|©1990, 1995||section list||1: Introduction||overview||General Contents|
|1.1 Overview||Section 1.2|
This inter-disciplinary thesis is broadly concerned with how to investigate and model the cognition behind people's performance of tasks that deal with complex dynamic, or real-time, systems.
The remainder of Chapter 1 (Introduction and study context) introduces the background to this study, details the aspects that are explored in the study, and gives a view of the logical structure of the thesis. The issues of the thesis are not straightforward, and there are no easy solutions reported.
Chapter 2 (Mental models and cognitive task analysis literature) is a literature survey that ends up discovering little of direct positive relevance to the central field of interest. Its main relevance to the rest of the study lies in revealing the way in which the literature as a whole fails to address the relevant areas effectively.
Chapter 3 (Early studies) further defines the area of study by exploring, and ruling out, both a complete study of a naturally occurring complex task (ship navigation), and machine learning approaches that are not based on human performance data.
Chapter 4 (The Simple Unstable Vehicle: a manual control task) reports the more detailed exploration experimentally, of a manual control task (a simulated bicycle-like vehicle) and explains the reasons, chiefly concerning psycho-motor issues, why this too is unsuitable for immediate study here.
Chapter 5 (Non-manual control task selection) is a detailed statement of the necessary features of a task that could be studied in the manner envisaged here. This would be useful for anyone considering undertaking a similar study. It goes on to evaluate options available at the time of the study, concluding that no available systems were suitable, and that a new task had to be constructed specially.
Chapter 6 (The Sea-Searching Simulation task and first experiment) describes the construction of a nautical mine-sweeping simulation task, suitable for the desired experiments, implemented on a Silicon Graphics Iris 3130 workstation, and now being held by YARD Ltd., Glasgow. Rule-induction was found to be a viable analytic tool enabling comparison of representations, and opening up many possibilities for deeper exploration. The methods of data preparation and analysis used, are discussed at length in this chapter.
Chapter 7 (Sea-Searching Simulation task: second experiment), following the findings of Chapter 6, investigates costing information, for a modified version of the same task, as a means of discovering about information use, and about the human structuring of the task. Here, novel analytic techniques are introduced, revealing an individual `context' structure to the task. Ideas both for extensions of these experiments, and for further experiments on the same task, are included in the discussion at the end of this chapter.
Chapter 8 (Overall interpretation of results, conclusions and directions) summarises the main findings of the study, also explaining the nature of the results, along with ideas about the work needed to make the results more general. Suggestions on overcoming the great remaining obstacles to applying this methodology to real tasks are put forward. This application could be to interface redesign, systems design, and training; and for operator support, we introduce the Guardian Angel paradigm, as a vision of what could eventually follow on from this work. Lastly, the implications for further work are explored. These focus around the idea of a new approach to rule induction, using a human-like context structure, which could be based on the principle of minimising the cognitive requirements of executing a task.
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