Abstract
This tutorial provides a "hands-on" (actually, "minds-on")
exploration of several basic processes and phenomena of human memory,
and problem solving. Th e emphasis is on developing both intuitive
and formal knowledge which can serve as background knowledge useful in
making educated design judgments when design guidelines fail,
conflict, or are nonexistent. The demonstrations used emphasiz e
phenomena with which any theory of memory or problem solving must
deal. In addition, the tutorial suggests some of the general
implications of these phenomena for designing interactive computing
systems.
Keywords:
Memory, Problem Solving, Design, Models of the User
Introduction AND CAVEATS
The emphasis in this tutorial is on demonstrations and exercises which
highlight some of the quite remarkable things human beings do in
interacting with, in learning about, and in making sense out of the
world around them. These things often seem to be quite ordinary
simply because we do them regularly, often without deliberation.
Nonetheless, some of them are quite complex and not well understood.
Since this tutorial emphasizes the development of an intuitive feel
for the material, it is important to recognize that an intuitive
understanding must be informed and validated by research results.
Ever since its founding, the findings of Experimental Psychology have
taught us not to trust unsupported personal hunches and intuitions
about the reasons for human behavior. There are a variety of ways in
which ordinary day-to-day intuitions about behavior, both our own and
that of others, can lead one astray (some are illustrated in the
tutorial). Most of the demonstrations used in this tutorial are
designed to replicate phenomena which have been studied or validated
under controlled laboratory conditions. In fact, several of the
demonstrations are drawn directl y from research studies, although
some procedural license is taken for purposes of demonstration.
MEMORY In one model of memory STM is described (e.g., 1, 6) as having
a limited storage capacity (seven plus or minus two chunks) for a
relatively brief duration (estimates range from 12 to 30 seconds
without rehearsal). Information can be maintained in STM for longer
periods of time with maintenance rehearsal (MR), although this simple
repetition of material does not appear to be very efficient at
transferring information into Long Term Memory (LTM). Rather,
elaborative rehearsal (ER) appears to be the most effective set of
processes for the transfe r of information into long-term storage.
Although the information in STM is usually thought to be represented
by one of a relatively limited number of codes , there are several
reasons to believe that any organizational structure in LTM is
accessible as a basis for forming the chunks that are held in STM.
LTM has a large capacity for storage of information for long periods
of time. There is, however, no easy or obvious way to determine the
limits of how much ca n be stored, or for how long it can be stored.
Several types of information are represented in LTM, including such
things as facts and events, motor and perceptual skills, knowledge of
physical laws and systems of mathematics, a spatial model of the world
around us, attitudes and beliefs about oneself and others, etc. This
information is more or less well organized, in a variety of ways, and
varies in its accessibility as a function of several factors. The
factors determining accessibility of the information in LTM include
such things as the conditions which existed at the time the
information was stored, the recency of its last use, its degree of
inter-relationship with other knowledge, its degree of uniqueness
relative to other information, etc. Most discussions o f failure to
recall information from LTM focus on explanations such as
interference, the absence or inappropriateness of retrieval cues, or
some type o f organic dysfunction such as brain damage.
An alternative model of human memory holds that there is no need to
postulate a STM. Rather, different degrees of persistence of
information in memory are thought to be a function of the depth to
which information has been processed. The greater the depth of
processing, the longer the retention period. In this model, chunks
are organizational units in LTM and the capacity limitation is on how
much information can be actively scanned at any given time. While
evidence exists to support each model of memory, and while the bulk of
the evidence seems to support the second model [1], there are certain
basic phenomen a with which any theory of memory must deal. For
example, regardless of whether one thinks of the seven plus or minus
two capacity limitation as the result of a limited capacity memory or
as a result of a limit on the amount of information which can be
activated and maintained in an active state at any given time, it i s
clear that there is a capacity limitation. Similarly, regardless of
whether one thinks that memory rehearsal processes have different
degrees of depth or that there are two different kinds of rehearsal
processes, it is clear that elaborative rehearsal is more effective
than maintenance rehearsal in insuring that the information will be
accessible in memory for a long period of time.
PROBLEM SOLVING
A major turning point in the literature on problem solving occurred
with the work of Newell and Simon (4). In their view, a problem can
be analyzed by means of a "problem space" representing various states
of knowledge of the problem solver, a series of transformations
between states, and a set of operators which produce those
transformations. A problem exists when we have a gap between an
initial state and a goal state. The means of solving the problem
involves applying the appropriate set of operators required to
complete a series of state transformations that will eliminate the
gap. These transformations must be accomplished without violating any
of the conditions on the operators.
As a result of repeated experience, problem solvers build up an
organized body of knowledge or information about the properties of a
particular type of problem and the operations or steps required to
solve it. This organized body of information is usually referred to
as a problem solving schema (e.g., 5). Human s develop a wide variety
of familiar problem schemas (3), and the typical individual has built
up a stock of such schemas which come into play in solving problems.
Some of these schemas are so familiar that they are activated almost
automatically and without much thought.
Typically, the effect of problem solving schemas is to help provide
reasonably efficient methods of solving frequently encountered kinds
of problems. However, sometimes a schema can interfere with the
problem solving process. Since it influences the problem solver's
early analysis of the problem and determines which schema, or schemas,
will be brought to bear in solving a particular problem, the way in
which that problem is represented can make a vital differenc e in how
easily the problem can be solved. When a problem is not solved as
easily as expected. it is often quite fruitful to look to the
adequacy of the representation of the problem, and to give thought to
changing that representation.
SOME IMPLICATIONS FOR HUMAN-COMPUTER INTERACTION DESIGN
In considering the nature of human memory it is clear that designers
need to take account of the fact that there are a limited number of
"chunks" of information with which a user can actively cope at any
given time. While the size of those chunks can be affected by the
development of additional new knowledge structures, that growth of
knowledge requires that the user be activel y engaged in elaborating
and assimilating that knowledge. In addition the demands upon human
learning and memory can be reduced by providing appropriate mnemonic
cues in the interface. In considering the nature of human problem
solving it is clear that designers need to take account of the fact
that users will bring to bear established problem solving strategies
which are developed from having solved problems which have been
frequently encountered in the past. While these established
strategies can be used to facilitate usage they can also create
process blockages which may only be solved by changing the way in
which the problems of interaction are presented to the user.
Among the general implications of the phenomena described above for
human-computer interaction design there are two which stand out. The
first of these, derived from consideration of the nature of long term
memory and the processes governing storage and retrieval of
information, is that humans interacting with computers can and do use
existing memories and memory structure s to assign a meaning or
interpretation to a wide variety of things, regardless of whether that
meaning was intended by the designers. The second major implication,
derived from consideration of the nature of the way people solve
problems is that, people ?...do not do what designers want them to do;
instead they tend to get actively involved and to think and plan and
solve problems (2). ?
References
1. Anderson, J. R. Cognitive Psychology and Its Implications. (4th
Ed.) W. H. Freeman, New York, NY, 1994.
2. Carroll, J. M., and Mack, R. L. Metaphor, computing systems, and
active learning. Int. J. of Man-Machine Studies, 22, 1, (1985),
39-57.
3. Hayes, J. R. The Complete Problem Solver. The Franklin Institute
Press, Philadelphia, PA, 1981.
4. Newell, A., and Simon, H. A. Human Problem Solving. Prentice-Hall,
Englewood Cliffs, NJ, 1972.
5. Norman, D. A. Learning and Memory. New York: W. H. Freeman, New
York, NY, 1982.
6. Solso R. L. Cognitive Psychology. (4th Ed.) Allyn and Bacon,
Needham Heights, MA, 1994.
