Grand Challenge in HCI: the Quest for Theory-led design – Alistair Sutcliffe (2005)

Grand Challenges in HCI: the Quest for

Theory-led Design

Alistair Sutcliffe

Introduction

Centre for HCI Design, School of Informatics, University of

Manchester, PC Box 88, Manchester, UK

Tel: +44 161200 3315

Email: ags@manchester.ac.uk

A grand challenge of theory-led design is proposed for HCI. The history

and state of the art in HCI theory and knowledge is reviewed, expanding

on Long & Dowell’s conception of HCI. A new approach to bridging from

theory to design practice is proposed that uses generic task models as a

means of locating theory-based design advice. Theory-based knowledge

is also transferred to design as bridging models and as critical cognitive

aspects which are applied to task models. Design of specific applications

uses theory-based knowledge via mappings to generic task models and by

the application of bridging models. The approach is illustrated by a case

study investigation of the design issues in notifier systems and explained

with a design scenario of hospital patient monitoring.

Keywords: theory, cognitive models, claims, bridging representations.

1 Introduction

Grand challenges have been much in vogue in the computer science community

[UKCRC 2005]; however, the computational emphasis in the grand challenges

competition has sidelined HCI to a lip-service role in Memories for Life challenge.

Fred Brooks [2003], however, was more enlightened and cites design of effective

user interfaces as one of three major challenges for the 21st century. The HCI

community should not be depressed by this outcome; instead, I argue it should

propose more ambitious and wider ranging grand challenges of its own, and in doing

so demonstrate that it has a broader ambition than computer science. In this paper I

will propose and expound the challenge of Theory-led Design.

The development and application of theory is a sign of intellectual respect in

most scientific or engineering disciplines, and HCI should be no exception. Long &

Dowell’s conception of HCI as craft, science and engineering urged systematic

development of principles, laws and guidelines derived from theory [Long & Dowell

1989; Dowell & Long 1998]. Barnard and colleagues in the AMODEUS project

represent the most concerted effort to translate theory into design practice over

several years. The cognitive theory of Interacting Cognitive Sub-Systems [Teasdale

& Barnard 1993], in combination with more formal system modelling was proposed

as a toolbox for designers [Barnard et al. 2000]. In restricted case studies, these

models could be demonstrated to ‘cohabit’, i.e. applications of each model analysed

different views on the same problem [Harrison & Barnard 1993]. However, a

key problem has been how to translate knowledge in psychological theory into a

form that is usable by designers. The task artefact theory has been proposed as

a means of developing HCI knowledge [Carroll & Rosson 1992], using claims to

express fragments for theory-based knowledge with contextual references to design

problems, artefacts and scenarios [Sutcliffe 2000; Sutcliffe & Carroll 1999]. While

claims continue to make modest progress [Carroll 2000; Sutcliffe et al. 2003], they

have not as yet become widespread as a bridging representation between theory

and design practice. The state of the art for HCI advice still remains as principles

[Sutcliffe 2003; Dix et al. 2003], or golden rules [Shneiderman & Plaisant 2004]

and the legion of, one suspects, under-used ISO guidelines [ISO 1997, 1998, 2000].

More recently HCI patterns have proliferated [Borchers 2001; Van Welie 2005],

often without any validation. While patterns can express knowledge in a more

contextualized manner, unless they are composed into a pattern language [Alexander

et al. 1977], they can present incompatible, inconsistent and fragmentary pieces of

HCI knowledge. The standardization process of developing an HCI pattern language

has been slow to emerge and one can question whether it would be necessary

since patterns duplicate much knowledge already present in better regulated sets of

guidelines.

Some may consider development of exemplar artefacts as a more productive

way to advance HCI. However, I believe that without theory, HCI will be doomed to

the invention of stimulating yet ephemeral artefacts [e.g. Ishii et al. 2001] without

generating generalized long-term knowledge. The thesis in this paper is to urge

the HCI community to adopt the Science of Design [NSF 2004] and thereby become

more than a sub-discipline of computer science. Instead, HCI can become the Science

of User-Centred Technological Design. In the remainder of this paper, I will review

the role of theory and HCI knowledge, and then propose an innovative approach

based on a new role for familiar task models. This will be followed by application of

the approach to investigate a particular area of attentive user interfaces, with a brief

discussion to conclude the paper.

2 Theories and HCI Knowledge

HCI is not short of cognitive theories to apply to design; see for example ACT-R,

[Anderson & Lebiere 1998], EPIC [Kieras & Meyer 1997] and LICAI [Kitajima

& Poison 1997]. However, theories of cognition have proved difficult to apply in

practice. They can be used to motivate experiments and demonstrate interesting and

useful design phenomena, for example Homoff’s work on optimizing menu layout

Figure 1: Long & Dowell’s conception of HCI, revisited.

for efficient search, and eyetracking studies that demonstrate that banner adverts are

not attended to or remembered but do impose subliminal cognitive cost [Burke et al.

2004]. This work uses EPIC as its theoretical lens. GOMS is the prime exemplar

of applicable theory [John & Kieras 1995], and continues to be the focus of many

studies although evidence of its effective use in industry is hard to find. A cutdown

version of LICAI has been successfully developed in combination with an

information searching algorithm (latent semantic indexing) in the CoLiDes systems

that can predict design flaws in website navigation and link cues given a model of

the user’s search goals [Blackmon et al. 2003].

The quest for bridging models from theory to design was pursued with some

vigour, first via design rationale, providing the glue to synthesize contributions from

different modelling approaches [Bellotti et al. 1995], and more convincingly by

developing Cognitive Task Models to analyse task sequences and diagnose potential

design problems indicated by reasoning with the ICS cognitive architecture [Barnard

et al. 2000]. Barnard, in his 1998 plenary address to this conference, proposed

* syndetic theory’ and a blending of several theoretical influences that could be

applied to design problems at different levels of granularity — micro and macro

theory. Unfortunately, application of this approach to scaled-up industrial design

problems has never been demonstrated.

Interest in theoretical approaches has continued in cut-down approaches such

as the Resource Theory that proposes an event modelling view incorporating

cognitive issues such as working memory and selective attention [Wright et al.

2000]. Interactors [Dix & Mancini 1998] provided an interesting approach for

encapsulating HCI knowledge in what are essentially ‘abstract interaction types’

(cf. ADTs) as specifications or code for generic interactive functions, e.g. multilevel

undo. More specialized approaches, such as Information Foraging Theory,

continue to motivate research in information retrieval [Pirolli & Card 1999], while

Activity Theory [Nardi 1996] has been much in vogue as an analytic framework

for ethnographic-style studies of CSCW and CMC systems. Although theory is

being used, its prime role seems to be an indirect influence on design via analytic

frameworks or general conceptual influences. For instance, it is difficult to extract

prescriptive design advice from the concepts of conflict, activity level, artefacts and

zone of proximal development in Activity Theory even though some have attempted

to derive heuristics from such opaque theory [Bertelsen & B0dker 2003]. The range

of applicable theory has been demonstrated by interest in theories of emotion [e.g.

Ortony et al. 1988], as an inspiration to frame design questions [Norman 2004], and

more directly as an embedded cognitive model to drive the emotional response that

embodies conversational agents [Cassell et al. 1999]. So theory is far from dead,

but the pathway for theory application in design research is fragmented, and more

critically to design practice, is unclear. The status quo is summarized in Figure 1.

The influence of theory-based research on design is tending to be recruited via the

scientific route in Long & Dowell’s framework, i.e. theory motivates experiments or

case studies, the results of which provide design guidelines.

So is there a consensus of what has been achieved so far? In the majority of

HCI text books, for example [Dix et al. 2003; Preece et al. 2002; Shneiderman &

Plaisant 2004], theory is present as the Model Human Processor [Card et al. 1983],

and as a bridging model in Norman’s [1986] action cycle. What is missing is the

meta-level guidance on how to exploit and develop theory in the design process: the

grand challenge of theory-led design.

We need to return to the debate on bridging from theory to design. Some

promising directions have emerged in cognitive dimensions [Green & Petre 1996]

which propose principles for the design and evaluation initially of notations but more

recently of interactive systems. Object system models [Connell et al. 2003] attempt

to apply cognitive dimensions within design contexts for particular problems, while

critical parameters focus attention on key cognitive requirements for interactive

systems [Newman et al. 2000]. The important direction, I believe, is to focus on

typical classes of problems which are common in HCI, understand the cognitive

and social implications of those problem classes and then apply the appropriate

theories to solving them. HCI needs to investigate tasks more deeply in order

to understand the psychological implications of certain classes of problem. Take

monitoring tasks as a specific example. Monitoring tasks are known to be error

prone and people find it difficult to concentrate over long periods of time. The types

of errors people make and their problem-solving strategies can be predicted using

several theories [Norman 1988; Rasmussen 1986; Hollnagel 1998]. Human error

theory predicts that interruptions and time pressures produce frequency and recency

gambling pathologies resulting in sub-optimal problem-solving strategies [Reason

1990].

Monitoring tasks involve a perceptual process of recognizing significant events,

cognitive processes of interpreting events, and domain knowledge to evaluate the

significance of events in context. Norman’s [1986] cycle of action can be reversed

to set these issues in an interaction context; i.e. once a significant event has

been recognized, interpreted, and evaluated one has to plan, specify and execute

the appropriate response. The critical cognitive aspects of monitoring tasks are

Figure 2: Process map of theory-led design.

selective attention and recognition of events, reasoning with domain knowledge to

interpret the events and then planning appropriate responses. To develop effective

support systems the designer has to understand the problem, isolate the critical

cognitive aspects, then use the appropriate theories or experimental evidence to find

appropriate solutions. This approach is summarized in Figure 2.

By linking theory to generic task models and bridging representations —

be they cognitive dimensions, claims or critical parameters — a library of HCI

knowledge can be built which enables effective reuse. Generic task models [Sutcliffe

2002] can play a key role by providing an access point from task analysis to reusable

knowledge. If specific tasks could be mapped to generalized tasks, and if the latter

are associated with theoretical, sound design advice, then designers will have advice

placed in the context of their current problem. They still have to specialize the advice

and reason about trade-offs but this is an advance on ploughing through libraries of

design guidelines or patterns. However, generic task models need to be associated

with ‘critical aspects’ to place theory in its application context. I have used the aspect

oriented programming analogy since it illustrates the problem. Theory provides

knowledge that is applicable in many parts of a design, i.e. cross-cutting concerns.

The problem is to define the theory treatment for the aspect and when to apply it at

‘point cuts’ in the design. Linking critical aspects to generic task models indicates

the point cuts, but defining the treatment is not so simple. This requires reasoning

about trade-offs using bridging models. There is no silver bullet for producing high

quality designs; however, theory-led design can make the bullet easier to aim. In the

following section I will put this approach to the test with an exploration of design for

notifier user interfaces, which support monitoring tasks.

3 Application of Theory-led Design

To illustrate how we should apply theory in HCI, I will investigate a current research

area as a ‘gedanken experiment’. Notifiers, attentional user interfaces or dual task

displays have attracted considerable attention over recent years [Horvitz et al. 2003;

McCrickard et al. 2003]. This research is motivated by a general user need, i.e. to

enhance support for multitasking and to monitor information such as stock markets

or the weather, while performing another primary task. The research problem is best

encapsulated by a scenario. Marilyn, a senior staff nurse, is in charge of a chronic

care ward and has to keep an eye on her patients during the night shift. The patients

are automatically given medication via drips for management of chronic and postoperative

conditions, e.g. pain relievers, anti-coagulants, etc. The patients’ heart and

respiratory rates and blood pressure are automatically monitored and displayed on

a screen in Marilyn’s office. She has to monitor patients’ condition and adjust the

rate of medication if the measured parameters depart from the expected treatment

plan. More urgent alerts must be triggered if the patients experience distress which

could be picked up by heart ECG sensors or an emergency call button which can be

activated by patients. If all is quiet Marilyn is expected to catch up on the day’s paper

work to complete duty rosters, treatment records, etc.

Several approaches have been taken to this problem and many systems have

been implemented which provide background monitoring displays as information

tickers [Maglio & Campbell 2000], ambient wallpaper [Stasko et al. 2004] and

radar metaphors to communicate the status of monitored information to the user

[McCrickard & Chewar 2003]. However, these designs are based on intuition and

give no guarantee of their effectiveness. Horvitz et al. [2003] have taken a more

principled approach by proposing a cost of interruption measure expressed as the cost

of diverting from the primary task compared with the benefit from the information

gained from the monitoring tasks. This enables reasoning about when to interrupt

using Bayesian networks with user defined valuation of the task activity, cost of

interruption and environmental measures. Chewar et al. [2004] have elaborated

this idea with a conceptual framework composed of three dimensions: Interruption,

Reaction and Comprehension, that draws attention to the cognitive parameters of the

problem, namely, when and how to alert the user to draw their attention away from

the primary task, how to communicate information relevant to the secondary task

and how to promote comprehension of such information. While these approaches

are better than craft-level design, they do not constitute a theory-based approach.

To examine the problem in a more principled manner we have to understand

the problem from a psychological viewpoint, and this is the first impact of theory:

the ability to conceptualize interaction problems. The first part of the problem is

alerting the users to relevant information for the secondary task. This poses the

system initiative question. Should the monitored information be accessible to the

user all the time, and hence possibly distracting from the primary task, or should it

only be made available when the system decides it is critical for the user’s interests?

The second issue is how to ensure the user has seen or heard the critical information

and responded to it. The third part of the problem is to support the user’s transition

from the primary task to the secondary task.

When to alert requires a model of the user’s task, the user and the context. This

is part of a user modelling grand challenge since acquiring a model of the user and

their context requires solving the difficult problem of inferring complex states from

Table 1: Cognitive task audit: Monitor and Evaluate tasks.

low-level data streams. I shall finesse this challenge and return to my main theme.

Task analysis is the conventional HCI approach to understanding the user’s domain

[Diaper 2002; Johnson 1992]. While a goal model and procedural sequences can

give us breakpoints where intervention should be more appropriate it doesn’t go far

enough. The cognitive demands of the primary task will influence when the user

interface should signal an alert. The role of theory is to provide a cognitive audit so

we can understand the critical aspects of a particular task and plan appropriate action.

An example of the cognitive task audit is illustrated in Table 1. In the hospital patient

monitoring scenario, working memory has to cope with keeping track of several

patients while selective attention will be distributed between the several patient

monitoring devices and the foreground tasks of updating drug registers and patient

records. Reasoning will be rule-based using the nurse’s training, but knowledge

intensive judgement [Rasmussen 1986] will have to be applied when the unexpected

happens.

A cognitive task audit requires application of general psychological knowledge

to the task in question. While this does utilize theoretical knowledge, it does so

only second hand via education. The designer has to know the theory in order to

apply it in a cognitive task analysis. However, if a set of generic task models could

be developed and annotated with cognitive aspects, then theoretical knowledge could

be reused by non-HCI expert designers. A taxonomy of generic tasks exists [Sutcliffe

2002]; however, the process of mapping from specific task to these generic models,

annotating them with cognitive properties and then applying such knowledge are

open research questions.

Three tasks involved in the notifier problem are illustrated in Figure 3, showing

the critical cognitive aspects. For recognition the salience and modality of the

stimulus is important. This is set against environmental obstacles such as complexity

of the environment and competing, similar stimuli. Precise design advice depends on

knowledge of perceptual psychology [e.g. Ware 2000] which can not be encapsulated

Figure 3: Monitor, Interpret and Evaluate generic tasks annotated with critical aspects and environment

 

Figure 4: Components in the Embedded Interaction Model for system initiative control.

in simple models, although design principles for choice of media and modalities

provide some guidance [Sutcliffe 2003]. These need to be combined knowledge

critical aspects such as selective attention to understand possible problems arising

from competing stimuli on the same modality, and the effect of distractions on the

monitoring task. In the Interpret and Evaluate tasks the critical aspects point to the

need to reduce working memory burden by supplying appropriate information for

understanding the event within a display appropriate to the user’s task and context.

Grand Challenges in HCl: the Quest for Theory-led Design 499

Attention Resource Theory [Wickens 2002] can provide an appropriate

framework for analysing the selective attention and when to intervene problem.

This provides the basis for specifying an embedded cognitive model which predicts

when to intervene, given a task model and monitored inputs of the user’s activity.

This embedded interaction model (see Figure 4) could be configured to other

notifier systems, thereby contributing another conduit by which theory can influence

design via reusable computational models that embed theory for solving interaction

problems.

Knowledge of the salience of perceptual stimuli and how the stimulus properties

affect attentional executive processing are necessary to design the alerting stimuli.

Such knowledge is only partially formulated even in cognitive theory such as EPIC

[Kieras & Meyer 1997] and experimental derived knowledge [Ware 2000], so the

designer will have to use several sources to understand how the salience of stimuli

interacts with users’ knowledge and motivation in perceptual mechanism. This

points to a need for new theoretical development. However, sufficient knowledge

already exists to suggest a design solution for the appropriate alerting stimulus and

modality. In our scenario, the alert will depend on the criticality of the information.

If the monitored parameters stray out of a normal range but into a non-critical zone

then a low-level stimulus will be used (e.g. colour change in the information display);

whereas if parameters stray into a critical zone then more salient alerts, such as voice

or sound coupled with visual highlighting, or animated displays, are required. Note

that this design adaptation will also be driven by the embedded interaction model.

Applying theory also helps understanding how to manage the transition from the

primary to a secondary task, although once again the task has a critical intermediary

role. Marilyn has to monitor several stimuli, interpret the measurements and then

decide on appropriate adjusting action. However, when an emergency occurs she

has to rapidly interpret the event, diagnose the problem and take remedial action.

In both cases her training will prepare her for the correct response. However,

the patient-monitoring task is close to a skill and requires little reasoning; in

contrast, responding to an emergency requires more conscious rule- and knowledgebased

reasoning (Rasmussen, 1986). Diagnosis places different cognitive demands

and hence requires information displays localizing the problem, while suggesting

possible causes and remedial actions

The storyboard design that might be prompted by the application of theory-led

design is illustrated in Figure 5.

The user’s foreground task occupies most of the screen, as windows with Word

and Excel that Marilyn uses for updating her records, writing reports and planning

rosters. The monitor is placed on continuous display on the side of the screen, since

change in the background monitored system is gradual so Marilyn can sample a

patient’s state on demand. A current and recent past display enables her to glance

at the display and see if the state of any patient has changed in the recent time

period. The display maps to rooms occupied by individual patients on the ward,

with colour coding used for change in parameters: from green within normal range

to red signalling a dangerous digression. Dangerous changes trigger an audio alarm

and highlight the patient’s location. The audio alarm uses canned speech messages

 

Figure 5: Storyboard design for the patient monitoring system.

which can be tailored to reinforce the message. Below the ‘room map’ display a time

line gives the sequence of visits to check on condition, changes to medication, and

reminders when periodic checks are due.

The above design decisions were motivated by several critical aspects. Use of a

continuous display monitor was motivated by the periodic nature of the monitoring

task and the cognitive aspect on reducing working memory burden. When to use

an explicit alert used the embedded model to calculate the trade-off between the

criticality of the event and the cost of interrupting the foreground task. Third was

how to alert the user to change; a variety of strategies were indicated linking the

strength of the stimulus to the criticality of the event. This used media design

principles as well as knowledge of language theory and selective attention. The final

design issue is how to make the transition between the foreground and background

tasks. System actions are tuned to the criticality of the monitoring task. For lowlevel

alerts the foreground task is automatically saved but no further action is taken

apart from displaying more information on the critical patients. For critical alarms

the work is saved, the Word and Excel windows are closed, and patient information

is displayed with appropriate treatment suggestions for the individual concerned.

In this case the system has made the transfer from supporting documentation to a

diagnosis task.

4 Conclusions

This exercise in theory-led design proposed a solution via three complementary

strands for applying theory to design: internalized knowledge of simplified

psychological theory, reuse of knowledge located via mapping generic tasks

Grand Challenges in HCl: the Quest for Theory-led Design 501

applicable to the problem, and design of reusable embedded interaction models. It

will always be difficult to separate the relative contribution to a design solution from

internalized and tacitly applied theory, reusable knowledge, external guidance and

advice. To an extent I argue for both as a necessary prerequisite for good design.

My quest is to provide different pathways by which knowledge from theory can

be applied to the design process. This is where I believe generic tasks and critical

aspects can play their role, first as a retrieval mechanism and secondly as a method

of structuring HCI to teach it in the first place.

It is germane to reflect whether this approach is really new. For example,

application of Ecological Interface Design [Vicente 1999] could have led to the

same metaphor domain representation of the patient monitor interface, although this

method would not have provided advice on cognitive aspects of media selection.

Claims and the task artefact cycle provide a similar access path to theory-based

knowledge, which I have proposed as a precursor to this approach [Sutcliffe 2000].

In an extended schema [Sutcliffe & Carroll 1999] claims have been linked to

generic task models and organized in taxonomies. Claims could therefore provide

design advice for specific critical aspects. The critical aspects are not dissimilar

to cognitive dimensions, and provide summaries of cognitive knowledge linked to

a particular design concern [Green & Petre 1996]. Generic task models, embedded

cognitive models and critical aspects supplement those views, but bring theory-based

knowledge closer to the designer by providing a more direct mapping to tasks and

design problems.

The example used in this paper has inevitably biased the focus towards cognitive

theory and single user systems. The impact of social theory and critical aspects for

collaborative systems has hardly been researched. For example are there critical

aspects of shared identity, mutual awareness, collective motivation, the glue of social

relationship as factors that influence the success of groups? So far we have but a

few heuristics to use, although a more well formed theory, such as Small Groups as

Complex Adaptive Systems [Arrow et al. 2000; Sutcliffe 2005] could provide more

insight into theory-led design for collaborative systems.

In conclusion, theory will continue to play a vital role in design, not only in

HCI but in the wider context of technology design, as computers become part of

everyday products. The quest to translate theory into usable knowledge for design

is still underway, and in this paper I have argued for a multi-path route via reuse

of knowledge in the head and theory embedded in computation models, as well as

localizing knowledge in a task context. This grand challenge has a wide-ranging

scope as a general theoretical approach to design not only of computing related and

computer embedded artefacts but to all designs that involve human interaction or

use. HCI could transform itself into the Science of Design by rising to this challenge.

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