delivering cognitive psychology to hci: the problems of common language and of knowledge transfer

interacting with Computers ~018 no 7 (1996) 89-111

Delivering cognitive psychology to HCI: the problems of common language and

of knowledge transfer

T.R.G. Green, S.P. Davies* and D.J. Gilmoret

Although cognitive psychology showed much initial promise, it has failed to make significant contributions to the study of human-computer interaction, which has led to a rejection of cognitivism in favour of situated action theory. The authors accept that the critique has much to offer, but reject the outright abandoning of cognitivism. Cognitive psychology needs a common language in which to describe interaction between people and artifacts: two examples of research in progress are described, one focused on events, the other on representations and the relationship between the information display and the conceptual model. Cognitive psychology also needs a better delivery method than the traditional research paper, and the idea is proposed of a vocabulary of ‘cognitive dimensions’, terms which can be meaningfully used by non-specialists (who will recognise familiar but uncrystallised concepts) and which can be used as indexes to the professional literature. These two components form a proposal for improving the effectiveness of cognitive psychology. The paper ends with the hope that mainstream cognitive psychology will broaden its area of enquiry.

There has been considerable debate concerning the extent to which cognitive psychology can make useful contributions to the field of human-computer interaction (HCI) - Draper (1992) gives a useful commentary on it. This paper presents our position in the debate, which, in our opinion, has been fuelled by unrealistic assertions and claims, and by confusion between the role of a science and that of an engineering discipline. We present a more moderate position, asserting neither that cognitive psychology can supply everything that HCI needs, nor that cognitive psychology is irrelevant to HCI. We also outline how cognitive psychology can make a more useful contribution to HCI than it has achieved so far.

The original hope, as is well known, was that cognitive psychology had much to

MRC Applied Psychology Unit, 15 Chaucer Road, Cambridge CB2 2EF, UK. *Department of Psychology, University of Hull, HU6 7RX, UK (address for correspondence). lDepartment of Psychology, University of Nottingham, Nottingham NG7 2RD, UK

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offer HCI - possibly even that HCI could be identified with applied cognitive psychology. One statement of such a cognitivist position can be found in Moran’s ‘Psychology of the end-user’ (1981) and in the classic text by Card et al. (1983) presenting the ‘GOMS’ model. This stance might best be characterised as an attempt to provide conceptual frameworks, modelling and evaluation tools for the design and assessment of interactive Systems. At a later stage, the cognitivist camp was split by internal diszcnsions (e.g. the ‘hard science versus soft’ exchange between Newell and Card (1985) and Carroll and Campbell (1986)). At present, cognitivists are in state of defensiveness and introspection, summed up by various contributors to Carroll’s recent collection (1991). Various versions of ‘action theory’ are springing up and aspiring to the place of honour, apparently now vacated by cognitive psychology.

There are two strands to this debate. One strand concerns whether cognitive psychology has any material bearing on HCI at all. Contributions to the debate by, amongst others, Suchman (1987) have led to the argument that behaviour is determined by the context (social and organisational) and that analysing the context of technology is more valuable than worrying about cognitive processes. Increased emphasis on the design of collaborative work systems (CSCW) has further extended this argument, with the assumption that individual cognitive limitations are not a critical factor in systems whose function is to enhance social communication. These arguments have mainly served to polarise the debate between those who see cognitive psychology as central (Vera and Simon, 1993) and those who see it as largely irrelevant (Lave, 1988).

The other strand assumes that cognitive psychology is potentially relevant, but makes a debate of how to make it more effective. It seems to be agreed that cognitive psychology has not contributed greatly to the design of interactive artifacts, nor as much as might be expected to the discipline of HCI in general. Various examples in which psychology is conspicuous by its near absence are adduced by various authors. One example which the authors found particularly telling was the monograph by Thimbleby (1990), entitled ‘User interface design’, where the index included 38 entries under ‘programming’ whereas under ‘psychology’ there was only 1.

The disagreement between cognitivists is not about how far cognitive psychology is making a contribution, but about why the contribution is so small For instance, Card et al. (1983) influentially claimed that what cognitive psychology needed to do was to offer quantitative estimates of the effects of design decisions, a position later developed in more detail by Newell and Card (1985). Subsequent authors have taken the position that although cognitive psychology could in principle address the concerns of HCI it cannot do so at present because it is answering the wrong questions, and thus rejected Card et aZ.‘s stance.

In the first section of this paper we sketch our objections to the argument that cognitive psychology has no role to play in HCI; then present our position, namely that cognitive psychology can make a more useful contribution to HCI than it has achieved so far by both devoting more effort to theoretical constructions which unite the ‘outside’ world with the ‘inside’ world, and taking seriously the problem of transfer of knowledge. The following two sections amplify both these points. In the last part of the paper we present examples of research.

90 Interacting with Computers ~018 no 1 (1996)

Is cognitivism in HCI dead?

We are often told that ‘science’ constitutes an attempt to uncover the reality behind mere appearance. Consequently, the scientific endeavour has striven to partition phenomena into manageable units of study and to supply accounts of events which supersede the everyday explanations of ordinary people. Not surprisingly, cognitive approaches to HCI have mirrored this approach, suggesting a piecemeal accumulation of mini-theories that are intended to uncover and explain some aspect of interaction.

This characterisation of science is well-known, but is not without its critics. One major source of contention, particularly in the social sciences and more especially in psychology, is that the process of ‘doing science’ and striving to be ‘scientific’ has led to an unhealthy disregard for ecologically valid data. The attempt to partition phenomena into manageable units has led to accusations that some fields of psychology have become too insular, neglecting the reality of humans interacting with other social agents and, indeed, with the world at large. This critical stance now seems to be spilling over into HCI, with a number of recent, high-profile attacks on the basic methodological and theoretical assumptions implicit in cognitively-driven HCI (Landauer, 1991; Suchman, 1987).

The reductionist stance of cognitive psychology in general, and HCI in particular, has been particularly provocative. Lave (1988) argues that cognition should be studied in the context of ‘persons acting in a setting’, that is, in terms which stress cognition as observed in everyday practice. In this sense, cognition is seen as a complex social phenomenon, which is distributed over activity and cultural settings. Seen from such a perspective, it is claimed that the cognitive scientist’s reductionist view of cognition dislocates cognition from its context, and in doing so makes unreasonable assumptions about the uniformity of culture and situation in order to facilitate generalisations outside the laboratory. More recently, Bannon and Badker (1991) extend the general thesis of Lave’s work to a position which effectively rules out, in principle, attempts to map out an understanding of interaction in cognitive terms.

Such views have two major consequences. Firstly, abstraction is largely ruled out, since all activity is mediated by situations which are likely to be largely unique. Secondly, and perhaps following from the first, interest becomes much more directed towards how things appear. Lave’s work suggests that phenomena should be considered as having meaning only with regard to how actors participating in a particular activity interpret those phenomena. Hence, there is no ‘essential structure’ lying behind cognition and action: each manifestation of a particular phenomenon will be tied to a unique social context or setting.

Laboratory-based studies, in their neglect of setting, would thus be unable to provide any real insight into cognition as it happens. Such a fierce critique of the cognitive paradigm challenges the fundamental premises and the basic methodological adequacy of the cognitivist approach, while suggesting a much wider view of cognition as distributed between social agents and artifacts. This has led to calls for more ecologically-motivated studies of artifact use (e.g. Norman, 1991).

We find ourselves strongly sympathetic to the desire for a better ecological

Green. Davies and Gilmore 91

grounding, and to the view that ‘meaning’ is not independent of the actor. Indeed, we can point to cases where we have argued exactly that position in the midst of papers which were cognitivist to the bone: for instance, the theory of ‘task-action grammar’ (Payne and Green, 1986), which presents a theory of interface consistency, explicitly acknowledges that it is the user’s (i.e. actor’s) view of the task that determines perceived consistency. Green et ~2. (1988) give an example of how one user, construing the world in one way, might find an interface consistent, while another user, putting a different construction on the world, might find the same interface inconsistent. Payne and Green (1989) actually demonstrated experimentally that apparent consistency was determined by the nature of the perceived task, as constructed by the user.

In short, we see no conflict in the calI for a broader understanding of cognition. But we find it impossible to accept the thorough-going rejection of cognitivist method. The anti-cognitivist position seems to present new problems of its own, For example, Lave’s call for studies of socially situated cognition raises important concerns about the scientific adequacy of her prescriptions: there are questions both about the generalisability of the studies she reports, and more proble- matically, about the methodological adequacy of these studies in relation to typical scientific criteria. Moreover, a fact laced with some irony, her view falls into the reductionist trap which it is so keen to avoid by presenting an approach centred upon the supremacy and determining power of the environment. However, we argue that this leads to a situation which fails to do justice to learning and skilI acquisiton by over-determining the causal nature of environmental structures and cues.

Psychology, in trying to provide a mutual understanding of the interactions between the physical and the social sciences, is often attacked by both sides. In one case, physical reductionists provide explanations in terms of neurological or lower level structures, while those promoting a social explanation construct accounts based upon linguistic interpretations (for instance, Lave’s dialectical approach) and the influence of cultural settings (Suchman’s focus on ethno- methodology). Neither account considers the role of cognition, nor provides a framework from which we can view the interaction between cognition and its environment.

One problem, is that science allows us to generate a multiplicity of explanations, which may give rise to regularities at many different levels of description. One form of analysis does not rule out others, although in many cases such explanations may not be commensurable. Hence, while explanations of certain phenomena may diverge, it is nevertheless true that such explanations may continue to co-exist (Churchland, 1981). Our claim is that it is not difficult to construct cross-disciplinary criticisms where the standards and methods of one discipline are used to pick holes in another. However, such forms of analysis do not enable one to reject the entire basis of another discipline.

Our claim is that the analyses provided by Lave and by Suchman are cogent in their own terms, and provide valuable insights into the situated character of thought and action, however, they are paradoxically reductionist in tone in that they suggest that cognition is a uniquely social phenomena that is not amenable to the techniques and methods of cognitive psychology. It is clear that while such


analyses might constitute good sociology or anthropology, they challenge cognitivism from a position which is not commensurate with that paradigm. Our aim is to show how at least some aspects of situated analysis might be incorporated within a revisionist perspective which gives priority to the environmental determinants of thought and action while maintaining continuity with existing accounts emerging from the cognitive paradigm.

It should be noted at this point that it is not out intention to suggest that theories of situated activity might somehow be completely subsumed within a traditional symbolic account. This approach has recently been suggested by Vera and Simon (1993) who claim that:

“There is no need, contrary to what followers of SA (Situated Action) seem sometimes to claim, for cognitive psychology to adopt a whole new language and research agenda, breaking completely from traditional (symbolic) cognitive theories. SA is not a new approach to cognition, much less a new school of cognitive psychology. Whether particular forms of human behaviour meet the criteria of SA is an empirical question whose answer is certainly different for different behaviours. But whatever the answer, complex human behaviour, whether it has been labelled as ‘situated or not, can be and has been described and simulated effectively in physical symbol systems”. (Vera and Simon, 1993, p. 44).

The difficulty with this view, in common with many situated analyses, is that it falls into the reductivist trap that we describe above. Our claim is that the uniqueness of certain features of human behaviour may well be an emergent property of social interaction which is not, and probably cannot, be captured in purely symbolic accounts. Similarly, nor should situated accounts be seen to replace theories emerging from the cognitive perspective. Both have a role to play, but both differ fundamentally in terms of what they are able explain. Polemic calls for the replacement of one paradigmatic view of cognition with another would seem to achieve little. Indeed, it appears that by doing this one may paradoxically serve to reinforce the views promoted by the opposing camp by adopting the same misguided assumptions about the explanatory coherence of different disciplines.

Another problem relates to the potential for ambiguity in the attribution of meaning. For example, Davies and Caste11 (1992) showed that designers tend to describe their activity in ways that do not map well onto behavioural manifestations of the same activity. The designers claim they are doing one thing, and clearly enough see themselves as doing that, but their observable behaviour looks rather different. Davies and Caste11 argue that descriptions of behaviour in domains such as this are formed by educational and work practices, and that a level of analysis focusing on performance can provide a different interpretation from the interpretation proffered by the agents themselves. As in all disciplines there exist different levels of explanation, and there is no reason at all why one explanation should rule out others.

Situated accounts of cognition and HCI also raise difficulties about the use of philosophical frameworks out of their original context. The domain of enquiry of many existing frameworks has been explicitly concerned with understanding manifestations of language. Using them to support or otherwise justify the

Green, Davies and Gilmore 93

relevance of considering action and activity in context takes the frameworks to domains where the connection with language is rather tentative, to say the least.

Does ‘HCI’ really exist? A further aspect of the debate over the role of cognitive psychology in HCI is that the terms of the debate usually presuppose that a discipline called ‘human- computer interaction’ exists in its own right. This is something that needs to be examined more carefully. In the first place, Long and Dowell (1990) point out that ‘HCI’ encompasses three rather different strands: science, engineering, and craft. Each has its own goals, its own methods, and its own knowledge representations and repositories. Although there are some possibilities of contribution to the engineering strand, it is the science strand that is most likely to benefit from cognitive psychology. The craft strand, as we see it, is hardly likely to benefit from cognitive psychology at all. Conversely, while situated action theory has plenty to offer the craft strand, it is unlikely - as we have seen - that it will benefit the science strand.

Yet in the second place, even within the science strand we are hesitant about the claims of ‘HCI’ to be recognised as a coherent object of study. What is special about the presence of a computer? We would prefer to study instead the relationship between users and ‘information artifacts’, or as Norman has called them (1991) ‘cognitive artifacts’: timetables, notations, slide rules, musical instruments, and cookers are all examples in which a computer is not involved. Such a study can be called ‘cognitive ergonomics’, which as Green and Hoc (1991, p. 296) argued, “is not a discipline defined by its subject matter, like petroleum engineering. It is rather a composition of several disciplines in search of a common goal.” They contrast this view with the HCI view that a real discipline exists which is unique to computer-based artifacts.

Nevertheless, the most active area at present is that where a computer is involved, and we shall therefore concentrate on ‘so-called HCI’ during this paper.

The need to study interaction

In this and the following section we lay out the two parts of our proposal for improving the contributions of cognitive psychology to HCI. The first requirement is that more investigations be made of the structure of external artifacts and their internal representations, in accord with the line taken by Norman (1991). How does cognitive psychology stand on this issue at the moment? Paraphrasing or maybe parodying, the different perspectives by which artifacts can be approached, three major perspectives may be distinguished.

Systems view (focus on artifact) The systems view focuses on properties of systems which are good or bad and builds systems around this understanding. Concern is with demonstrable impact - the artifact works, therefore it is a good thing. Examples include the development of direct manipulation interfaces, the development of graphical programming languages, etc. This view sees HCI as a separate discipline, whose

94 Interacting with Computers vo2 8 no 1 (2996)

goal is the provision of better computing systems (or at least better interfaces to computing systems).

In many respects this is the application of psychology as ‘common-sense’, with the efforts of psychologists not appreciated since the useful knowledge is in the public domain already. The quality of the systems can be seen as a direct result of the quality of the common-sense psychology of the designer.

The contribution of the psychologist to this model is most commonly as an evaluator, simply employed to enable definitive answers to questions about which system is better. Holders of the system view will tend to believe that the raison d’he of HCI is to build better, smarter and more usable systems.

Psychological view According to this view, designs will improve through an understanding of the psychological processes which can be brought to bear on a computing problem. The concern is with guidelines, principles and rules about how people use computer systems. Examples of this approach would be KLM and GOMS (Card et al., 1983) and ‘training wheels’ for minimalist manuals (Carroll, 1990). All of this work addresses the knowledge or procedures that people use and ways to help them acquire them.

Insofar as this view directly addresses the design of the interface, it does so through providing guidelines about how people perform, or through the design of methods which impose consideration of psychological factors in the design process (e.g. John Long’s group’s work on Jackson Structured Design Methods, described by Walsh, 1989).

In this view HCI is simply an arena for applied cognitive psychology. In its most extreme form, it can be argued that guidelines derived through psychological research can be applied regardless of context or domain of application, since the guidelines apply to individual cognitive processes, and not to the system or artifact. Thus the model information processor used in KLM and GOMS is an architectural model, which applied equally to all information which might be processed’.

Interactive view The interactive view recognises that a person brings some standard cognitive processes to any interaction with an artifact, but that the way these processes are used is affected by the nature of the artifact. Whereas traditional cognitive psychology tends to perceive mental processing as ‘input-processing-output’, this interactive view allows for the possibility that output and further input may occur during the processing.

For cognitive psychology to be successfully applied to HCI (and maybe to other domains, too) it is necessary to both understand these standard cognitive processes, and to understand how external and dispositional factors, including

‘Note that it is this form of cognitivism which is being aggressively challenged by Suchman, Lave, et al. Many of their criticisms do not apply to the application of cognitive psychology through an interactive perspective.


Time

Input & Processing

Input Processing

Figure 1. Usual view of cognitive processing (above) needs to be augmented by an interactive view (below)

organisational issues (Clegg, 1994; Hutchins, 1995), might influence the particular configuration/instantiation of these standard processes.

The need for knowledge transfer

As the second leg of our proposals for improving the contributions of cognitive psychology to HCI, we suggest that the routes for knowledge transfer be more explicitly considered. Disappointment with slow progress (and over-selling of the original claims for cognitivism) has led many members of the HCI community to a too-ready rejection. Thus, Landauer (1991, p. 60) considering the contribution of cognitive psychology to the design of ‘humanly useful and usable systems’ claims that “for the most part, useful theory is impossible” and that “where it is possible, the role of theory will be constrained and modest”. Diaper (1989) claims that psychology has “no useful facts”. This in-principle rejection of psychology’s possibility (by researchers who have themselves made contributions to psychology) comes from the failure of psychology to make noticeable impact on the activity of HCI. Yet it is hard to imagine how progress could be anything but slow. The route from research to practice is frequently lengthy and indirect.

Problems of knowledge transfer: Here are some particular problems with the route from research to practice:

Infrastructure: The structure of academic cognitive psychology, at least within the Anglo-Saxon world, conflicts with teamwork directed at applied goals. HCI


designers and cognitive psychologists are rewarded in different ways and for different achievements; they publicise their work through different routes; and they have different ideas about ‘reading the literature’ or ‘knowing what’s been built’.

The reward system in cognitive psychology encourages large numbers of isolated papers by individual authors, rather than teamwork towards a common goal. Moreover, rewards are for original research rather than for presenting someone else’s work in a comprehensible form, which will do little to advance a career.

StyZee: The stylistics of cognitive psychology set up a standard, institutionally- accepted framework within which any experimental paper must sit, in which the machinery of hypothesis-testing is employed to deliver a significance value. This approach is neither comprehensible nor rewarding to the practitioner, who is not unreasonably impatient when, like using a cannon to shoot a squirrel, the apparatus of experimental design is trained on a small, topical, urgent issue, and six pages of tables and charts are required to tell the reader some small fact that was intuitively obvious already.

Content: Cognitive psychologists have focused extensively on the internal processes of cognition. They have little to say about the importance of external artifacts and representations, save at the perceptual level. This makes laboratory results hard to generalise to a wider context, and indeed makes much of the literature of cognitive psychology more or less useless to the practitioner unless he or she is willing to become a psychological theoretician. As Carroll (1991, p. 8) puts, it, “psychology has traditionally divided tasks into small components, instead of asking directly how people accomplish their tasks”. Norman (1991) has developed this thesis at some length.

The position we adopt in this paper is that cognitive psychology cannot replace HCI designers, but it can help them; specifically, it can help them understand how choices of external representations can influence internal processes and thereby influence how artifacts are used. To do so, cognitive psychology must develop a means of disseminating knowledge in a more usable style.

Transfer of cognitive psychology: organizational models and social mechanisms

How does knowledge get transferred from one discipline to another? A number of patterns can be observed. The problem is that none of these is suitable for our purposes.

Osmosis: The simplest model presents scientists as dispassionate and impartial searchers for truth, who carefully search the literature as often as possible and attempt to synthesise all findings relevant to their research topic. If this model were correct, the steady accumulation of relevant research results would somehow reach and influence everyone appropriate. Computer scientists and software engineers who were creating languages, environments, and applications would start to incorporate more and more research results from the cognitive literature. Alas: this model is a fairy story.


Jewel in fhe mud: Depressingly, in a more realistic model a single research result sticks out from one culture (e.g. cognitive psychology) and is cited, well or badly, by many researchers in other cultures (e.g. in HCI). Other results are disregarded, like so much mud. The best-known ‘jewel’ in software psychology is Miller’s ‘magical number 7, plus or minus 2’ (Miller, 1956), a classic of experimental psychology in the information-processing paradigm, destined to be widely used and misused in support of all sorts of diverse suggestions about software design (DeMarco, 1979; Coad and Yourdon, 1990). Sometimes it was clear that researchers had not understood Miller’s paper, probably had not even read it, and were simply copying a fashion.

New wave: In a pattern of change familiar to us all, prophets and disciples of a revolutionary new approach overtake existing practice, abruptly and energeti- cally sweeping aside the insights of a previous era, as ‘tired and out-of-date’. Cognitive psychology itself was a new wave once; today, the proponents of situated action make a new wave trying to sweep away cognitivism.

Curriculum design: It has, of course, been proposed that students of HCI (and other kinds of design, come to that) should be taught elementary cognitive psychology. Indeed,some excellent attempts have been made to provide suitable materials (e.g. Monk, 1984). Such a proposal sounds better in an academic laboratory than at the ‘chalk face’. Computer science students, who make up the bulk of HCI practitioners-to-be, already find the curriculum daunting. It is unlikely that additions would be welcome. Moreover, the questions of style and content of research-based cognitive psychology remain unanswered.

Organisafional redesign: A ‘usability’ stage can be deliberately introduced into the design process. This method can only be used where the design process is fairly well-specified and self-conscious, but in practice many software engineering organisations do indeed use ‘design methodologies’. Walsh et al. (1989) give a good account of how one such methodology, Jackson Structured Design, was adapted to include an explicit user interface specification stage, and claim that they will be able to overcome the obvious problem that “for human factors and JSD to be successfully integrated, contributions from both need to be appropriately timed and structured’. These developments are very welcome, although we shall have to wait awhile to measure their success. But approaches which are limited to formalised design methodologies are not really likely to become widespread.

Towards deliverable research

In this section we shall illustrate our argument with three examples of research consciously aimed at crossing the gap between cognitive psychology and HCI. All three examples illustrate alternative methods of finding a ‘common framework of analysis’ in which both parties may work, the cognitive psychologist and the non- psychologist, where the focus of interest is on the interaction between the person and the artifact.

98 interacting with Computers ~018 no 1 (1996)

Our contention is that person-system research cannot be achieved merely by collating person-based research with artifact-based research. It is only feasible if a common language’ can be developed, in which relevant aspects of both the

person and the system can be expressed. This sounds impossibly difficult, but as our examples will show there are many different routes, with very different approaches. We make no apologies for drawing these examples from the work of ourselves and our colleagues; after all, one forms one’s research strategy because one believes it is the correct strategy!

The Barnard-Harrison interaction framework Our first example is a semi-formal analysis of interaction between a user and an artifact such as an automated bank teller (also known as a cash dispenser). To avoid the problems of focusing exclusively on either the person or the system, Barnard and Harrison (1992) have developed an ‘Interaction Framework. In their account:

“Theoretical models of user cognition or performance specify constraints and properties of sequences of cognitive states involved in the execution of a ‘task’. These models will tend to analyse the user’s goals and the mental operations called upon to achieve them. In contrast, formal models of the interactive behaviour of systems specify constraints and properties governing sequences of device states. . Taken in isolation. ‘the interaction’ is seen simply as an action by one party followed by a response by the other. Taken together, conjoint action of user and device forms the notion of an ‘interaction state’. An interaction trajectory is a sequence of such states.”

The problem of designing artefacts is then recast as a problem of designing an interactional space.

One of their examples is the following problem, familiar to all users of windowing environments: the user has opened two or more windows, and is typing in them alternately. There is an interruption or a pause for thought, during which the user stops typing. On resumption, the user starts trying to type, but tries to do so in the unselected, inactive window. The typing appears in the other window, causing a dislocation in the flow of activity.

Their method of analysis distinguishes between successive ‘interaction states’, called ISl, IS2 etc. In their ‘unselected window’ scenario, we suppose that the user has two open windows and is alternating between answering mail and word processing. The scenario starts at a point where the user is doing word processing (state ISl); then the user is called away from the workstation for a considerable period of time. The word processor window remains active: this is state IS2. Eventually the user returns and wants to log off the mail system. The user ‘types’ the appropriate command, but forgets to select the mail window, so the text appears in the word processor window - state IS3. The user repairs the mistake by deleting the inappropriate typing and selecting the correct window (IS4). Finally the user retypes the input to the intended window (IS5).

Barnard and Harrison call the repair episode an ‘interactional detour’. Such detours are quite likely to happen in the circumstances described. As the authors point out, the standard designs of windows do include signals to say which window is currently active, but evidently these episodes show that the intended


communication sometimes fails. The conventional wisdom of HCI says “ensure that the system state is displayed to the user”, but in the example given the system state is displayed to the user. What has gone wrong?

Although there may be many possible reasons for the problem, the authors highlight one particular possibility. They remark that current window border designs, used to signal whether the window is active, only acknowledge states of definite engagement or equally definite disengagement. An ‘active’ border signal is used on the window that the user is currently working with: its signal is little more than “you are interacting with the window you are currently interacting with”. The border thus provides only redundant information, and the user probably quickly learns to ignore it.

The interactional framework alerts us to another possibility, easily overlooked if we only consider the user’s viewpoint or the system’s viewpoint. This other possibility is a state of ‘possible disengagement’. Returning to the scenario, consider that the user pauses for thought. The mouse is stationary and no keys are depressed. After some delay, the interaction. state changes to ‘possible disengagement’: the user may still be reviewing information from the active window, but the ‘system’ has no evidence that the user is still there. In the ‘possible disengagement’ state, the window border changes to an new expressive signal designed to alert the user by catching the attention - any moving pattern would do. The pattern could be introduced gradually. If the user has indeed disengaged, the active pattern will direct attention to the active window when the user returns: if the user has not in fact disengaged, the gradually more active pattern will not disrupt mental activity, and will vanish instantly when the user resumes activity.

From this example, Barnard and Harrison suggest that explicit ‘marking of transitions’ is desirable - indeed, they lay out four ‘interactional principles’ - and they go on to describe in brief a laboratory study by Lee (1992) in which users were deliberately induced to make ‘unselected window’ errors; when active borders were used, unselected window errors fell by about 50%.

In later work, the interaction framework has been extended and has been applied to much larger and more complex problems, which have nevertheless the same character that the important topic of analysis is neither the user nor the hardware system, but the interaction between them. For example, Blandford et al. (in press) describe the problem of designing an ‘awareness server’:

“The design problem we focus on is based on work at Rank Xerox PARC and EuroPARC. A company has a monitor, speaker and camera set up in all the offices of its employees. People can make audio-visual (AV) connections between offices to see or talk to others. Various kinds of connection, such as sending a message or videophoning are possible. People are allowed to edit a separate list, for each type of connection, of people who have permission to access them. An Awareness Server . . . has been designed to display miniature video images ‘snapped’ from the cameras in the offices of people who subscribe to it. The video images are displayed together in a special window which can be opened whenever the user chooses. The system gives general awareness of what is going on rather than detailed information; this is intended to be useful to people who might want to make other kinds of connections, e.g. to let them know whether someone is likely to be disrupted by a videophone call.


Clicking on one of the video images opens a window in which information about the image owner is displayed; some of this information (e.g. name and address) is static, and some (e.g. the time when the image was snapped) is updated. The window has an ‘OK’ button and a ‘send mail’ button which opens a ready-made electronic mail text window for a message to the image owner.

The designer is planning to add ‘glance’ and ‘videophone’ connections to the Awareness Server. Glance gives a brief, finite, real-time video connection (without audio). Videophone is a medium-term AV connection that can be rejected by its target (just as a ‘phone call can be ignored). The designer is considering various possible ways of implementing this additional functionality.”

Space does not allow a discussion of how the interaction framework is applied to this design problem, for which we refer the reader to Blandford et al. Our point is that it illustrates an approach which avoids focusing on either the person or the system; the awareness server example demonstrates that it can be applied to complex, real design problems.

Relating conceptual model to system image Our second example describes a different attack on the same target, the creation of a formal description method. Here again the intention is to describe both parties in the same language, but whereas the Barnard-Harrison framework describes events, the next example describes representations.

A familiar problem in designing cognitive artifacts, as in other types of information display, is to devise a suitable representation for information that the user must read. This problem has been studied in various domains, among them graphical perception (e.g. Bennett and Flach, 1993) and human-machine interfaces for process control (e.g. Woods, 1991). A key issue is the mapping between the visual features and the semantic domain Green (1991) described a technique for applying an expanded version of entity-relationship modelling to the description of notational structure, and Green and Benyon (1992) showed that the same approach could be extended to capture the differences between two persons’ conceptual models - say, a designer’s and a user’s, or any other two people.

The technique, called ‘entity-relationship modelling for information artifacts” (ERMIA), adapts an analytical tool that is very well-understood in systems analysis and data modelling, the entity-relationship diagram. The essence of the data modelling version is that data can be described as entities, defined by attributes, and by relationships between entities. By reducing the level of detail about relationships to a minimum, many important structural aspects of a data model can be revealed. So, for example, a data model of people and car ownership might assert that every person was associated with a single name, but that a given name might be associated by more than one person, or even not associated with anyone; and that a car was also owned by someone, but that not everyone owned a car. It is common practice to use a visual representation of these data models. One representation (of many possible) is shown in Figure 2: the role of the visual representation is partly to clarify the structure, and partly to enforce the austere limitations in the power of the description language..(Working in a more powerful system, such as predicate calculus, would allow much more to be said but would reduce comprehensibility, it is argued.) In our example, it becomes quickly


Figure 2. The entity ‘Name’ may be associated with any number of instances of the entity ‘Person’; the open circle shows that a given Name may not be associated with any Person at all. A Person is always associated with just 1 Name. A Person may be associated with many Cars or with no Car, but a Car is always associated with just 1 Person. Open circles denote ‘optimal’ relationships, closed circles denote mandato y ones. 1 and M denote cardinality of relationships (1: M), etc)

apparent that our first data model was too simple: one person may be known by two names (e.g. one Western and one Eastern), a car may be jointly owned by several people, etc.

Green and Benyon (in press) show how this analysis may readily be applied to some of the recurrent themes of HCI. We use two of their examples as illustrations. In the first, we show how ERMIA can give an unambiguous description of the discrepancy between mental models held by different agents (whether different users, users and designer, or whoever else may be involved), and can do this in a formalism that makes a useful and effective common language. One of the few studies to compare naturalistic mental models was that of Payne (1991), who elicited models of the functioning of automatic teller machines (ATMs) from 16 subjects and showed how they affected people’s behaviour in using the machines. He reported:

“A striking observation about the mental models of 514 and 515 . . . is how different they are. One subject [S14] believes that a great deal of information is stored on the plastic card, and that this information is updated when the machine is used. The other subject [S15] believes that the only information on the card is the user’s PIN (Personal Identification Number). The first user believes that each bank machine is ‘intelligent’ . . . The second believes that each bank machine is a ‘dumb’ terminal to a central computer, where all the records are stored and all the computations are performed. . . . Such variety is rampant in the data.” (p. 12)

Like any natural-language description of this type of material, Payne’s description has to find a compromise between precision and tedious verbosity. Figure 3 shows how the structural aspects of these different beliefs can be represented in ERMIA. Because ERMIA presents a clear view of the different models, it could be used as part of the process of reasoning about the revelation of models. If we have a designer’s model that the designer wishes to reveal, he or she can look at the model of the interface and see to what extent the ‘intended model shows up. Similarly one can gather different user views, in the manner of Payne’s work, and compare them to the designer’s view, making the models and their possible differences explicit through ERh4IA.

In our second example, we turn to another important topic of HCI, the search for information. Card et al. (1994) write

“In a world of abundant information, but scarce time, the fundamental information access task is not finding information, but the optimal use of a person’s scarce time in gaining information.”


Subject 14: network of interconnected intelligent machines, everything stored on the card

Network 1 m

Subject 15: central machine with local ‘dumb’ clients, nothing on the card except the PIN

Figure 3. Comparison of two mental models of ATMs described by Payne (2991)

Card et a2. defined what they call the ‘cost of knowledge’, i.e. the time required for the user to navigate through an information display to a given target, and investigated the ‘cost of knowledge characteristic function’, or the amount of knowledge available as a function of user effort. Their example contrasted a standard week-at-a-glance calendar with a ‘Spiral Calendar’, in which successive mouse clicks opened a new era, millennium, century, decade, year, month, week, and day.

An ERMIA representation of the spiral calendar is shown in Figure 4. Each entity is a sorted list, and therefore the experienced user can use a binary search method. The shape of the cost-of-knowledge characteristic function is therefore almost exactly logarithmic. Table 1 shows the number of days accessible for a given number of search steps in the Spiral Calendar and in the conventional week- at-a-glance design, the ‘flat’ calendar.

It is instructive to compare the ERMIA analysis with the analysis used by Card et aZ. (1994), who arrive at a similar prediction by a different route. Their method has the advantage of predicting actual times for users to achieve given goals, which ERMIA, by its withdrawal from surface representations, cannot do. Instead of modelling the structure of the information, they modelled the user’s method of access, using GOMS (Card et al., 1983). GOMS models are presented in


Table 1. The number of days accessible in a given number of steps, starting from a given day, in the two types of calendar

Steps Flat spiral

1 7 7 Week 2 14 30 Month 3 21 365 Year 4 28 3650 Decade 5 35 36500 Century 6 42 365000 Millennium 7 49 3650000 Era

considerable detail (Table 2) which allows the authors to obtain precise predictions of timings. Unlike the ERMIA approach, in which predictions are purely symbolic and are derived from the structure model, Card et al. arrive at their prediction by considering the time taken for individual actions, which allows them to include the time taken for reading the display (‘GET-YEAR’) and also allows them to take into consideration such factors as the size of the target buttons for the ‘POINT-TO’ action.

The ERMIA and GOMS approaches do not yield fundamentally different results, but they operate in fundamentally different domains. ERMIA makes explicit the information structure; GOMS makes use of the information structure, but in a purely implicit way. So the approaches are complementary, not antagonistic, and will probably be useful for different purposes and at different stages of design. We would anticipate that analyses at ERMIA’s level of generality are most useful during early design, while GOMS-like analyses that are sufficiently detailed to yield close time predictions are most useful during later stages of design.

More germane to our present point, however, is the observation that whereas GOMS requires the attentions of an HCI expert, the relatively unsophisticated ERMIA analysis is couched in a language that is more likely to be already familiar to the designer - and if it is not already familiar, it is simple to learn.

Narrow-bandwidth communication channel: the ‘cognitive dimensions’ framework Lastly we describe an approach designed specifically to transmit cognitive psychology to non-specialists. The purpose of this approach is to change the level

Figure 4. An ERh4ZA representation of the structure of the spiral calendar. The arrow symbol indicates that entities of the type are sorted by a given attribute; thus ‘Era’ is sorted by ‘Era number’ (abbreviated E#)


Table 2. GOMS method for locating the date 23 November, 1719 using the Spiral Calendar (omitting unnecessary details about starting the task)

GOAL : ACCESS-DAY-CALENDAR GET-YEAR GOAL : SELECT-CENTURY (170%)’ . ’

if necessary

POINT-TO (Century = 1700-1790s) + Century-display

GET-YEAR GOAL : SELECT-DECADE (1710;)’ ’ ’ ’ ’

if necessary

POINT-TO (1710-1719) + Decade-display

GET-YEAR . ’ ’ ’ ’ ’

if necessary GOAL: SELECT-YEAR (1719)

POINT-TO (1719) + Year-display

GET-YEAR GOAL : SELECT-MONTH (November)’

if necessary

+ Month-display GET-YEAR

’ * ’ ’ ’ ’ if necessary

GOAL : SELECT-WEEK ([??I) POINT-TO (23)

+ Week-display GET-YEAR

’ ’ ’ ’ ’ ’ if necessary

GOAL: SELECT-DAY [23] POINT-TO (23)

+ Day-display

GET-YEAR ascertains the target year. The ‘if necessary’ directives allow the user to skip selecting a century if the display already happens to show the required century. GOAL sets a sub-goal which is achieved by the POINT-TO operator

of discourse amongst choosers and users of applications and amongst designers. The non- specialist understanding of any discipline requires a vocabulary on which to hang familiar but ill-formed concepts: the germ theory of disease, Mendelian genetics, Newtonian mechanics - these are all cases where everyday language has picked terms from the specialists and used them to clarify everyday discourse. We need to make this happen in HCI. All too frequently the level of discourse in evaluating software, even between highly experienced users, is one in which important concepts are struggling for expression.

Figure 5 illustrates a fragment of dialogue between users, in which at least three concepts are thrashing about. The concepts involved are not difficult, but they have not been systematically brought together and named, let alone had their inter-relationships exposed.

The cognitive dimensions framework (Green, 1989; Gilmore, 1991) is a preliminary attempt to define a useful and usable set of concepts which can be introduced into assessments and descriptions of cognitive artifacts. The main focus has been on artifacts which are used to create information structures, such as word processors, spreadsheets, and software engineering environments, and it has been assumed that the typical user may be performing in a way that includes


A: ALL files in the book should be identical in everything except body pages. Master pages, paragraph formats, rejerences pages, should be the same.

B: Framemarker does provide this . . . File + Use Formats allows you to copy all or some formatting categories to all or some files in the book.

A: Grrrmrrr. . . . . . . . . Oh People Oj Little Imagination ! ! ! ! ! ! !

Sure, I can a!o this . . . manually, every time I change a rejerence page, master page, or paragraph format . . .

What I was talking about was some mechanism that automatically detected when I had made such a change (. . .) Or better yet, putting all of these pages in a central database for the entire book . . . . . .

C: There is an argument against basing one paragraph style on another, a method several systems use. A change in a parent style may cause unexpected problems among the children. I have had some unpleasant surprises of this sort in Microsoft Word.

Figure 5. Verbatim transcriptfrom an electronic mail discussion oja document processor, FrameMaker (trademark of Frame Technology Corporation). The three ‘speakers’ are discussing viscosity, conquerable by increased use ojabstractions at the cost of increases in hid&n dependencies, but because they have no terms directly &noting these concepts and the trade-offs, they have to re-create the concepts and explain them to each other, even though the ideas are no doubt quite familiar to them all

some degree of opportunistic behaviour. Under these conditions, it is necessary for the information structure to permit rapid access to any part, to allow parts to be refashioned readily (since that is one of the key aspects of opportunistic planning), to allow the purpose of any single component to be rapidly identified, and so on.

Moreover, these methods are time-consuming, not to say time-ravenous; so they cannot be used widely. Finally, most methods focus on downstream evaluation, but by the time the product has been designed in detail it is too late to change anything. The answer, we believe, is to adopt a higher-level framework of concepts. Detailed findings can be translated into these concepts; problems of design can draw on the concepts, not for solutions but for guidance. Such a framework is not supposed to be a collection of new concepts, but an orderly synthesis of ideas. As we shall argue below, by explicitly formulating and naming concepts they can be given added force. To evaluate a visual programming language (VPL), we must consider four factors (at least):

. the programming language or notation; l the programming environment; l the type of task;


l the typical user’s experience, knowledge, style, and other individual characteristics.

The cognitive dimensions framework applies to the first two. It is critical to consider both the notational structure and the support

environment: to evaluate the system, not just one component. The notational structure is the skeleton of the programming language, its internal dependencies, its order constraints, its verbosity or succinctness, but not its content. It is relatively easy to isolate these aspects and consider their virtues. The support environment controls what the user can do and see: this can be elusive. In fact, one can readily forget that the environment, as such, exists at all, except when some smart features are supplied; nevertheless, whether one is working on a programmer’s workbench or with pen and paper, or even in one’s head, one is working in some kind of environment, which provides its own operations for storing, viewing and changing representations of the program (Davies, 1993).

Designing and exploring requires creation and modification, therefore recomprehension of material that has already been created. To some extent Norman’s famous ‘seven stages of user activity encompass these requirements. But modification of an existing design often also requires abstraction and thinking ahead (for example global search-and-replace in a word processor is a form of abstraction), not catered for in the seven stages.

Only a flavour of the cognitive dimensions can be given here. Some of them are very straightforward, such as ‘viscosity: this denotes resistance to local change. Viscosity, like the other dimensions, is a property of the system in use, determined by the notation or information structure and by the operations available. Thus, technical prose with numbered sections may be viscous or fluid, depending on whether there are tools to renumber sections when new ones are added. Although these ideas are simple and familiar, they have not received standard names, leading to at best time-wasting definitions, at worst confusion, in discussion of designs. Figure 5 illustrates the problems: Speaker A is talking of using abstractions to counter viscosity. Speaker B missed the point because there is no clearly recognised term ‘viscosity’: the problem has to be spelt out.

If the terms were well-recognised, the discussion would automatically move onto the trade-offs inherent in taking certain solutions. For instance, creating abstraction mechanisms is a very common approach to reduce viscosity, but it has its own drawbacks. Speaker C is warning against one of the frequent drawbacks, hidden dependencies.

Clearly, the choice of cognitive dimensions has to be determined by several factors: they must be quickly meaningful to non-specialists; they must be supported by acceptable evidence; they must relate to how users actually behave (e.g. it needs to be shown that high viscosity lowers performance, and encourages a shift to alternative strategies); and together, they must capture most of the important aspects of structure and structural operations.

Some of the dimensions are recalcitrant. One such is role-expressiveness, the degree to which the purpose and interconnectedness of a structural component may be recognised readily. There are many examples in many domains: Petre and Green (1992) document the extensive use by electronics designers of a ‘secondary


notation’, superimposed on the formal notation, to convey aspects of domain relevance which were not conveyed by the formal notation; in a different vein, Saarilouma and Sajaniemi (1991) show that the comprehension of spreadsheets is considerably affected by whether the signals given by the layout conform to the true structure of the spreadsheet. There is currently no body of theory of structure- parsing applicable to artificial notations (programming languages, flowcharts, musical notation, etc) that comes anywhere near approaching the maturity of psycholinguistic theories of natural language parsing. In its absence, this branch is handicapped. Nevertheless, some progress can be made towards theoretical analyses: for example, Green and Boming (1990) showed that a psycholinguistic theory of natural language parsing could be extended to provide predictions of comparative difficulty of parsing equivalent structures in two designs of programming language, able to include the contribution of typographical layout within the uniform model of feature-based parsing.

The cognitive dimensions are naive and unsophisticated in terms of contemporary user models. That is what allows them to be comprehensible to non-specialists. Green and Petre (in press) report a detailed investigation into usability aspects of visual programming environments in terms meant to be comprehensible to computer scientists and software designers; confirmation that the framework can be used by computer scientists comes from papers by Modugno et uI. (1994) and Yang et al. (1995) in which those authors successfully applied the framework to programming environments they were designing.

The framework of cognitive dimensions is far from complete, but the aim is apparent: to supply a vocabulary of discourse in which non-specialists can find terse descriptions of important aspects, reminders not to overlook other aspects, and some hint of the trade-offs between different aspects; and which can be indexed into specialist research in each field. In this way, some of the traps of design may be avoided, especially traps to do with overlooking simple user needs for revision and for comprehensibility, and comparisons of design solutions may be made at a higher level of discourse. What is crucial to this objective is that the cognitive dimensions framework does not presuppose any special efforts in setting up alternative forms of organization, additions to the HCI training curriculum, or additional workload for designers in tracking and digesting research papers; all it is intended to do is to supply more powerful concepts in the everyday HCI vocabulary.

How does this constitute a ‘delivery’ of cognitive psychology? By making sure that the vocabulary includes terms for design considerations which have been shown relevant by cognitive psychology. Role-expressiveness is one such; others are exhibited in Green (1989).

Conclusions

The conclusion we reach is that despite the attacks on cognitivism in HCI, there are perfectly healthy lines of development for cognitive psychology. But in saying this several cautions must be sounded. First, the term ‘HCI’ is being used here as a term of convenience. The lines of development we have noted apply to interaction with alI types of cognitive artifact, not just to computer-based ones, and indeed we


see no reason to make a special case for the computer. Second, the critiques mounted by the action theorists are not without some force: accounts of ‘usability’ which deny the importance of distributed cognition and the role of the user in constructing a view of the world must be seen as no more than first approximations. Thirdly, the importance of different ‘narratives’ must be acknowledged, told possibly by the same actors for different purposes, conveying differing (and possibly incompatible) views of activity.

We have demonstrated three lines of development which all move away from the view that cognitive psychology serves to supply time-and-error estimates. Two of these lines are ventures in developing representations of interactive situations which apply equally to both partners, the person and the system. The third line is even less theoretically ambitious, seeking only to crystallise and expose concepts which many users (even if not HCI workers) already recognise, but which have not yet been presented in an organized way.

Of course, we are hardly the first to notice that there are problems in transferring cognitive psychology insights to HCI in a way that is compatible with organizational reality. We could cite many examples: one will serve, the ‘cognitive walkthrough’ technique developed by Lewis et ~2. (1990), in which a design is assessed by a small team who consider a typical user task, and record each choice that the user must make. For each choice, they then consider where the required knowledge for a correct choice might come from: from the display, the manual, general familiarity with such devices, domain knowledge, etc. This technique is evidently quite effective. But such a technique shows less promise of being able to index into the research literature than the ‘cognitive dimensions’ framework; also, it has far less chance to raise the overall level of discussion in choosing and evaluating artifacts. To make our platform succeed, better knowledge of many areas is needed. We have mentioned in passing the need for more understanding of the psychology of representations, and for theories of perception and parsing of artificial structures and notations. We end, therefore, with a hope that the

mainstream cognitive psychology will broaden its horizons in these, and other, directions.

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Received February 1995; accepted November 1995

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delivering cognitive psychology to hci: the problems of common language and of knowledge transfer

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