Quantitative Modeling of Human Performance in Complex, Dynamic Systems (1990) / Chapter Skim
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2. Approaches to Human Performance Modeling
2. Approaches to Human Performance Modeling
Pages 16-51
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From page 16... ...
For example, models of human reaction time typically predict response time primarily as a function of the number of possible signals or their relative probability, and give seconda~y consideration to physical factors such as how far apart Me response keys are, whether eye movements are needed to monitor signal occurrence, or anatomical dimensions of the operator that might affect performance. Several of Me human information processing models have been adapted from engineering models to represent human behavior.
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From page 17... ...
There are also many models of shortterm memory (see, for example, Norman, 19 70~. Yet, however successfully it is validated in a laboratory setting, each models only a small part of human information processing, and the interaction among models of limited scope cannot be specified nor can the overall behavior of the human be predicted.
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From page 18... ...
In applied settings, particularly in system design, only a small subset of human behavior can be predicted by a model of limited scope. If other aspects of information processing affect the output of the model in uncertain ways and if the properties of the environment (such as the spacing of displays or the force required to activate a control)
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From page 19... ...
. The task network approach, which emerged from operations research, is oriented primarily toward the sequencing of large numbers of discrete tasks arranged in an appropriate network so as to achieve a particular goal; models based on this approach focus on the time required to complete individual and total tasks and the error probabilities associated with performing these tasks.
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From page 20... ...
Classical information theory describes the relation of signal probability to reaction time (Hick, 1952~. Signal detection theory accounts for the relative effects of signal strength and the observer's response bias in the detection of sensory Formation (Green and Swets, 1966~.
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From page 21... ...
This contains and controls a highly integrated set of information processing submodels, each with its own set of algorithms and rules of operation. The rationale underlying development of the HOM process submodels is that, although thousands of different operator tasks exist, they require only a limited number of different microactions such as reaching for and manipulating control devices, recalling information from short-term memory, looking at displays, and absorbing information from them.
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From page 22... ...
... _ ~ ~}1 _ _ GRASP ~ 1 LOOK AT Lo Invoking of Microactions ( Knowledge List ~ ~ - - _ Invoking Transfer/Recall FIGURE 2-2 Major submodels and knowledge lists in the Human Operator Simulator (HOS)
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From page 23... ...
APPROACHES TO HUMAN PERFORMANCE MODELING the simulated operators lonP-term memory. 23 , ~ , · Attention and recall of current task responsibilides: The HOM assumes operators can work on, or attend to, only one active procedure at a time, although rapid changes in attention among active tasks are permitted.
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From page 24... ...
24 QUANTITATIVE MODELING OF HUMAN PERFORMANCE Assertions can be simple (e.g., ALTITUDE IS LESS THAN 1,000 FEET) or highly complex (i.e., by using logical ANDs, ORs, and NOI§)
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From page 25... ...
In addition, operator loading, down to individual body parts, can be examined. A significant advantage of HOS lies in He manner in which task times for the resident HOM are determined.
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From page 26... ...
26 QUANTITATIVE MODELING OF HUMAN PERFORMANCE 3 on board three different versions of P-3C ASW (and-submarine warfare) patrol aircraft, a pilot in a NASA lbrrn~na1 Configured Vehicle (TCVy, and the Tactical Officer (TACCO)
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From page 27... ...
Subsequent modifications of initial inputs can usually be made rapidly to test the impact of suggested changes on any portion of system design, and HOS can have its greatest impact on system design when used in this way. A goal of HOS development was to minimize the need for users to estimate the means and variances of the hundreds of task times that might be required by a task network approach model.
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From page 28... ...
In addition, techniques used to develop manual control models, as well as some of the models themselves, have been used successfully to model human performance in tasks other than manual control. The most successful approaches to modeling human manual control performance have drawn on the theory and techniques of control system design, analysis, and evaluation.
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From page 29... ...
The principal areas of manual control modeling needing further work are mult~variable control, control of nonlinear systems, control of highly automated and slowly responding systems, and modeling the performance of less than fully trained operators. Ho distinguishable trends in HEM development using control theory have emerged over the past decade.
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From page 30... ...
The information processing model represents the operator's ability to construct from his understanding of the system, and to derive from incomplete and imperfect knowledge of the moment-by-moment state of the system, a set of expectancies concerning the actual system state as needed for control or decision making. The OCM structure described above, with the continuous control portion replaced by appropriate decision elements, has been used as a basis for human performance models of failure detection (Gal and Curry, 1976; Wewerinke, 1981)
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From page 32... ...
The PF and PNF models employ derivatives of the basic information processing structure used in me OCM and other control-theoretic models mentioned above. 1b this structure, mechanisms are added for dealing with the multitask environment, including those necessary to account for task selection and the execution of routine procedures or discrete tasks.
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From page 33... ...
In addition, the structure lends itself to a synthesis of venous approaches to modeling human performance. For example, in addition to aspects drawn from existing control theory models, PROCRU models discrete tasks and rule-based procedural activities in fashions that are analogous to those used in the task network and knowledge-based approaches, respectively.
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From page 34... ...
A task is usually described by an operator action, an object of that action, and other qualifying or descriptive information, for example, time to complete the tasL A procedure is a collection of tasks required to accomplish some goal. A task network is a collection of procedures and tasks that contains hierarchical and sequence information The task network approach has been He basis of many early uses of human performance models in complex, practical, real-world systems.
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From page 35... ...
5. The task network approach may be used at many levels of human performance modeling from high-level mission performance to low-level button-pushing tasks.
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From page 36... ...
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From page 37... ...
Time/Accuracy Models There is no explicit human performance information shown in the task network, but there are some implicit assumptions about human performance: tasks will be done in the order shown, and a procedure/task cannot be started until the preceding procedure/task has been completed. The early applications of the task network approach assigned attributes to each task such as time to complete a task and probability of correct execution; these attributes were used to compute performance.
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From page 38... ...
(Miller, 1976~. The task network is then executed, usually without random task times, to determine a time profile of operator loading.
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There is no single macromodel for the task network approach to human performance modeling because there is no unique method to model the two
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From page 40... ...
The task selection logic emphasizes task precedence, resource availability, and random choice, but there is no specification of how to accomplish simultaneous tasks. In addition, SAW allows the use of resource parameters that could be employed to represent human information-processing resources.
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From page 41... ...
The tasks queue up until they are processed, as in the time-required model described earlier. Strengths The advantages of the task network approach to human performance modeling are its intrinsic generality and the ability to formulate HPMs at any desired level of demiL The task network approach encourages tOpdown modeling.
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From page 42... ...
(Note how little human performance modeling is displayed in Figure 24.) Inasmuch as each new task network can be, in a sense, a new human performance model, the validity of extrapolations to new domains or modifications of new tasks in a domain must be evaluated carefully.
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From page 43... ...
In particular, knowledge-based models use an architecture of the mind that Is quite different from the architecture of a conventional Ton Neuman machine. As Figure 2-5 shows, knowledge is organized into two distinct classes: information in working memory and information in long-term memory.
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From page 44... ...
General problem-solving rules are called weak rules because they are only weakly dependent upon the context in which they are used. In expert systems research, weak rules are sometimes referred to, collectively, as the inference engine, because they control the process of inferential reasoning that is applied within a specific problem-solving domain.
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From page 45... ...
, a program that relied on context Dee inference rules to solve problems, given only a minimum of domain specific knowledge. For example, given appropriate minimal definitions of the domain, He GPS program solved problems in chess, calculus, and symbolic logic (Ernst and Newell, 1969; Newell and Simon, 1972~.
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From page 46... ...
These programs are shells or inference engines containing weak rules that organize the domain-specific rules established by the user (Aim and Coombs, 1984; Goodall, 1985~. Examples of shells include EMYCIN, KAS (Knowledge Acquisition System)
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From page 47... ...
A knowledge-based model of problem solving that uses schema is in some sense intermediate between our definitions of comprehensive and limited-scope models. Programs have been developed that utilize schemes appropriate for solving certain classes of problems in different fields, ranging from word problems in school arithmetic to problems in elementary physics.
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From page 48... ...
Air Force and Navy. In summary, knowledge-based modeling appears to be a very promising way of modeling human cognitive activities in complex supervisory control situations.
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From page 50... ...
In addition, proponents of the information processing, optimal control, and task network approaches are in venous stages of explonng, implementing, and testing methods for including knowledge-based behavior of one sort or another within their respective models. Second, some significant general concerns apply to all of the approaches:
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From page 51... ...
Finally, it is significant to note that there are several viable approaches to developing comprehensive human performance models of pragmatic utility to system designers and developers. Presently, and for the foreseeable future, no single approach is likely to dominate the field; rather, it is to be expected that the various approaches will be applied most effectively in problems closest to their original focus of development.
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