computer interaction

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Ergonomic perspectives on advances in humancomputer interaction K. D. EASON

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Department of Human Sciences , HUSAT Research Institute, Loughborough University of Technology , LE11 3TU, UK Published online: 06 Jul 2010.

To cite this article: K. D. EASON (1991) Ergonomic perspectives on advances in human-computer interaction, Ergonomics, 34:6, 721-741, DOI: 10.1080/00140139108967347 To link to this article: http://dx.doi.org/10.1080/00140139108967347

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Ergonomic perspectives on advances in human-computer interaction HUSAT Research Institute and Department of Human Sciences, Laughborough University of Technology, LE 1 I 3TU, UK

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Keywords: Human-computer interaction; Cognitive ergonomics; Socio-technical systems design; Human-machine interaction; Computer systems design processes; User participation.

Advances in human-computer interaction have stimulated the development of cognitive ergonomics to model interaction between two different infonnation processing systems. However, predicting human-computer systems performance also involves task, user, and environmental factors. This paper reviews developments relating to all of these factors at the individual human-computer interaction level, and at the socio-technical systems level. Thereafter it examines the problems of improving human-mmputer interaction in practice, and the need to embed human considerations in all forms and at all stages of computer systems design processes. 1. Introduction The information age is proceeding at such a pace that it is now rare to enter an office or a factory floor that does not boast glowing display screens. The development of the field of human-computer interaction has occurred at a similar rate, and international conferences dedicated to the topic such as INTERACT90 (Diaper et al. 1990) and CHIY90(Carrasco Chew and Whiteside 1990) attract large numbers of delegates. There is also a developing list of handbooks and textbooks (Helander 1988, Booth 1989, Sutcliffe 1988). A very large proportion of the population now interact with computers on a daily basis, and the search for ways of rendering complex information services accessible, usable, and acceptable to the non-specialist user assumes ever increasing importance. An obvious paradigm for human-computer interaction is the single user exchanging infonnation with a computer system. It is this focus for the subject that has given a major stimulus for the development of cognitive ergonomics and, because it deals with information processing in both animate and inanimate systems, the development of interdisciplinary cognitive science. Treating human-computer interaction as a form of conversation between different kinds of participants, each equipped with capabilities for storing, processing, and transmitting information, has placed many demands upon our understanding of the cognitive processes of human beings. However, we interact with computers not merely to exchange messages, but to engage in complex tasks in the red world. If we are to model task performance with computers, we need the classic ergonomic framework-human, machine, task, and environment-as depicted in figure 1. Broadening the subject in this way cames us beyond considerations of cognitive ergonomics into many aspects of physical ergonomics. Even this framework is insufficient to capture all of the variables that are critical to successful human-computer interaction in many applications. The individual user in an organizational context often shares a larger task with colleagues, and the computer system may serve many users simultaneo.usly. T o understand 00 14-01 3919 1 53.00 8 199 1 Taylor & Francis Ltd.

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human-computer task performance, we may also need a broader socio-technical systems framework (Eason 198 8). In this review we will examine advances at each of the levels shown in figure 1. We will begin by considering human-computer interaction as a form of conversation between two participants capable of processing information (level 1). We will then broaden the framework to examine user, task, and environmental factors which may affect task performance (level 2). The next stage will be to consider the factors which are important when human-computer interaction takes place within a sociotechnical systems framework (I eve1 3). The field of human-computer interaction is advancing both as a field of knowledge and as a practice discipline and, in the final part of the review, developments in the application domain will be examined.

2. Advances in fonns of interaction The general form of human-computer interaction has improved immensely in the past few years. T o interact with a computer a few years ago required the accurate typing of obscure commands exact to the position of every bracket and semi-colon, and often produced from the computer an array of equally obscure and often unreadable alphanumeric strings. Successful interaction meant considerable human adaptation to the unbending and unforgiving computer. Whilst computer specialists were willing and able to make this adaptation, the average 'man in the street' could not or would not. The computer industry has therefore sought more natural ways of interaction which are 'user friendly', are experienced as easy-to-use, and need little specialist training. One aim is direct manipulation, in which the natural actions of the user provide direct inputs to the computer. The best known manifestation of this approach is the WIMP interface (Windows, Icons, Mouse, and Pull-Down Menus) (Preece 1990). Using this form of interaction, guiding the mouse and selecting icons on the screen, means that many activities can be initiated without recourse to a keyboard or other forms of indirect interaction. Although these forms of interaction are much superior to their predecessors, there remains strong evidence that users experience many difficulties in making use of computer systems. The range of facilities, the power, and the speed of modern systems means that the user is effectively driving a very sophisticated machine. The evidence of field studies of computer use shows that as the power increases so the


Ergonomic perspectives on advances in HCI complexity of interaction increases, and most users react by limiting usage to a small part of the functionality (Eason 1984). Since technological advancement and the integration of widely differing systems will serve to bring a much larger range of services to the user in the future, the bottleneck of user interaction has to be resolved if much of this technological benefit is to be realized. In order to resolve these issues we need a much better understanding of the ways in which people process information in complex tasks, and in particular the way people work with complex infonnation services. It is this spur that has led to the rapid development in cognitive ergonomics, defined by Barber and Laws (1989) as dealing 'with mental work which is done in the context of, or with the aid of, or in interaction with machines, notably computers'. They arrive at this definition with much difidence since it is a newly emerging discipline with no clear boundaries. Communication requires actions at many levels, from physical movements to the manipulation of symbols. As a starting point, therefore, a number of authors have proposed models of the different levels of interaction necessary in human-computer interaction. Foley and van Dam (1982), for example, propose four levels which, from the physical to the abstract, are the lexical, syntactic, semantic, and conceptual levels. In a very influential framework, Moran (198 1) describes six levels which involve three components of interaction. The physical component is made up of device and spatial layout levels of interaction, whilst the communications component incorporates syntactic and interaction levels. The conceptual component includes both a semantic and a task level of interaction. Much of the research that has been undertaken can be characterized by the level of interaction that it addresses. At the device and spatial layout levels, for example, there have been many studies of the psycho-motor skills appropriate to computer interaction whilst at the semantic and task levels researchers have concentrated upon conceptual models and strategies. The. opportunities for using different psycho-motor skills to interact with a computer are gradually widening. The interaction may now involve not only alphanumeric characters but graphics, images, video, and sound. One of the exciting possibilities is speech processing; speech recognition by the computer as a means of input and speech synthesis as a means of output. Speech processing has been seen as the new panacea for human-computer interaction; what could be more natural and easy than speaking your instructions? Unfortunately, as with all universal panaceas, it turns out to have characteristics which render it inappropriate in many circumstances. As Gaver (1 989) points out, sound exists in time and the content of the message is easily forgotten. As speech technology advances, so it is becoming possible to identify the circumstances in which it is a very good option for interaction, when, for example, users need their 'bands free' for other operations. In other circumstances other forms of interaction, for example, by mouse or keyboard, may offer superior performance. Technological developments are now making even more dramatic forms of interaction a possibility, for example, the 'dataglove' (Fels and Hinton, 1989) enables the computer to follow every movement of the hand while helmets and spectacles provide the user with stereoscopic vision and the opportunity, by head and eye movement, to move around in a three-dimensional world (Milgram et al. 1990). By using the array of input and output capabilities now available, it is possible to create a 'virtual reality' (Mercurio and Erickson 1990), a computer simulation in which the user can move around which comes close to interacting with the real world. The growth of media for interaction and the range of devices available for each

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medium has led to many studies to determine optimum forms of interaction. There have been a number of studies to compare different means by which users can point at specific locations on a screen. Direct pointing devices, like touchscreens and light pens, are easier to use than indirect devices such as cursor controls. They are also superior in performance when the target location is large (Albert 1982, Haller et al. 1984). However, when the target Iocation is small the constraints on direct pointing devices, for example, the sensitivity of the touchscreen and the thickness of the finger, mean indirect pointing devices are more appropriate. These studies demonstrate a conclusion which win be repeated throughout this review; the optimum form of interaction is critically dependent upon characteristics of the task being undertaken and properties of the user. A challenge for ergonomics in the next decade will be to determine the mix of interaction facilities that is most appropriate for different task, user and environmental circumstances. At the conceptual level of interaction early research on cognitive processes sought to identify general rules for good quality human-computer dialogues. This research led to the identification of dialogue guidelines such as 'dialogues should be consistent' and 'systems should allow actions to be reversed' (Shneidennan 1987). Many authors have collected and classified these guidelines (Gaines and Shaw 1983, Smith and Mosier 1986, McMillan and Moran 1985, Maguire 1982). There are now numerous guidelines, and many of them appear to be in conflict. Attempts have been made to locate a few universal principles, based upon underlying cognitive processes, but those that have been proposed, for example, 'minimize the cognitive load on the user', are not easy to operationalize. One way out of the guideline impasse is to create conceptual models to predict human-computer interaction performance and to base these models on known principles of cognitive functioning (Lansdale 1985). An early model of this kind which has been very influential in subsequent model development is the GOMS model (the Goals, Operators, Methods, and Selection rules model) developed by Card er al. (1 980). This is a model which assumes a purposive and rational user and predicts the selection rules that should be used in task performance. Developments of the GOMS model have examined the cognitive issues at the different levels of interaction. In presenting his Command Language Grammar (CLG), for example, Moran (198 1) utilizes the top four levels of the six level framework described above. In this model the strategic actions of the user are determined at the task and semantic levels by the conceptual model the user holds of the task, and the way it maps onto the computer system. The syntactic and interaction levels define the more tactical actions of the user in using the 'language' embedded in the forms of intraction used in the specific computer system. This separation of levels has been used by other researchers to propose models that relate to specific levels. For example, TAG (Task-Action-Grammar) proposed by Payne and Green (1 986) is an attempt to map the task level to the action level of interaction. Another example is cognitive complexity theory (Kieras and Polson 1985), which uses the GOMS approach to analyse the complexity the user will have to manage to accomplish a particuIar task with a particular system. Despite the progress made with these models, there remains considerable unease that there are no good predictive theories of human-computer interaction pedbrmance. One of the problems is that the models tend to assume expert users who have well developed plans and a perfect knowledge of available actions. As such they are not good predictors of typical user behaviour. Another problem is that they


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address what Moran (1 983) has called the 'internal tasks', i.e., the computer-related tasks such as editing, saving, merging, searching, etc., and have little to say about the 'external task' which is the reason the user is interacting with the computer-writing a novel, designing a bridge, preparing an estimate etc. This distinction raises a broader problem for theories of human-computer interaction. Predicting human behaviour with computer systems in realistic settings has proved difficult because so many variables other than the complexity of the interaction have an influence; the knowledge of the user, the clarity of the task purpose, user motivation, the organizational context, e!c. Investigators such as Barnard and Hammond (1983) have found it impossible to establish ideal structures for dialogues, for example, noun-verb orders, because the preferred order is context dependent. This view is summarized by Suchman (1 987) who asserts that, for the user, action is 'situated'; determined by the variety of factors present in the situation rather than predetermined by the overall plan the user is executing. The user is here seen as a selforganizing resource who may have an overall purpose but is capable of reviewing and adjusting behaviour as a result of a variety of factors. This conclusion means that investigators of human-computer interaction have extended the range of enquiry to look more closely at user and task characteristics and the setting in which interaction is taking place. Before turning to these broader issues there is, however, another approach to consider. An attempt to establish the quality of human-computer interaction is the study of usability. The pragmatic aim of this approach is to identify the properties that ensure a system can be used effectively by its users. Initial work concentrated upon defining the properties which made the greatest impact upon usability. Shackel (1 986) lists as usability criteria the effectiveness, learnability, and flexibility of the system and the attitude to the user. Usability evaluation has become a major theme as laboratories have been developed in which video recordings can be made of subjects using new products, the results being used to establish the strengths and weaknesses of the system (Tyldesley 198 8). Evaluation studies have quickly demonstrated that systems are not universally usable; interaction is affected by many variables which means that the circumstances in which a system is intended to be usable need to be fully described. The Working Group developing usability standards in the International Standards Organization (Brooke er al. 1990) defines usability measures as 'the effectiveness, eficiency and satisfaction with which specified users can achieve specified goals in a particular environment', (p. 358). It is once again the task, user and environment which are defining variables. It is difficult to represent all of these variables in a laboratory, and there is now a move to undertake usability evaluations in field or 'contextual' settings (Whiteside et al. 1988). These attempts to model and understand human-computer interaction have provided many useful ways of representing and assessing different forms of interaction. When it comes to predicting performance, however, the conclusion is always the same. It cannot be done without reference to the task, user, and environmental context in which interaction takes place. We turn, therefore, to an examination of the way in which these variables influence interaction.

3. Task characteristics The objective of human-computer interaction is to enable people to improve their task performance. People use computer systems for a very wide range of tasks: to book an airline ticket, write a letter, design a bridge, search for a reference, do the

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K. D.Eason annual accounts, control a power station, etc. To achieve effective task performance across this range we need to be able to establish what information services are needed in each case, and the appropriate forms of interaction. We need methods of task analysis and classification and ways of establishing the forms of interaction which go with each type of task. Since human-computer task performance is a partnership, we also need to establish appropriate roles for each partner. In early systems the way the task was to be performed was built into the system and its form of interaction; for example, the order entry clerk used a form filling type of dialogue to enter the relevant data in a fixed sequence. This approach created relatively simple forms of interaction for the user because'there were few choices, but interaction was inflexible, which meant that the user had little discretion and when -the task varied the system couId not cope. Systems of this kind worked (but were not necessarily liked) in situations where the tasks were routine and highly structured. When this approach was used to support unstructured tasks such as problem-solving and decision-making it was not effective, causing Sackman (1968) to refer to 'computer tunnel vision', where systems force users into a narrow way of defining and performing tasks, and Ackoff (1968) to re-name systems for managers 'management mis-information systems*.These systems were rejected by their users because they were unable to cope with the user's model of the task and did not have the flexibility and adaptivity required to map varied and developing task requirements. Systems to serve unstructured tasks are now designed to shift the locus of control to the user. Modem systems provide a range of information handling resources that users can recruit to support their work on the task permitting them to control the way it is performed. It may also be possible for the user to configure or personalize these facilities so that they match the specific requirements of the task. The user's self-organizing capability and the ability to integrate many different factors in the situation to determine how to proceed can then be respected. When this works well the computer is a powerful tool which enhances human intellect. However, there remain many problems. Greater flexibility creates a more complex interface, which may make the system unusable to the non-specialist user. The access to facilities and modes of interaction may still not permit the user to work on the task in the most natural way. Systems developers may attempt to control, through the system, the way work is undertaken, to prescribe the one best way, and users may resist these constraints. The emergence of expert or knowledge-based systems has brought a new dimension to the question of control in the human-computer partnership. Building the knowledge of how to perform tasks into the computer system means that, in theory, even complex, judgemental tasks can be undertaken without human aid. The role of the human could be reduced to setting the parameters for the task and implementing the system. The most common example of the application of expert systems is medical diagnosis, where the system is given the patient's symptoms and can predict the most probable disease. Systems of this kind raise the allocation of function issue in an extreme form. There is both the question of whether the expert system can perform the task better than the human, and whether it should be allowed to perform the task. For example, computers making medical diagnosis decisions raises ethical and moral questions, as well as issues of responsibility. If the doctor proceeds on the basis of the diagnosis and it proves to be wrong, is the error the responsibility of the doctor, the system, or the designer of the system? Weizenbaum (1 976) provides a powerful argument that we should ask not only what the computer


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can do, but what it is desirable to permit it to do in the affairs of humans. It is noticeable that after a decade of development work there are very few expert systems in operation which taken the dominant role in task performance. Most applications that have proved acceptable and usable have employed the expert system as a support (Wyatt and Emerson 1990) or as an assistant (Eason et al. 1987), so that the human operator remains in control of task performance and fully responsible for its outcome. Successful human-computer interaction 'depends upon the degree to which the system and the user can agree on the characteristics of the task they are performing. The user can and will determine these characteristics in siiu, i.e., at the time of performing the task. The system, on the other hand, has to be developed tong before this event; and the assumptions it incorporates about the task are vital to subsequent performance. The forms of task analysis that are undertaken and the way the results of the analysis are incorporated in the systems development are therefore imperative. Many forms of task analysis for systems development have been proposed and, as Sutcliffe (1989) points out, a variety of methods are needed. at a number of different levels. Techniques for mapping the 'external' task (Moran 1983) are necessary to understand the context within which the task is undertaken, the variety it demonstrates, the essential role of the human operator, etc., and amongst the techniques available are the soft systems methodology (Checkland 1981) and open system task analysis {OSTA) proposed by Eason and Harker (1980). The development of any form of expert systems also requires forms of knowledge elicitation (Welbank 1990) to capture the knowledge from expert task perfomers that is then embedded in the system. There are also a number of techniques available for analysing the internal task of performing the activities necessary to use the system. These techniques also operate at different levels; hierarchical task analysis (Shepherd 198 5) and TAKD (Johnson et al. 1988) provide methods for analysing the overall organization of systems use, whilst command language grammar (Moran 1981) and its derivatives analyse the detailed levels of interaction. These techniques may generate a lot of information about the task to be supported, but they are not well co-ordinated with one another or with the process of systems development. A major problem is the tendency of systems developers to drift into a prescriptive mode; they design a system which makes assumptions about how the task will and should be undertaken. One of the most important research questions to be addressed is the conceptual basis for a systems development process which identifies the appropriate level of flexibility in the system to permit the user to exercise discretion in undertaking the task. Designing a system which restricts task performance may not be acceptable to users. Designing a system as a myriad of small scale tools which can be recruited by the user to provide flexible task performance may result in an unusable system. The search for optimum structure for acceptability and usability is a major challenge. One development which may, in part, resolve this problem is the creation of UIMS (User Interface Management Systems) (Pfaff 1985). These systems are based upon the assumption that it is possible to separate the dialogue between the user and the system from the functions the system is performing on behalf of the user. A UIMS provides the opportunity to give the user a consistent, usable form of interaction across a range of applications. In theory new applications can be added to allow the user to perform other tasks while the UIMS maintains control over the form of interaction. The main question over the development of UIMS is whether they can


actually provide the interface to a wide variety of applications and still sustain appropriate support for each type of task. As Grudin (1989) points out, users may want consistency because it permits transfer of training, but not at the expense of using a form of interation which is not fit for its purpose.

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4. User issues The initial classifications which drew attention to the implications for human-computer interaction of different kinds of users were fairly simple. Nonspecialist or n a h e users and those who made only part-time use of systems, for example, need more support from the system than expert or full-time users. Users who are experts in the task domain make more stringent demands on the way the system supports the tasks than those who do not know the task domain. It is obviously important for designers of systems to understand the characteristics of the intended users of the system, and most systems are designed for a range of users. Forms of user analysis are therefore necessary to complement task analysis to ensure the heterogeneous character of the user population is fully recognized. If nothing else, this will serve to prevent the designer using him or herself as the archetypal user to test the system. Studies of users, however, have demonstrated that sophisticated theories rather than simple classifications are necessary to explain user behaviour with computer systems. Many authors have proposed 'user models' to aid this endeavour. Unfortunately, as Young (1 983) points out, many different types of model have been proposed which has led to considerable confusion. There are user models of tasks, user models of systems, designer models of users, and 'embedded models' (Benyon and Murray 1988) which are models of users held in systems. There are also descriptive models of what users understand of the systems they use, and there are prescriptive models of what users would need to understand to make effective use of systems. One of the reasons for ineffective human-computer interaction is that users hold incomplete or inadequate models or representations of the system they are using which leads to errors and inappropriate actions (Young 198 1). User support has become a major topic in human-computer interaction as investigators have sought how best to help users develop the knowledge to make good use of systems. The traditional methods of training sessions, manuals, in-system explanations, etc. have been used to provide an accurate 'system image' (Norman 1986), but these techniques demand that the user tries to learn about systems before using them. Research shows, however, that it is quite common for users to learn by trial-and-error operation of the system. There are two ways of tackling the problem of a user who does not seek formal guidance. One way is to design the system so that it relies on the existing knowlege of the user. The other is to have an intelligent system that adapts to the behaviour of the user. In the first approach the problem is to detect relevant knowledge that is shared by all potential users. A solution to this problem which has attracted a lot of attention is the development of a metaphor for the system (Lakoff and Johnson 198 1). This is a simple and powerful representation of the system which is known to the user and which, when applied to the system, will give the user a good basis to guess what it does and how it operates. The best known example is the 'desktop' metaphor used for the Xerox Star and Apple Lisa interfaces (Cranfield Smith et al. 1982). The system interface operates as a user might operate when sitting at a desk; the screen contains icons which look like filing cabinets which can be opened to remove documents. In



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theory the user familiar with office work should be able to guess what to do to operate the system and may be able to make a lot of progress without recourse to a manual. The concept of a system metaphor has had a powerful effect upon interface design and the search for appropriate metaphors has been intensive. There are, however, difficulties. Halasz and Moran (1982), for example, note that the metaphor has to become increasingly complex to explain the complete system and the original metaphor may, in fact, be quite misleading with respect to many of the functions in a system. The other approach is to design an adaptive system which responds to the knowledge, habits, and needs of the individual user. This kind of system would recognize when the user wishes to use a function never previously employed and would provide full explanatory support in the dialogue presented for interaction. If the user requested a function used many times before, the system would present a faster and briefer form of interaction perhaps using processes and terms established by the user. To achieve this kind of effect, the system would need an embedded model of the user (Carroll 1987, Benyon and Murray 1988) which would be a quantitative model updated after each period of interaction. Such approaches have exciting possibilities; an intelligent 'front end', perhaps within a user interface management system, which controls the access for the user to a wide variety of applications and modifies the form of interaction to suit the knowledge and wishes of the user. An important issue is how the adaptation is made. One way is for the system to contain trigger points which operate after a number of user experiences of similar functions and automatically introduce a form of interaction appropriate for the more experienced user. Spall and Steele (1 990) report a system operating on this principle which failed to match the actual learning patterns of users. They concluded that learning processes were subject to many factors, and were not easily encapsulated in a quantitative model. An alternative is to leave the user to customize the system. Unfortunately this too would probably be ineffective, since users tend not to see opportunities to tailor systems to their needs (Jorgensen and Sayer 1990). MacLean et al. (1 990) report a study in which they succeeded in creating a culture where usertailoring of systems is the norm: it may be that the mix of an easy-to-tailor system and a user environment where there is support for tailoring is the direction to take. This points to two middle ground options. First, the 'embedded models' might recognize the opportunity for a change and ask the user to confirm whether the change was opportune (Brooke and Barrett 1 989). Second, a new breed of technician is beginning to appear in application settings who acts as a castomizer for groups of users. These people could examine the output from the quantitative user models on a regular basis and use it to suggest changes to the users or ensure users know how to make changes for themselves. In summary, studies of users have identified two kinds of variance, inter-user and intra-user variability. Inter-user variability has to be recognized in system specification and the design has to cope with the different kinds of user in the user population of the system. Intra-user variability invoIves tracking changes in user knowledge and behaviour over time and finding ways of supporting these changes and reducing the need for extra learning or effort on the part of the user. 5. Environmental factors Human-computer interaction takes place within a context and many factors in this context can influence the success of the interaction, which means they have to be


taken into account when the form of human-computer interaction is specified. A broad distinction between two kinds of contextual variable helps to summarize these factors, although it does not do justice to the complex interactions of variables that can occur. The distinction is between variables in the physical environment and those that relate to the social environment in which the user is operating. In the next section we shall consider the social environment in some detail; here we focus upon the physical environment. Many studies have examined the work stress associated with the use of visual dispIay terminals. A common finding is that full time users engaged in repetitive tasks show a high incidence of visual fatigue, back ache, and neck ache (Hunting et al. 1981). However, much controversy has surrounded claims that the use of visual display terminals may also lead to more serious health problems; skin rashes (Tjdnn 1984), cataracts (Zaret 1984), adverse pregnancy outcomes (McDonald el a!. 1984) and, more recently, repetitive strain injury (Rowe et a!. 1986). In each of these cases attempts to verify that there is a causal link between the health problem and the use of the technology have produced contradictory evidence. The link between use of the technology and serious, long term health problems has still to be substantiated but, because it is a matter of serious concern, remedial actions have already been formulated. These include screening users in risk categories (pregnant women, people with eye defects, etc.), designing jobs to avoid long term repetitive work in constrained postures (Grandjean 198 7), and ensuring regular rest pauses. There has also been a concerted attack on the design of the visual display workstation, the associated furniture, and the physical environment to reduce strain on the user. Many texts giving advice on the design of visual display work places in offices have now been produced, (see, for example, Cakir et a!. 1980). Despite the range of research, the problems of stress caused by the physical setting in which computers are used are, if anything, growing. The portability of modern computers means they are being used in many different settings, by people working from home, in vehicles, in hotels, etc. I t is rarely possible to control the environment in which these computers are used, which creates new design problems for the equipment. Davies (1 98 3), for example, describes the design of a portable terminal for electricity meter readers that had to be usable in darkness and bright sunlight. The use of visual displays in vehicles presents another difficult design problem because of possible interference with the driving task. 6. Hurnan-computer interaction in a so&-technical context The majority of computer applications are implemented in an organizational context where the task being undertaken by human-computer interaction is part of a larger task shared by staff of the organization. For many years studies have been undertaken of the impact of the computer on the individual user and the social structures within which users work. Many case studies and surveys (Buchanan and Boddy 1983, Long 1987) have shown the effects of computers on the numbers of jobs, the changes in the nature of jobs, the way people work together, and the way organizations control and co-ordinate complex tasks. There have been many controversies. Do computers lead to enriched or deskilied jobs? Is power more centralized or decentralized? Do communication patterns become more impersonal,. or are they enriched to create 'global villages'? Many of these debates have arrived at a similar conclusion; that the computer undoubtedly has an effect, but it is not



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predetermined. There is no 'technical determinism'. The form of the impact is shaped by the way the system is designed and implemented. Studies of these issues have been the province of industrial sociologists and management theorists, and, when considering the often adverse consequences of computer use for the human user, they have focused attention upon the goals and values of those developing computer systems. They have been critical of the psychologists and ergonomists who seek to optimize facets of human-computer interaction. Bjom-Andersen (1988) asks 'Are human factors human?' and questions the wisdom of studying, say, the optimum structure of a menu, when the way the computer dialogue controls task behaviour and deskills the job goes unchallenged. These studies have implications for the nature of human-computer interaction at two levels. Fim, at the individual job level they question once again the locus of control between the user and the system. Downing (1 980) concludes that developers and managers use systems as a means by which prescribed forms of task performance can be enforced. Users may be forced to follow precisely the 'form filling' structure of the dialogue and may be paced by the system. She suggests that the computer can become the white collar equivaient of the assembly line. Flexible systems, however, may give control to the user. Facilities such as a 'suspend' option can be used to freeze the system and enable the user to take a break or deal with an enquiry at any time. Such facilities can be very important in controlling one's own rhythm and pattern of work. Secondly, at the inter-personal level, the use of the computer system may have implications for relations with superiors and colleagues. Undeclared monitoring, for example, may produce a detailed account of user behaviour-without the knowledge of the user. The European Economic Community Directive on VDU Use (Stewart 1990) which seeks to enforce good practice in many areas of physical and cognitive ergonomics, expressly forbids undeclared monitoring because it is an invasion of privacy. It should be noted that the embedded models of adaptive systems are also a form of monitoring, and who has access to the data they contain may be a matter of serious concern to the user. A related issue is that the data bases users create and use, the messages they send etc., may be of a confidential nature, and users will only employ systems which are secure. This requirement makes passwords and other security techniquesa necessary part of the form of interaction, which all too often has the effect of making the system less usable to authorized and unauthorized users alike. There are therefore many ways, in which human-computer interaction has to be related to its social and organizational context. In recent years there has been an important coming together of social psychologists, computer scientists, and cognitive ergonomists to study this issue under the banner of CSCW (Computer Supported Cooperative Work; Bannon el al. (1988)). However, the starting point for this work is not the computer impact studies described above, but the problems and issues that surround co-operative working via electronic mail, electronic conferencing, video conferencing, and other techniques for engaging in shared work through the medium of the computer. The general aim of this work is to'create an electronic medium which would provide users with the range of media and the flexibility of interaction for the free exchange of information that characterizes a problem-solving group gathered together in face-to-face contact in one room. The objective, therefore, is to enable participants in different locations, perhaps working at different times, to contribute to a common problem space, to take turns in making contributions, to


K. D.Eason produce rough sketches of ideas as well as detailed proposals, and to respond informally to the ideas expressed by others, etc. The search for forms of interaction to support this kind of task opens a new chapter for human-computer interaction. It removes the largely implicit paradigm of one usedone terminal and a task restricted to one user, and replaces it with a shared task tackled by a socio-technical system; a collection of people in some kind of social structure using an array of loosely or tightly coupled technological tools for processing and sharing information. Exciting as these developments may be, they seem curiously out of gear with the issues raised by most computer impact studies. The main difference appears to be that CSCW exponents are studying the kinds of group communications that occur between relative equals, particuIarly in academic and research environments. In these situations matters of control and co-ordination of activities towards the common goal are matters of local negotiation amongst members of the group. The impact studies, by contrast, have been undertaken in typical industrial and commercial organizations in which collective tasks are undertaken by staff in highly differentiated roles; managers give instructions to subordinates, specialists take responsibility for specific aspects of tasks, recommendations go to authorized decision makers, etc. It is unlikely that the forms of interaction emerging from CSCW studies will be successful in these settings until the systems can recognize and support the specific roles of each contributor. Achieving this objective requires fonns of organizational analysis which can identify the information implications of the rights, obligations, and needs of each role, as well as the characteristics of the overall task that they share (Harker et 41. t990a). 7. From theory to practice Studies of human-computer interaction have created many findings and theories that have practical implications for the design of computer-based systems. Many of the studies have been undertaken specifically to inform the design process. Indeed one of the current debates, reminiscent of debates about the nature of ergonomics, is whether human-computer interaction is a scientific discipline or an engineering design discipline. Some take the view that it is both a theoretical branch of cognitive science and an engineering discipline (Norman 1986, Long and Dowell 1989). Others, for example, Whiteside and Wixon (1987) argue that it is a broad-based engineering discipline which requires inputs from cognitive science and from many other bodies of knowIedge that contribute to the contextual setting of interaction. Long and Dowel1 (1989) point out that current practice in the design of human-computer interaction is more correctly described as a 'craft discipline', in which practitioners rely heavily upon intuition and untested assumptions, than an 'engineering discipline' which relies upon well-founded, generally applicable engineering principles. In this section we will review contributions to the design of human-computer interaction to examine the kind of process necessary for successful interaction. An important point of departure for the study of human-computer interaction design is the investigation of how systems are currently designed. A number of studies (Rossen el 41. 1987, Harker el a/. 1990b) have shown that there is no systematic attention to human issues in present day design processes, which tend to be dominated by .technical and economic considerations. There is, however, a growing recognition that system success depends upon usability and acceptability, so in many design processes some effort is made to put these topics on the development



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agenda. As a result there have been attempts to develop practical design contributions from the topics considered in the foregoing sections and to test these contributions in commercial design settings. One approach to providing these design contributions is to package findings, principles, and theories about good human-computer interaction practice into manuals which designers can employ to guide their work. Very popular manuals exist for the design of the software interface, e.g., Shneidennan 1987, and the hardware interface and workstation, e.g., Cakir et al. 1980. The difficulties designers experience in using manuals of this kind have been documented by Mosier and Smith (1 986) and Eason and Harker (1 991). The guidance is often specific to a situation that does not pertain in the design process in question, or is so general that the designer does not know how to relate it to the design problem. The assumption behind many attempts to apply research findings in human-computer interaction' is that knowledge can be directly applied to practice. Kiein and Eason (199 1) call this the 'knowledge-into-use' paradigm for application and, following a survey of a wide variety of case studies of the utilization of human and social sciences, conclude that direct transfer is very rare. Human behaviour is contingent upon so many factors that anyone dealing with a specific situation has to internalize relevant principles and findings and consider their relative significance to the current situation in order to amve at an appropriate solution. This recognition has led to a greater emphasis upon human factor contributions to the process of design. The aim is to establish techniques and tools which aid the exploration of relevant human issues as the design process proceeds. In this approach research findings are used to establish the goals for human-computer interaction (functionality, usability, acceptability, etc.) and to input relevant findings into the processes of achieving these goals. Focusing attention upon the design process and how to support it has led to four important questions. Where in the design process should human factors issues be addressed? Can existing design processes be user centred? What is the role of the urer in the design process? What are the human factor issues associated with the different kinds of design process that lead to the system sitting on the user's desk? Each of these questions will now be addressed. The conventional view of the systems design process is that it is a linear sequence of activities (a 'waterfall') in which each stage is completed before the next begins. In general the sequence proceeds from systems analysis, through conceptual and physical design, to implementation and application. The form of interaction is established in the physical design stage and it might be assumed that this would be the stage when human factors issues are considered. However, if the system specification is inadequate, good physical design may not rectify the problem. In fact, if the system is to serve the full needs of the user population, human issues have to be addressed at every stage of the design process. There now exist methods, many of them computer-based, to support user-centred approaches to each phase of design. The User Skills and Task Match (USTM)set of methods, for example, supports the task and user analysis aspects of systems analysis leading to the establishment of criteria for functionality and usability (Hutt et a/. 1987). Early evaluation of prototype systems in usability laboratories (Brooke 1986) and in contextual studies (Whiteside et al. 1988) provide techniques for assessing whether physical designs meet established usability criteria. A good system can still fail if it does not match the organizational setting and other techniques, for example the ETHICS methodology

.


(Mumford 1983) provides procedures for the socio-technical systems design in the applications context. Human issues have, therefore, to be addressed at all stages of design. If they are not, there is a danger that where efforts are made they will be wasted. This analysis has led to a number of attempts to provide human factor tools and methods for the entire design life cycle. In some cases these methods provide an integrated framework for design in a particular context; for example, the user-centred methods provided by Gardner (1 988) in the context of the procurement of large scale military systems. In other cases the methods are developed to match the stages and procedures of existing commercial systems design methodoligies; for example, the implementation of human factors methods into the structured systems design methodology, SSADM, (Dmodaran et a!. 1988). Both of these approaches are for the development of bespoke or single client applications. Others have focused upon the generic or multi-client systems development processes in vendors of information technology systems. Galer et al. (1988) report the HUFIT (Human Factors in Information Technology) set of methods which is a 'tool box' of methods to support the design in a variety of vendors. As this work proceeds it calls into question the extent to which normal design methods can cope with human factor concerns. The conventional design process, the 'waterfall' approach, poses many problems from a human factors perspective. If, for example, a usability evaluation shows there are inadequacies in design, it must be possible to return to an earlier phase to undertake re-design. Problems with the waterfall method are widely recognized in the computer industry, and many developments are now based upon iterative design in which rapid prototyping of possible solutions permits earlier evaluation leading to re-design. This kind of approach provides better opportunities for the evaluation of usability during the design process. The term 'user-centred' design has emerged as a way of expressing design processes in which human factor issues are ofcentral concern. In some formulations, for example Norman and Draper (1986), the emphasis is upon translating knowledge about human-computer interaction into practice. In other approaches, for example Eason (1 988), the emphasis is upon user participation in the design process. All forms of usercentred design support the involvement of users but quite different philosophies can be detected. In the knowledge-into-use approach users constitute sources,ofdata; they are experimental subjects, who can inform researchers and designers about relevant aspects of human behaviour. In the user participation approach the users are clients, establishing their requirements, choosing between alternative technical options and planning their own futures (Ehn 1988). Recent commentators have noted the conflict between these approaches (Blomberg and Hendersen 1990, Bannon 1990). The supporters of the knowledge-into-use approach have expressed doubts about user participation, especially when reacting to rapid prototypes, because the user may not always be the best judge of his or her requirements. The supporters of user participation point to the way in which decisions taken during systems development express different values and objectives. Different potential systems can support autocratic or democratic values, encourage openness or secrecy, give control to the user or the computer, etc. They argue that it is for users to choose between these alternatives because they have to live with the results, rather than the designer who will go on to other systems (Hirschheim 1985, Kumar and Bjglrn-Andersen 1990).



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There is here a new version of a dilemma that has confronted practising ergonomists in many other situations. Who is the custodian of the human issues in the design process? Should it be a designer specializing in human-computer interaction, who will know the relevant theories and findings and be able to use the many human factors techniques to translate them into practice? Or should it be the user, the true client for the system, whose needs the system is designed to meet? The designer may know the techniques but he or she does not have to live with the consequences. The user is the client, but will not have the specialist knowledge. As always in these circumstances it is a question of constructing a partnership in which both can play an effective role. The conflict may not be quite as stark as it appears, because the proponents of the different roles for users and usercentred design are often describing different systems design processes. The particular form of interaction that a user experiences is likely to be the product of several design processes, as figure 2 illustrates (Eason '

1989).

End User

Design PrcMxwa

Ha Go& Role of Users

for specific

Generic Interfaces Fledbility TO& for Local Design

Task Match User Match Organizational Match

Adaptability S~PPO~+ Personalisation

Subjects

Figure 2. Human-cumputer interactive design in different systems development processes.

An important feature of the computer industry is that vendors are marketing hardware and software products and systems that are intended for sale to many customers. When they are purchased these products and systems are integrated with other products to produce application systems tailored to the particular needs of the organization. The particular part of the application system that is made available to a specific user can also be tailored to meet the personal needs of the user. This pattern of implementation produces three design processes where user needs can be addressed. It is instructive to ask which issues need to be addressed in each process and what role th'e user plays in each case. In vendor design of generic products the aim is to produce generic forms of interaction, and many vendors produce standardized interfaces for their products, which will be easy to use and consistent across the product ranges and will support a wide range of applications. The creation of effective forms of interaction requires the identification of usability principles for a wide variety of users, tasks, and environmental conditions, and the provision of sufficient flexibility for later design processes to construct applications for specific tasks. The products also need to provide tools to support subsequent design. Users who participate in the design of these systems are not specifically involved in creating a system for themselves; rather they act as representatives of a wider clientele. They may be more properly


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K.D.Eason

considered as subjects, helping designers generate general findings about human-computer interaction. The process by which generic products are tailored to serve particular applications in specific organizations involves the identification of unique user, task and organizational requirements, and matching systems to these needs. There may also be a process of socio-technical design as the technical system is constructed to be compatible with organizational changes. These processes are concerned yith choices between alternative socio-technical systems and are of great concern to users. As a result most formulations of this design process have user representatives, as a minimum, judging the proposals made by designers and, in some formulations, for example, Mumford (1 983), leading the process. A dominant concern is how users can be helped to make informed choices between technological options and the favoured approach is to enable users to actively engage with 'dynamic prototypes' (Harker 1987) or realistic trials (Tapscott 1982) so that judgements can be founded on experience of the technology. In the final stage a specific set of facilities is provided for a particular end user. The developments at this stage have to be truly and individually user-centred if the user is to find the facilities usable and acceptable. No matter how well they fit the characteristics of users in general, user commitment and ownership will only come if the facilities now fit the unique characteristics and requirements of the particular user. The design process must now adjust the system to the characteristics of the user and hislher range of tasks, and a support structure is required to facilitate learning and the progressive exploration by the user of the potential of the facilities that are available. This kind of local and on-going 'design' process is necessary if optimal task performance is to result from human-computer interaction. Viewed through this sequence of design processes the range of circumstances in which it is necessary to 'institutionalize' human concerns (Klein and Eason 199 1) if human-computer interaction is to be optimized becomes apparent. The particular way in which human-computer interaction needs to be addressed varies with the distance of the decision from a specific end user and this affects the role and contribution of the user to the design process. 8. Conclusions: towards support for the self-organizing user The field of human-computer interaction research and practice is burgeoning as the technology proliferates and advances. This survey is but a small sample of the whole range of research outputs now appearing. There are, however, some unmistakable trends as the discipline matures. Initially the field appeared to be a special case in the human-machine interaction domain in which cognitive issues were dominant because both human and machine were engaged in information processing activities. Within this paradigm, the field of study has blossomed as a truly interdisciplinary development in cognitive science, because of the need to find a framework within which the drfferent information processing taking place within the human being and the computer could be described, and effective forms of interaction developed. To treat human-computer interaction as only an exercise in information exchange bet ween different kinds of information processing systems has, however, proved an inadequate basis for predicting human-computer task peformance. The more reductionist, experimental studies which have examined specific aspects of hardware or software have time and again been shown to yield r e d ts of very limited generality, because so many other variables affect performance in real tasks. We have



737

in this review explored these variables by examining the task, user and environment (physical and organizational) factors which have been shown to have an impact upon human-computer interaction. The effect of research on this topic has been to take the study of human-computer interaction in many different directions and to cover most other topics in ergonomics as other human characteristics and behaviour are seen to be relevant. This development is in many respects leading away from an integrated theory of human-computer interaction, but there is a significant discernable trend in the way the two partners in the interaction are now considered. In the design of many early computer systems the assumption was made that the system would shape in most respects the way the task was to be performed, reducing the human partner to a subservient role. Today the perspective is different; the human being is now seen as the self-organizing and adaptive partner capable of responding to the changing requirements of the outside world and pursuing many different kinds of goal in task performance. The human is therefore the dominant partner who will utilize the services of the computer system only to the extent that it can provide a useful, usable, and acceptable contribution to task performance. The imperatives for the design of the computer partner have therefore shifted to the creation of a flexible array of easyto-use information services which the user (and latterly the co-operating group of users) can deploy to accomplish complex tasks. er has occurred in This shift to a user-centred view of h ~ m a n - c o m ~ u tinteraction part because of dramatic developments in the technology which have made the flexible presentation of sophisticated services ever more practical. It has also been stimulated by the results of the many studies reviewed here and, in particular, the conclusion that the 'uptake' of the technology wit1 only occur if the machine adapts to the user rather than vice versa. Lastly, it is undoubtedly also the case that researchers and developers have brough't their own values and aims to the development of human-computer interaction so that it can be truly 'user-centred' by liberating human intellectual capacities. The values of the human-computer interaction community are expressed by the titles of recent CHI conferences: 'Wings for the Mind' (1 989) and 'Empowering People' (1 990). Very rapid progress has been made in producing forms of human-computer interaction that give wider ranging support for the intellectual capabilities of the human user and even more promising prospects lie ahead as the technology develops. The research laboratories of the IT companies have working prototypes of flexible, adaptive, intelligent, multi-media systems of enormous potential. However, the commercial delivery of systems to end users is often a different world; one in which users may still find themselves confronted with unusable and unacceptable systems. The fact that the achievement of good human-computer interaction depends apon design processes close to users taking account of many specific user requirements means that transfer from research to practice is a major task. Embedding the fruits of research on human-cqmputer interaction into every stage and every form of computer systems design process is the next necessary target if the average user is truly to get the benefit of a sophisticated information-handling partner.

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