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Mental Moclels in
H uman-Computer
~ nteraction
Research Issues About What the
User of Software Knows
John M. Carroll and Judith Reitman Olson, Editors
Workshop on Software Human Factors:
Users' Mental Models
Nancy Anderson, C-hair
Committee on Human Factors
Commission on Behavioral and Social Sciences and Education
National Research Council
-
NATIONAL ACADEMY PRESS
Washington, D.C. 1987
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NOTICE: The project that is the subject of this report was approved by the Governing
Board of the National Research Council, whose members are drawn from the councils
of the National Academy of Sciences, the National Academy of Engineering, and the
Institute of Medicine. The members of the committee responsible for the report were
chosen for their special competences and with regard for appropriate balance.
This report has been reviewed by a group other than the authors according to
procedures approved by a Report Review Committee consisting of members of the
National Academy of Sciences, the National Academy of Engineering, and the Institute
of Medicine.
The National Academy of Sciences is a private, nonprofit, self-perpetuating society
of distinguished scholars engaged in scientific and engineering research, dedicated to th'e
furtherance of science and technology and to their use for the general welfare. Upon
the authority of the charter granted to it by the Congress in 1863, the Academyihtas
a mandate that requires it to advise the federal government on scientific and technical
matters. Dr. Frank Press is president of the National Academy of Sciences.
The National Academy of Engineering was established in 1964, under the charter
of the National Academy of Sciences, as a parallel organization'of outstanding engineers.
It is autonomous in its administration and in the selection of its members, sharing with
the National Academy of Sciences the responsibility for advising the federal government.
The National Academy of Engineering also sponsors engineering programs aimed at
meeting national needs, encourages education and research, and recognizes the superior
achievements of engineers. Dr. Robert M. White is president of the National Academy
of Engineering.
The Institute of Medicine was established in 1970 by the National Academy of
Sciences to secure the services of eminent members of appropriate professions in the
examination of policy matters pertaining to the health of the public. The Institute acts
under the responsibility given to the National Academy of Sciences by its congressional
charter to be an adviser to the federal government and, upon its own initiative, to
identify issues of medical care, research, and education. Dr. Samuel O. Thier is president
of the Institute of Medicine.
The National Research Council was organized by the National Academy of Sciences
in 1916 to associate the broad community of science and technology with the Academy's
purposes of furthering knowledge and advising the federal government. Functioning in
accordance with general policies determined by the Academy, the Council has become the
principal operating agency of both the National Academy of Sciences and the National
Academy of Engineering in providing services to the government, the public, and the
scientific and engineering communities. The Council is administered jointly by both
Academies and the Institute of Medicine. Dr. Frank Press and Dr. Robert M. White are
chairman and vice chairman, respectively, of the National Research Council.
The United States government has at least a royalty-free, nonexclusive and irre-
~rocable license throughout the world for government purposes to publish, translate,
reproduce, deliver, perform, dispose of, and to authorize others so as to do, all or any
portion of this work.
Available from
Committee on Human Factors
Commission on Behavioral and Social Sciences and Education
National Research Council
2101 Constitution Ave., N.W.
Washington, D.C. 20418
Printed in the United States of America
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WORKSHOP ON SOFTWARE HUMAN FACTORS:
USERS' MENTAL MODELS
NANCY ANDERSON (Chair), Department of Psychology,
University of Maryland
ELIZABETH K. BAILEY, Consultant, Falls Church, Virginia
JOHN M. CARROLL, Watson Research Merited, IBM
Corporation, Yorktown Heights, New York
RICHARD J. JAGACINSKI, Department of Psychology, Ohio
State University
DAVID R. LENOROVITZ, Computer Technology Associates,
Inc., Englewood, Colorado
MARILYN MANTEl, Center for Machine Intelligence, Ann
Arbor, Michigan
PHYLLIS RElSNER, Almaden Research Center, IBM Research,
San Jose, California
JUDITH REITMAN OLSON, Department of Computer and
- Information Systems, Graduate School of Business
Administration, University of Michigan
JANET WALKER, Symbolics, Inc., Cambridge, Massachusetts
JOHN WHITESIDE, Digital Equipment Corporation, Nashua,
New Hampshire
STANLEY DEUTSCH, Study Director
111
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COMMITTEE ON HUMAN FACTORS
1986-1987
THOMAS B. SHERIDAN (Chair), Department of Mechanical
Engineering, Massachusetts Institute of Technology
NANCY S. ANDERSON, Department of Psychology, University
of Maryland
CLYDE H. COOMBS, Department of Psychology, University of
Michigan
JEROME I. ELKIND, Information Systems, Xerox Corporation,
Palo Alto
BARUCH B. FISCHHOFF, Decision Research (a branch of
Perceptronics, Inc.), Eugene, Oregon
OSCAR GRUSKY, Department of Sociology, University of
California, Los Angeles
ROBERT M. GUION, Department of Psychology, Bowling Green
State University
DOUGLAS H. HARRIS, Anacapa Sciences, Santa Barbara,
California
JULIAN HOCHBERG, Department of Psychology, Columbia
University
THOMAS K. LANDAUER, Information Sciences Division, Bell
Communication Research, Morristown, New Jersey
JUDITH REITMAN OLSON, Department of Computer and
Information Systems, Graduate School of Business
Administration, University of Michigan
RICHARD W. PEW (Past Chair), Computer and Information
Sciences Division, Bolt Beranek and Newman Laboratories
Cambridge, Massachusetts
STOVER H. SNOOK, Liberty Mutual Research Center
Hopkinton, Massachusetts
v
L ~
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ROBERT C. WILLIGES, Department of Industrial Engineering
and Operations Research, Virginia Polytechnic Institute and
State University
STANLEY DEUTSCH, Study Director (1984-1987)
HAROLD VAN COTT, Study Director
E~UM - p. vii
The Air Force office of Scientific Research
should have been included as one of the
sponsors of the Committee on Human Factors.
V1
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Foreword
The Committee on Human Factors was established in October
1980 by the Commission on Behavioral and Social Sciences and
Education of the National Research Council. The committee is
sponsored by the Office of Naval Research, the Army Research
Institute for the Behavioral and Social Sciences, the National
Aeronautics and Space Administration, and the National Science
Foundation. The principal objectives of the committee are to
provide new perspectives on theoretical and methodological issues,
to identify basic research needed to expand and strengthen the
scientific basis of human factors, and to attract scientists both
within and outside the field for interactive communication and to
perform needed~research. The goal of the committee is to provide
a solid foundation of research as a base on which effective human
factors practices can build.
Human factors issues arise in every domain in which humans
interact with the products of a technological society. In order to
perform its role effectively, the committee draws on experts from
a wide range of scientific and engineering disciplines. Members of
the committee include specialists in such fields as psychology, en-
gineering, biomechanics, physiology, medicine, cognitive sciences,
machine intelligence, computer sciences, sociology, education, and
human factors engineering. Other disciplines are represented in
the working groups, workshops, and symposia. Each of these dis-
ciplines contributes to the basic data, theory and methods required
to improve the scientific basis of human factors.
· .
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Contents
Abstract ee ~ o~ XV
Introduction .
Models of What, Held by Whom? ....
Types of Representations of Users' Knowledge..
Simple Sequences, 6
Methods and Ways to Choose Among Them, 8
Mental Models, 12
Surrogates, 13
Metaphor Models, 13
Glass Box Models, 14
Network Representations of the System, 15
Comparisons, 17
How Users' Knowledge Affects Their Performance.
Chaos and Misconception in Both Novices and
Experts, 20
Skilled Performance, 21
.19
Applying What We Know of the User's Knowledge to
Practical Problems 23
Designing Interfaces, 24
User Training, 26
Research Recommendations.
References .
1X
29
....34
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Preface
There has been a long-standing problem with inferring the
causes of complex behavior. Mental events are not directly ob-
servable; they must be inferred from overt behavior. Behaviorists
reject mental events as legitimate scientific concepts. More re-
cently,~ however, developments in cognitive science and artificial
intelligence, in which mental events are specifically modeled and
found to have measurable correlates in behavior, have brought the
concepts back into fashion. These mental events, their description
and postulated interrelationships, are the subject of this report.
We focus specifically on the mental events that are postulated to
occur as someone learns or performs complex tasks on computer
software.
From the point of view of cognitive science, users of computer
software systems base their behavior on stored knowledge about
particular sequences of actions, on general rules about how to
accomplish certain tasks, or on a mental mode! fan underlying
understanding of how the system works). Knowing what the user
knows about or expects from a system has implications for both
design and training purposes. From a design point of view, the
system could be designed to fit the user's goals in accomplishing
tasks or could display enough of how it works to make accomplish-
ing a task easy to understand. From the training point of view,
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users could be given instructions aunt exercises that clearly present
sequences, rules, and/or a mode} in order to make learning and
-
per ormlng easy.
At present, there is no satisfactory way of describing what
the user knows. There Is no way to characterize the differences
among users of various systems as they go through the process
of developing an awareness and understanding of how the system
works or how a given task is to be performed. Consequently, the
Committee on Human Factors conducted a two-day workshop on
May 15 and 16, 1984, to determine means for achieving a better
understanding of what users know and its implications for system
and software design as well as user training. This workshop was
a continuation of the committee's efforts to define research needs
in the area of software human factors. Ten nationally known
researchers on software design, cognitive psychology, and human
factors met to discuss the issues having to do with what a user of
software knows.
As background for this workshop, John M. Carroll wrote an
invited paper entitled "Mental Modeb and Software Human Fac-
tors: An Overview. This was distributed to all participants in
advance of the meeting. In turn, the workshop members prepared
short two. to three-page position papers addressing additional top-
ics and issues that they believed were important and warranted
discussion at the workshop. Much of the discussion at the work-
shop centered on sifting through the many definitions of the term
mental model, gathering ideas from among the variety of methods
used to represent users' knowledge about software systerr~s.
This report was prepared by merging the ideas generated by
the workshop members with those in Carroll's paper. It includes
his central organization and literature review, adds more recent
information, and clarifies the distinction between mental models
and task representations. This report was then distributed to
workshop participants for changes and additions.
This report is written for the researcher concerned with the
psychology of performance of complex tasks and for the prac-
titioner who would like to use information about how the user
thinks about both the task and the system in the design of com-
puter software, its documentation, or training for its use. Most
of the research on these questions has used software-based text-
editing tasks as a domain and looked at the mental models people
are purported to build of only simple devices. The results should be
·—
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gener~lzed to even more complex tasks, such ~ process control,
t=Ucal decision m~lng' project pl~nlug, and ~~blcs design;
but tbek scope bag not been tested. Abe exclusion ~ these kluds
of tasks ~ not to be taken ~ ~ ludlc~lon that the rese~rcb re-
ported cannot cover these more complex tasks. But their scope
an important resewn need.
Judith ~~ Olson
. ..
flu
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Abstract
Users of software systems acquire knowledge about the system
and how to use it through experience, training, and imitation.
Currently, there is a great deal of debate about exactly what users
know about software. This knowledge may include one or more of
the following:
simple rules~that prescribe a sequence of actions that apply
under certain conditions;
general methods that fit certain general situations and
goals; and
mental models, knowledge of the components of a system,
their interconnection, and the processes that change the
components; knowledge that forms the basis for users be-
ing able to construct reasonable actions; and explanations
about why a set of actions is appropriate.
Discovering what users know and how these different forms
of knowledge fit together in learning and performance is impor-
tant. It applies to the problem of designing systems and training
programs so that the systems are easy to use and the learning is
efficient. Research on the effects of different representations on
ultimate performance is mixed. Research on exactly what users
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know is scattered. Analytical methods and techniques for repre-
senting what the user knows are sparse but growing.
This report reviews current work and through the review,
identifies several important research needs:
Detail what kinds of mental representations people have of
systems that allow them to behave appropriately in using
the software.
Detail what a mental mode! would consist of and how a
person would use it to decide what action to take next.
Produce evidence that people have and use mental models.
Determine the behaviors that would demonstrate a mental
model's form and the operations used on the model.
Explore alternative views of goal-directed representations
(e.g., so-called sequence/method representations) and de-
tai} the behavior predicted from them.
Expand the types of mental representations that may exist
to include those that may not be mechanistic, such as
algebraic and visual systems.
Determine how people intermix different representations in
producing behavior.
Explore how knowledge about systems is acquired.
Determine how individual differences have an impact on
learning of and performance on systems.
Explore the design of training sequences for systems.
Provide systems designers with tools to help them develop
systems that evoke "good" representations in users.
Expand the task domain of this research to include more
complex software.
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