Mental Models in Human-Computer Interaction Research Issues About What the User of Software Knows (1987) / Chapter Skim
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Mental Models in Human-Computer Interaction: Research Issues About What the User of Software Knows
Mental Models in Human-Computer Interaction: Research Issues About What the User of Software Knows
Pages 1-39
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1 Mental Models in Human-Computer Interaction: Research Issues About What the User of Software Knows
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Because a number of researchers are concerned with mental representations, and because this topic has an impact on cognitive psychology and software human factors, there is an emerging need to clarify the concepts underlying knowledge representation and mental models as they apply to human-computer interaction. We intend to fill this need by reviewing relevant current research and presenting a preliminary framework of the kinds of mental representations of procedures people might have.
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Engineers have mental models of their design. This highlights another distinction, that between descriptive and prescriptive representations.
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For example, a user who is a programmer might have a very different understanding of a piece of software than a person with no programming experience. Also, multiple mental models or several representations at different levels of abstraction might coexist within the same individual.
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Similarly, some word processors require the user to memorize short, common 1This is a subset of the knowledge Rouse and Morris (1986) call mental models.
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A second description of simple sequences of actions is the keystroke model (Card et al., 1980a,b, 1983; Embley et al., 1978)
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Simple algebra is then used to predict which of various whole design alternatives, or which of various user methods, will require the shortest time to perform. These analyses of simple sequences serve to facilitate both comparison of existing software packages for the one that will require the shortest time to perform and the design and development of new system languages.
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The GOMS model states that users have some rules by which they choose the method that will fit the current situation. For example, users may know that there are several methods that can be used to find the first place in the manuscript to be edited: using the search function with a distinguishing string to be found, using the page-forward key until the target page is found visually, or using the cursor key to find the specific target location visually.
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Command grammars use a different analytic representation, but are analyzing the same kinds of mental events. The command language grammar (CLG)
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. The formalism, however, allows a number of intriguing predictive possibilities for understanding and recalling command languages.
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. Mental models are used during learning (such as using an analogy to begin to understand how the system works)
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Metaphor Models A metaphor model is a direct comparison between the target system and some other system already known to the user. A common example, referred to widely in the literature, is the metaphor that "a text editor is a typewriter." Many investigators have observed that new users spontaneously refer to this typewriter metaphor during early learning about text processors (Bott, 1979; Carroll and Thomas, 1982; Douglas and Moran, 1983; Mack et al., 1983)
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. Glass Box Models Glass box models lie between metaphors and surrogates.
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. Studies of prescriptive conceptual models tell us something about what kinds of models are useful, and about models that people could generate.
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Circles represent states or tasks, arcs represent the connections between states, and labels to the arcs represent the actions the user takes. Source: Kieras and Polson (1983:104)
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The mental models approach, on the other hand, accounts for errors as well as accurate behavior in novel and standard situations, but does not predict the details of behavior well nor how the models are learned. Sequence/method representations, because they are composed of goal-action pairs, by their very nature predict how knowledge is used.
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Neither of these approaches addresses the continued learning that goes on as the user acquires or discovers new strategies for efficiency. Research on mental models, on the other hand, has not concentrated on the details of how a user uses a mental model nor how it is acquired.
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, we have not focused on these behavioral processes per se. Nevertheless, this aspect is critical both to assessing the empirical content of current analyses and to determining how these analyses might be applied to practical problems like the design of user interfaces and training materials.
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found that users performing a task in a menubased retrieval system developed and maintained simplistic sequences of actions that were eventually ineffective in accomplishing their search goals. Chaotic and misconceived conceptual models are not merely an issue of early learning and something that users outgrow.
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Whether they can be generalized to the greater cognitive complexity of human-computer interaction tasks is an open question. If we assume that knowledge of simple sequences is in the form of goal-action pairs, then we should be able to apply what we know from traditional verbal learning studies about the retention of paired associates (e.g., Hilgard and Bower, 1975; Postman and
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They argue that if one incorporates command names generated by naive users, these names are natural but often are not distinctive enough to allow users to keep from getting them confused among each other. Preexisting paired associates can help transfer, but if they are not distinct paired associates as a set (e.g., A-B may be good until it must be learned along with A-C)
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We have described them in terms of the theoretical representations posited and some of the cognitive processes included in each type of analysis. It seems safe to conclude that while the area of research on users' mental representations is very active, it is not yet well developed (see the Research Recommendations section below)
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One approach to picking a model is to design user interfaces to accord with naive user conceptual models (Carroll and Thomas, 1982; Mayer and Bayman, 1981)
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. The theoretical problem with this approach is that in the context of iterative and often radical redesign of a user interface, it is difficult to clearly separate the effect of the model on usability from that of other aspects of the redesign.4 A second design approach is to reduce the problem of communicating an appropriate conceptual model to the user by simplifying the system and its interface.
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Several researchers have been concerned with developing techniques for providing users with appropriate conceptual models, something that even state-of-the-art instructional materials for software often fail to do (Bayman and Mayer, 1984; DuBoulay et al., 1981; Halasz and Moran, 1982)
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Mayer (1976, 1981) provided students with a diagrammatic tool which incorporated a variety of concrete metaphors (e.g., input as a ticket window and storage as a file cabinet)
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Most of this work has focused on the use of mental models narrowly in training, namely, by telling the student the model or by providing simple and explicit advanced organizers (Ausubel, 1960)
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Here the desktop metaphor failed but also served to highlight effectively a specific fact about icon manipulation for the learner. The active learning view provides a means of reconciling the observation that mental models are often chaotic and misconceived and the fact that users do often succeed in learning and using software.
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The construction of the appropriate comparative test situations and the inferences that can be drawn from the responses, times, and errors must be based on a clearer notion of the form that the model might have and the processes that may act on it. If the analyst can predict behavior knowing that the person has a mental model of a particular sort, then the analyst should be able to discover the mental models of other people from systematic examination of their behavior.
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We currently have a better conception of what it means to have sequence/method representations and what processes may act on them to produce behavior than we do of mental models. GOMS represents the structure of goals, methods, and actions in a mental hierarchy for well-learned cognitive tasks.
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This report has reviewed a variety of types of knowledge that may be held by a user of a computer system. It is likely that users have some knowledge stored in several of these representations: some well known procedures for executing simple sequences; some well-formed GOMS-like structures for doing familiar but more complicated tasks; and some mental models that help the user explore alternative actions to take when an error occurs or when a novel task is presented to them.
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Most of the research in the area of mental models and sequence/method representations for human computer interaction has focused on text processing and simple device models. Whatever results
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These may be ideal domains in which to test notions of the use of mental models, the productive interaction of sequence/method representations and mental models, and the involvement of general problem-solving skills, reasoning, and decision making. REFERENCES Adelson, B
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(1982) User models of text editing command languages.
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Proceedings of the 1983 CHI Conference on Human Factors in Computing. New York: Association of Computing Machinery.
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Stevens (eds.) , Mental Models.
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(1986) Supervisory Control, Mental Models, and Decision Aids.
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Stevens (eds.) , Mental Models.
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