation, interviews, and inference. The purpose of this article is to show how to use this description to construct a model useful for finding the components of the task most critical for determining the completion time of the task. If a system is being designed, simulations with the model can provide estimates of what the task completion times will be with various proposed designs. Users are sensitive to small differences produced by different systems and will modify the organization of their behavior to take advantage of features of a system that shorten task completion time (Gray & Boehm-Davis, 2000).
One major technique for describing a system is hierarchical task analysis (Shepherd, 2001), developed initially by Annett and Duncan (1967). Because of its popularity and its handiness for determining task completion time, we will explain what we are doing in terms of hierarchical task analysis, but other forms of task analysis would be suitable starting points as well. Hierarchical task analysis is a specific method in which tasks are represented in terms of hierarchies of goals and subgoals. A very simple example is in Figure 1. The goal is to select an option from a pop-up menu that appears somewhere on a computer screen. The goal is achieved by carrying out operations according to plans. …