Projected Cognition – extending Distributed Cognition for the study of human interaction with computers

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Interacting with Computers 20 (2008) 128–140 www.elsevier.com/locate/intcom

Projected Cognition – extending Distributed Cognition for the study of human interaction with computers William H. Edmondson *, Russell Beale School of Computer Science, University of Birmingham, West Midlands B15 2TT, United Kingdom Received 14 May 2007; received in revised form 8 September 2007; accepted 23 October 2007 Available online 7 November 2007

Abstract In this paper, we introduce the notion of Projected Cognition as an extension to Distributed Cognition. Distributed Cognition is a conceptual framework which can be useful in studying human interactions with artefacts; the idea is that of cognition not bounded by the cranium but instead perfusing artefacts in ways that are recoverable. We argue that this analysis has not been fully understood in relation to the behaviour of humans with artefacts in that the intentionality in behaviour has been ignored. We argue that we need to view the human as sometimes projecting their intention in behaviour onto the artefacts they use, and suggest that this conception permits greater clarity in the study of user behaviour with artefacts such as computers. We illustrate the development with case studies of two users of complex configurations of computers as well as examples drawn from the published literature. We conclude with consideration of some design implications and discussion of related domains in HCI where Projected Cognition could be influential.  2007 Elsevier B.V. All rights reserved. Keywords: Distributed Cognition; Observational study; Multiple computers; Virtual desktops; Projected Cognition; Computer supported cooperative working

1. Executive summary This paper presents a new idea – Projected Cognition – by means of which analysis of human interaction with artefacts, especially computers, can be made more comprehensive. The paper is essentially in three main parts. The first part (Section 3) reviews our understanding of the widely used concept of Distributed Cognition. Distributed Cognition acknowledges that a purely intracranial conception of cognition is too narrow: cognition can be distributed over time, over space and objects, and over other cognizers. It is proposed that work in such a tradition has become insensitive to the intentions of users and that these intentions can be key to understanding what users are doing, especially in complex settings. This proposal is made in the context of discussions of various well-known examples from the literature on Distributed Cognition. *

Corresponding author. Tel.: +44 121 414 4763; fax: +44 121 414 4281. E-mail address: [email protected] (W.H. Edmondson).

0953-5438/$ - see front matter  2007 Elsevier B.V. All rights reserved. doi:10.1016/j.intcom.2007.10.005

Projected Cognition is promoted as a way of shifting analytical focus to the intentions of users. It can be envisaged as an aspect or subset of Distributed Cognition and has the important characteristic that the person distributing their cognition is doing so with intent, or in such a way as to permit recovery of intent. Projected Cognition is seen in functionality which is allocated to or imposed on resources. The second part (Section 4) looks in detail at the computing resources used by two people who have each arranged their work environment around more than one computer. One user has four computers and six screens in his office, and his work covers a variety of different activities: experimental data analysis (number crunching); teaching; general administration; specific administration (admissions work as part of undergraduate recruitment activity). The second user has only two computers, but his utilization is both rigidly patterned and flexible: he considers he has two major tasks and each requires (different) configurations of the two machines as means to deploy the resources he needs. Observational work coupled with face-

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to-face interviews reveals that use of multiple computers reflects complexities in task structures not apparent when looking at use of multiple applications on a single computer. It is not the case that using multiple machines is an extravagant way of deploying multiple monitors. The final part of the paper (Sections 5 and 6) reviews the outcome of the observational work, in relation to developing the notion of Projected Cognition. Patterns of user behaviour are analyzed and the utility of multiple computer configurations is explored in relation to complexity of tasks. The interpretation is that users can project their intention on to the computational resources in such a way as to achieve and manage complex task structures. Examples of such tasks are ‘admissions work’ in a university department, and ‘gaming’ using role-play games via the internet. It is noted that users might achieve their projection of cognition onto the resources in ways which are individualistic and perhaps incoherent. This has implications for development of CSCW in settings involving multiple computers because the intentions of the users may not be readable (other than by themselves). Implications for design of software applications are also recognized and contextualized within the discussion of Projected Cognition. Possible empirical studies are discussed. 2. Introduction This paper is in several parts. In Section 3 we provide an account of Distributed Cognition to which we add the notion of Projected Cognition, interleaving examples as appropriate. The next section contains an account of two users of complex computer configurations, showing the utility of the new approach. The remaining sections offer a general discussion of Projected Cognition in the context of HCI and an appraisal of its utility, both in theoretical terms and in relation to domains in HCI such as CSCW where Projected Cognition could be influential. Scope for further empirical work is discussed as well. 3. Distributed and Projected Cognition The key conception of Distributed Cognition is that the cranial fixation in conventional thinking about cognition is too limiting. Cognition is more than just an intracranial process accessible only via some sort of interactive behaviour such as speech. Within this framework it is recognized that cognizers distribute their cognition into their environment – and thus onto artefacts – and this can happen in complex ways. An important aspect of work in Distributed Cognition is that ethnographical techniques are involved in uncovering what is going on. 3.1. Distributed Cognition – core concept Appreciation of the conception of Distributed Cognition comes readily if we start with some historical examples of the development of artefacts. Hutchins (1995) provides

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an account of the development of navigational instruments such as the astrolabe which, he shows, encapsulates knowledge of facts and (computational) processes and constitutes ‘‘. . . a physical residuum of generations of astronomical practice.’’ Hutchins (ibid) offers other examples and thereby builds in the mind of the technically literate and numerate reader a very clear conception of the distribution of cognition into and onto artefacts over historical time. de Le´on (1999) provides an elegant account of the evolution of the operation of a rifle. His paper is titled ‘‘Building thought into things’’ which neatly encapsulates the point being made here. As with Hutchins’ examples, de Le´on’s account shows how the cognition in the artefact can be extracted, layer by layer, as a sort of cognitive archaeology. The cognition has been distributed over time, from more than one cranium, and yet is essentially recoverable and thus ‘re-cognizable’. It is important to note three things about this style of Distributed Cognition. Firstly, it is implicit: each contributor to the artefact made an improvement or modification with the intention of making the artefact more effective or aesthetic or whatever, but not with the intent of making their cognitive processes recoverable (the artefact was not produced with modern day cognitive archaeology in mind!). Secondly, and in a sense implied by the first point, it is not necessary for a successful user of the artefact to recover the Distributed Cognition within the artefact. A very obvious example of this point is found in usage of cross-head screws with motorised drivers. An electric screwdriver ‘makes sense’ of the development of the cross-head screw (the driver does not slip out of the head of the screw as easily as the conventional blade screwdriver does with a slothead screw), and some assembly workers probably come to realise this without tuition. Their perception does not necessarily improve their skill in trained settings but may perhaps yield more effective performance in untrained situations. The third point relating to the examples above is perhaps the most important. The artefacts are very specific in terms of the activities undertaken by the user. Indeed, in the case of the rifle firing mechanism, as recounted in de Le´on’s paper (op cit), the activity of preparing the armament for use is nowadays reduced to loading the ammunition; the original task was complex and has essentially been eliminated as the firing mechanism has become greatly simplified. In the case of the astrolabe the complex navigational task is streamlined as general purpose computational effort is constrained within the artefact. In essence the originally complex task becomes merely an activity with the artefact. As Hutchins (op cit) explains: ‘‘Many of the instruments of Western navigation are based on the principle of building computational constraints of the task into the physical structure of the artifact.’’ This reduction in task complexity through creation of special purpose artefacts is widely encountered in human experience with tools. The core conception of Distributed Cognition, often attributed to Hutchins, but plausibly independently arrived

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at by Bærentsen (1989) – cited by de Le´on (op cit) – relates to task specific artefacts which evolve over time and where current users do not need to ‘keep up’ with the evolutionary/historical record. From this base the conception is extended to a more general statement that cognition can be distributed over shorter time-spans, over space (in addition to objects), and over other cognizers. These cognizers need not necessarily be human – guide dogs for blind people would be an example here. Distribution of affect has also been proposed (Edmondson, 2003) whereby artefacts/actors come to have emotional significance or relevance in similarly distributed patterns (distribution over time, over space and objects, and over others). Distributed Cognition is a powerful concept, one which has done much to further our understanding of human behaviour, especially with artefacts. More widely, the issues raised in the practical world of Human Machine Interaction find parallels in theoretical developments in psychology and philosophy where, for example, serious consideration has been given to the concept of extended minds (for a review, see Wilson, 2005). Our concern here is not to diminish the importance of the concept, but rather to provide a more nuanced account of some behaviours than might otherwise be readily available. In doing so we find it necessary to consider some problems with the conventional conception before proposing a modest extension.

3.2. Problems with Distributed Cognition accounts Research in Human–Computer Interaction has profited from the use of ethnographical methods and interpretations afforded by the theoretical framework of Distributed Cognition (Halverson, 1994; Rogers and Ellis, 1994; Hutchins, 1995; Smith and Hart, 2006). However, it has been argued (Wright et al., 2000) that the approach does not provide an effective model of interaction, necessitating the development of a complex resource model including interaction strategy. For researchers looking to understand and improve the experience and effectiveness of interaction with computers the essential insights from working within the Distributed Cognition framework are: (a) it makes sense to observe users at their work and to interview them about their conceptions of the roles played by computers in what they do; (b) it is possible to bring some coherence to observations of users’ behaviour when the accounts are set out in terms of Distributed Cognition; (c) the conception of Distributed Cognition is not without its problems. We turn now to consider these problems. We have come to realise that there are three issues that need to be addressed when looking at complex interaction behaviour within the framework of Distributed Cognition. The first is that the focus on ethnography can come at the expense of producing informed design solutions (Hughes et al., 1992). Good ethnographers produce insightful accounts of behaviour with artefacts which read convincingly (see for example, Hollan et al., 2000; Brown et al.,

2002; Rode et al., 2004) but which do not provide such clarity in relation to prospects for improved system design. The second issue is that the accounts seem to lack a dynamic aspect – it is as if the behaviour has been dissected like a dead specimen. The problem of providing systematic accounts of behaviour which preserve the feel of activity as it happens has been noted before; Wright et al. (2000) advocate incorporating an understanding of the user’s interaction strategy, for example. Wærn et al. (1999) note the need to distinguish process accounts from ‘‘rear-view mirror’’ accounts. In the text earlier we used the phrase ‘‘cognitive archaeology’’ and we suspect that the reader’s acceptance of this is indicative of the way in which ethnographic studies have come – unhelpfully – to be thought of as ‘‘rear-view mirror’’ work. The third issue is that users behave with intent, and this can be a significant part of the distribution of cognition. We consider that sometimes it is necessary to recognize the intention in behaviour to make sense of the observed activity, but the observed behaviour does not necessarily look obviously intentional, or where it is the intentionality is not clear to participants. Whereas the conventional notion of Distributed Cognition is an aspect of observable behaviour a concern for the intention in behaviour requires assessment of underlying behaviour (Edmondson, 2001). The concern is more for a ‘why is X doing that?’ style of probing in ethnography than it is for ‘what is X doing?’ observation. Our focus now moves on to considering intention in interaction and to case studies which profit from such a perspective whilst at the same time illuminating the general enquiry. 3.3. Projected Cognition Our view is that Distributed Cognition is now rather too much a ‘third person’ perspective on observable behaviour. To be sure, accounts of users with artefacts need to be objective where possible, but the ethnographer’s work is more than just observation, recording, documentation and measurement (Bannon, 1995). Ethnomethodology is about trying to understand why behaviours are as they are, from the perspective of participants as much as from those observing (Forsythe, 1999). It is possible that in recent years a concern for objectivity has undermined the notion of ‘participant observer’ and thus the original insights from work on Distributed Cognition – notably illustrated in Hutchins’ extensive context setting narrative (Hutchins, 1995) – have given ground to those who prefer to stand aside and merely document the details. We have introduced the term Projected Cognition, as an extension or elaboration of the notion of Distributed Cognition, in order to capture or reflect the underlying behaviour of users – their motivations and intentions, their sense of purpose or task rather than task details or activities (the issue here is scale of granularity rather than terminology). Projected Cognition is an aspect, subset, or manner of Distributed Cognition, and has the characteristic that the per-

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son distributing their cognition is doing so with intent, or in such a way as to permit recovery of intent (by themselves or others). The conception we are concerned to capture in the term Projected Cognition is that people interacting with artefacts or machines may do so in a manner which reflects their will rather than their skill. Skilled tool usage, for example, can be thought of as an extension of a person’s articulators accomplished in such a way as to look like incorporation of the artefact into the body. Craftsmanship is practised, ‘automatic’, but still describable as Distributed Cognition. Projected Cognition goes further to cover situations and behaviours which are not practised, where the extension of articulation is not incorporated, where the person’s will is manifest but the physical outcome not automatic, where the tools/artefacts available do not offer the desired functionality. In such settings intention motivates activity but this activity is not always predictably or skillfully patterned. Projection of cognition is about imposition and allocation – the cognition is still distributed, but the manner of distribution matters, and matters in the moment, because the outcome depends on the successful management of the distribution. Much of what we uncover as ‘conventional’ Distributed Cognition, for example Post-It notes on computers, or cartoons attached with fridge magnets in the kitchen, or shopping lists, or . . .. resembles the swarf of thought. What is captured in the notion of Projected Cognition is the distribution itself, as an activity, with its manner and effectiveness there and then. We will see a variety of illustrations below and two examples from an observational study show how complex this projection can be in settings where the functionality of specific tools does not map well into the structure of tasks. Even when practised, in the sense familiar to the person concerned, projection of cognition can be variable in ways which detract from its readability – by the individual concerned and by others. This matters because without some measure of readability of the activity the person can ‘lose the thread’ of what they were doing – as when one returns to the keyboard after a break, to peer at the screen to be reminded of what one was trying to do (the problem is the need to recover the intention). This issue also matters in CSCW settings where the need is for others to be able to read the situation and recover intentionality. So, part of projection of cognition is the expectation of the individual, and of co-workers when involved, that the intention is recoverable. In this regard such interaction has properties not unlike dialogue where intention must be recovered for successful interaction. Which is to say, without going deeply into the literature on pragmatics and discourse, that humans in at least one (other) domain of behaviour are skilled at ‘reading’ the intentions of others. 3.4. Projected Cognition – theoretical issues We noted earlier that conventionally it is considered that cognition is distributed over time, over space and objects,

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and over other cognizers. This can also be assumed for Projected Cognition. For example, Projected Cognition can apply over various timescales (but perhaps less obviously than the more archaeological reading of Distributed Cognition). The projection of cognition over space and objects is illustrated in the detailed examples to be found below and in Section 4. Likewise, the projection of cognition over other cognizers is seen in some teamwork and discussions thereof – see also the example below of User A’s working environment. In short, it seems that incorporation of Projected Cognition into the overall framework of Distributed Cognition is readily achieved. We could claim in addition that such linkage enhances the value of ethnographic work by licensing observers’ intuitions about intentions. Ethnographers rightly have concerns about the validity of attributions of intention, but Projected Cognition provides a way of anchoring such discussions. 3.5. Projected Cognition - examples The key thought to be carried forward in the reader’s mind is that Projected Cognition is active, not passive, and anchored in a person’s activity which intentionally allocates to or imposes on – artefacts, spaces, and cognizers – functionality or specificity which s/he requires. There are a number of points which can usefully be made with examples. We first consider the sort of situations where Projected Cognition and Distributed Cognition might be thought to overlap. Two examples are useful here: • A person who picks up a bicycle tyre lever to open a can of paint may do so the first time with novel intent and thereby projects their cognition. Years later the same person with the same tyre lever opening another can of paint may think nothing of it – the tool is now special purpose. To the observer who does not know about bicycle tyres both events illustrate Distributed Cognition (the tool is a specific shape for opening paint cans) – but if they know that the first occurrence was indeed novel they would recognize that situation as Projected Cognition. If they know about bicycle tyres and the levers used they would recognize the projection of intention as having taken place at some time and might check through dialogue when that happened (‘‘That’s handy.’’ ‘‘Yes, had the idea years ago when I had a bicycle and used to repair punctures – the bike’s long gone but I kept the little levers from the repair kit.’’). • A kitchen is a configured complex of resources designed to serve a primary task which has two phases (there may be other tasks). Food is prepared for consumption using a variety of tools and utensils (phase 1) and the tools and utensils have to be returned to their initial state (phase 2 – think of this as ‘resetting’ the kitchen for phase 1). Kitchens have some very basic core components which tend mostly to come preconfigured – availability of energy resources for heating etc., cupboards

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and surfaces, cool/cold food stores, water supply and washing arrangements. The physical disposition of these is typically arranged to minimize hazards and unnecessary carriage of items. So far, so ‘standard’; in reality kitchens vary enormously. Users impose and allocate functionality and the kitchen becomes ‘personalized’ through projection of cognition (strongly so in the case of a dominant user, more diffusely in the case of a family all of whom cook). The users are projecting cognition onto the situation in ways which sometimes are novel for them (but not, perhaps, for observers), sometimes ‘fossilized’ and ‘time-honoured’ and now only Distributed Cognition (but perhaps not for the observer), and sometimes novel for one user but not others. Guests are more or less skilled at reading the Distributed Cognition in the kitchen they visit and may have to read the Projected Cognition as they participate in meal preparation (they may be given specific tasks and have cognition projected onto them, which may or may not be readily accepted – kitchens can be the location for heated discussion as well as heated food!). The guest may project their own cognition which has to be read by the owners after they have left (‘‘Now, where did he put that jug? Oh, I see, that makes sense.’’). Office layout can be considered within the Distributed Cognition framework to provide evidence of projection into the environment not just of the cognition of the user but of the intention behind these artefacts. However, the intentionality has not been foregrounded in earlier accounts within the Distributed Cognition framework (Rouncefield et al., 1994). It is important to understand that the user/worker may be doing things to the environment with the intention of recovering a state of mind, not just as the consequence of a state of mind. • For example, a Post-It note on the frame of the computer screen is put there to remind the user to phone xyz about abc. A straightforward Distributed Cognition account of the use of Post-Its has it that the user is distributing task information/memory into the environment. The Projected Cognition account has it that the user has the explicit intention that when they next sit at their computer, the note will be read and they will also be reminded that xyz is on holiday and will be back and further that they can recover the information about the return date from memory (or another phone call). Or not – sometimes the projected distribution fails and instead of writing the name of the person, or the issue, one finds just a phone number.1 We have all seen such notes, even if we do not produce them. This phenomenon occurs because, at the time, the notion of whom to phone is foremost in the mind of the writer, and it 1 One of us likes to call such a sparse Post-It note an ‘‘anomerandum’’, namely a memorandum without the name of the person to be called!

does not occur to him/her to distribute that information into the environment: they choose to project the intention to ring, but may forget to note all pertinent details, like whom to ring. Likewise, users with cluttered offices may, for example, arrange piles of paper as records of intent, for example with regard to processing the nearest pile first, or as reminders (again) of intent to do particular things. A more generic illustration of the difference between Projected Cognition and Distributed Cognition comes from looking at the distinction between ‘purpose’ and ‘task’, on the one hand, and ‘activity’ on the other hand (granularity again). In relation to tools – a special type of artefact – the distinction is actually quite clear, although subtle. • A complex or general purpose ‘screwdriver’ tool-set may have a variety of different ‘bits’ (the technical term for the short pieces of metal in shapes designed to fit into the handle, at one end, and to match the shape of the fastener, at the other end). To use such a tool one has to recognize the desired configuration, locate the appropriate ‘bit’, and fix this into the handle. The purpose drives the configuration until the activity can become merely the task of rotating the fastener. The point being made here is straightforward – the user of a complex screwdriver tool-set projects cognition via the selection of the appropriate ‘bit’. The general purpose tool is temporarily allocated to a specific task. • Training for use of specific tools is necessarily easier than training for general purpose situations, (cf. Wærn et al (op cit)), because the latter requires training for task characterization and activity identification prior to task execution. Note that it is commonplace to find ‘bits’ for the ‘screwdriver’ that are specially shaped sockets to fit over the heads of bolts, and the nuts into which they screw. The ‘screwdriver’ tool-set is more accurately but cumbersomely termed the ‘rotational fastener’ toolset. The variety of specific or individual activities accessible via the general purpose tool-set increases as the complexity of the ‘bits’ increases; correspondingly the user has to work more effectively with their sense of purpose to configure the tool-set for a specific task. The point of elaborating the screwdriver example is to illustrate complexity in configuration. Task switching, or multi-tasking, seems to be a succession of different (sub-)tasks using a single general purpose tool. This is complex projection of intention and sense of purpose, but as we will see below computers offer yet more complexity. Task configuration and task switching in the general case requires projection of cognition. In fact, we can provide a neat bridge between one of the historical examples introduced earlier – the astrolabe – and the use of computers, to which we turn next.

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• Hutchins (op cit) notes that the astrolabe, an ‘‘analog computer’’, achieves its effectiveness by being more general purpose than it initially seems. He writes:

‘‘Each astrolabe is really a kit that can be assembled differently according to its use: As the configuration of the celestial coordinates changes according to the latitude of the observer, a set of removable plates – sometimes as many as six, engraved on both sides – is usually supplied, fitting into the hollow of the mater [frame], so that the user can select the plate most appropriate to his own latitude.’’ (NMM, 1976, p.14). What we see here, then, is an analog navigational computer configured by the user for the specific task of navigation at a specific latitude. The user is projecting cognition and the astrolabe, as they use it, reflects their intention. Note that the Distributed Cognition of those who produced the astrolabe is not an issue here – the artefact is in other hands now. But it was designed to permit the projection of cognition, the configuration for a specific task, that the user must go through to bring the artefact into use for the specific task of navigation in specific waters. When the process of configuration is itself well-practised it becomes Distributed Cognition rather than projected. 4. Projected Cognition – using computers Computers encountered in offices are typically general purpose tools. They are configured by selecting the application(s) to be used. What can observation of users tell us about how well the systems are designed for users to project their cognition? We turn now to consider two users of complex computer configurations. Much of the material in this section is adapted from an observational study of users of multiple computer systems (see Beale and Edmondson, 2007). Our concern here is to foreground the discussion of factors which illustrate the projection of cognition. We also include a brief discussion of existing work on users of virtual desktops and multiple monitor systems. Office systems have been widely studied (e.g. Rouncefield et al., 1994; Sellen and Harper, 2003), but this study (Beale and Edmondson, 2007) looked at multiple computer systems in particular, and provides two examples which illustrates the value of extending Distributed Cognition to include Projected Cognition. 4.1. User A User A is a University lecturer, with a wide range of responsibilities and activities. His office environment has a large number of shelves, filled with books and journals. Despite the predominance of paper and books within the office, A considers most of his work to be done on the computer, whether it is teaching preparation, administration,

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or research. A’s computer setup comprises four machines with six screens. From left to right in the photographic montage shown below, these are: a Mac G5 with 2300 screen and 3 TB of field data; a G4 laptop with screen (and a separate wired keyboard and mouse), a Samsung monitor attached to the laptop, a 2300 Mac display attached to a Mac G4, with a keyboard/mouse along with an older Mac display attached to the same machine; and lastly a PC laptop and screen on the desk behind the swivel chair. Thus there are two laptops and two desktop machines – see Fig. 1. All the machines are physically networked onto his department’s Ethernet network, and so are visible to each other, and to the central filestores. However, all of the machines are also wireless enabled. The Macs are MacOS X 10.4 and the PC has XP installed. Apart from the PC (with its integrated keyboard and a wired mouse) the other machines have wired keyboards and mice. A was studied in situ on a number of different occasions over about a month; the first session was of about an hour’s duration, and was mainly observational, whilst the subsequent ones were for similar durations but involved much more discussion and questioning. Additionally, the usage and setup was discussed outside the office on numerous other occasions, and a number of short office visits also contributed to the study. A’s perception is that the tasks he undertakes are mapped onto the computers, and not so much onto the displays. In fact, it seems simplest to state that the tasks are most strongly related to the four keyboards that are on the desk surfaces in his office. When asked to describe how his work is mapped on to the different machines, A presents a perspective on his work that partitions tasks into specific activities: admissions, research, and preparing lectures are major tasks and each involves email, spreadsheet use, word processing, some special purpose software such as Powerpoint (for teaching), Access (for admissions), etc., and both tasks and activities are allocated to specific machines/screens. Email is interestingly both a task in itself (allocated to the right hand screen attached to the G4) and a subcomponent of other tasks (see below for further discussion). However, the need for a number of computers is, at this stage, unclear – would not the same effects be visible if we have a different set-up: one computer, one screen, with or without virtual desktops, or the same number of screens, all attached to one computer? The single computer scenario is not possible for practical reasons, since two operating systems are in use at the same time. The PC laptop is used for only one task: student admissions. The University runs a central admission system that is only accessible via a PC client, and hence the laptop supports that task. All discussions with A showed that he felt that the role of the laptop was for admissions, and felt happy with a cognitive allocation of admissions to that machine. Of interest is the fact that A went through a phase of trying to get reliable PC emulation to work on the Mac G4 so as to avoid the use of another machine. Problems

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Fig. 1. A’s set-up: six screens, four computers, one user.

with running the university’s admissions software in such an environment led to A’s reluctant acceptance of yet another machine into his office. Thus the proliferation of machines for A was not something desired for its own sake. The sense for A that the PC laptop is the ‘Admissions’ machine is thus a cognitive allocation in response to the machine’s presence. This account indicates that for A it would be quite acceptable to be without the special ‘Admissions’ machine if all the software ran on the Mac. On the other hand, the complexity of switching applications (to accomplish task switching to and from admissions work – see later discussions in Section 5) that might be required in such a setting might spur A to acquire another machine in such a scenario – we will never know. The admissions process has a strong paper-based element, and much of the actual work on admissions requires reading and understanding the forms, and recording the outcomes on the system. It has been proposed in the University that the UCAS forms will be distributed electronically and when this happens the ‘Admissions’ PC will be needed for that work also. What is more interesting is that communications from the department’s other admissions people, and from the centre, that arrive by email, are actually processed on the G4 Mac, (actually on the older Mac monitor). This display is used primarily for processing email, whether admissions or other messages. It is the case that the emails are fundamentally meta-information: information about applications, or questions from students, but in all of our conversations regarding where the work is done for admissions, whilst A will discuss happily the emails received on the issue, when asked to identify the computers used will only present the laptop. Cognitively, he only associates the admissions task with the one machine, despite often undertaking email activities related to admissions on the other machine. When questioned on

this apparent inconsistency in categorization of the PC as the ‘Admissions’ machine A recalls that once he was obliged to have the machine he set out to do all the emails for admissions on the PC as well. The department’s email service is available via IMAP – so all the computers A uses can handle email on just one account. The email client on the PC was set up by A to have a signature referring to his role as Admissions Tutor (and A made such a signature optionally available on the G4 machine which he characterizes as the main email machine). But despite being able to access his incoming email, and to send appropriately signed outgoing email, A used his ‘main’ email machine instead. A also reports that he discourages himself from using all the computers as equivalently general email machines by not sharing his address book across the machines. Thus on the research machine he has a limited set of email addresses just related to the work done on that machine. A’s account of the PC is simplified or ‘idealized’ and actually concerned with intentions rather than reality – and this is revealed in a curious way. The admissions work in his department makes extensive use of MS Access; it serves as a CRM system as well as for monitoring progress with applications paperwork and decision making. The fact that this is not available for the Mac OS X environment could be used by A to strengthen the case for calling the PC laptop the ‘Admissions’ machine, and thus to reinforce the cognitive partitioning of work onto machines. However, in relating the account of the usage of the machines A does not dwell on Access at all. The account reflects A’s projection of intentions – Projected Cognition – in that A has configured the machine to serve a number of related tasks within the overall task of handling admissions. A’s actual behaviour (e.g. use of email) does not always match the intention. A’s description of the intention is idealized

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because the real allocation of software and hardware resources to the larger tasks like admissions work is not as clean as intended. This has implications for the design of applications and for readability of intentions by visiting co-workers (see discussion below). A’s discussion of the other machines is also idealized. For example, A says of the Mac laptop and attached screen that he uses this setup for teaching work. For example, the most common usage scenario observed, and reported, is the task of lecture preparation; specifically, when creating Powerpoint slides the laptop is used to provide the overview and notes, whilst the individual slides are displayed on the Samsung monitor because of its conventional 4:3 aspect ratio. On further questioning it transpires that the portability of this machine (with its preferred operating system) is important – he takes it to lecture rooms around the University to deliver the lectures, and stores the material on this laptop. But A also takes it to meetings to make notes and to distribute those notes to others directly from the meeting room (using the wireless capability). In addition, there are aspects of teaching work (not lecture preparation) which A does on the G4, such as emailing students and colleagues, and preparing web materials for upload to the School’s servers. Indeed, it transpires that despite the fact that all the machines are linked to the School’s servers A considers the G4 to be the primary interface to the servers (possibly because this setup has the most screen estate) and thus it provides for effective file browsing and emailing simultaneously. A’s characterization of the G5 as a research machine is the least ambiguous. The machine has 3 TB of JBOD store with data gathered in the field. This machine is dedicated to the data processing – but has email facilities which are used for research focussed email, for example when sending graphical output from Matlab on the G5 to colleagues. However, A has been known to mount the G5 on the G4 as a volume, in order for graphs to be spread out over three screens for visual inspection. A’s physical configuration of the room makes the intended functional separation of the machines very obvious once it is explained. One of the key features of the setup is the arrangement of chairs in the room. By choosing a particular chair, A chooses a particular machine, and hence, cognitively for him, a main focus of working. What transpires from this account is that A’s characterization of the machines as functionally allocated is not complete – the tasks are too complex and the functional separations not readily maintained (witness the discussion of email above). One way to clarify this is to discuss with A the fact that he has actually assembled in his office a set of resources which he considers to be physically allocated cleanly but which actually he utilizes rather more incoherently than he thinks. Importantly, he says he is able to work with this distributed resource without becoming confused, so he obviously has some success at mapping underlying activities to the resources (and he reports having had two or more machines in his office for over

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10 years, so he is comfortable with multiple computer resources). But what he is actually doing is in fact only recoverable through introspection, observation and interview. A’s account of the usage does not reveal the true complexity, and only when observation is added, and the discrepancies and different cases of use highlighted do we get the fuller picture. This is not an uncommon finding, but does support the need for direct field observation as well as accepting reported behaviours and user-based descriptions of use. Additionally and more objectively, perhaps, one can deepen the discussion by noting that the six screens and four keyboards permit attention switching and task suspension with minimal disruption. The issue here is that A can switch between machines and ‘pick up where he left off’ without having to find the caret, locate and foreground the desired client/application and so forth. This is observed behaviour. The attention switch is manifest by swivelling the chair and reaching for and using the other keyboard/ mouse (of the two available when seated on the swivel chair) or getting up and moving to another chair. We will return to A’s set-up, and the interpretation it prompts in the Projected Cognition framework, in the later discussion. 4.2. User E User E is a male University student, in a Computer Science department, who is in his final year of undergraduate study. He was recruited to the study (Beale and Edmondson, 2007) after overhearing the researchers discussing the project, and letting them know he also used two machines. He was interviewed for approximately 90 min, using open questions and probing his answers for deeper understanding and self-knowledge. Because of his late involvement in the study the researchers were much more aware of the existing patterns of multiple computer use, and so used more focused questions, and were able to probe more deeply, despite the study period being shorter. However, all the material here is based on User E’s reported patterns of use, dissected with questioning, but not on observation. His set-up (as photographed by himself) is shown in Fig. 2. He uses two machines, both Macs: a laptop with Intel Dual core, with 80 GB hard disk, and a G5 Dual Processor desktop with a 40 GB disk – both running Mac OS X 10.4. Each has only one screen and they are not networked together by default, though they can be cross-mounted wirelessly for file transfer purposes. For around 6 months he tried a second screen linked to the desktop (giving a 1900 and a 2100 screen on that machine) – but did not like it, citing problems in moving the mouse larger distances, in not using the second monitor but instead using tabbed browsing or overlapping windows on a single monitor, and finding it hard to work out what he wanted to put onto which monitor. E reports he does not like to move his attention from one screen to the other when using the same application, the cause of some of his difficulties in using

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Fig. 2. User E’s working setup: laptop on left, desktop screen on right, machine under desk to right of chair.

multiple monitors, but is happy to move between multiple windows on one screen. He has used two machines for six years, upgrading the desktop and the laptop alternately, getting a new machine every 12–18 months. He reports that his ideal set-up would be two desktops, but needs a laptop for University-based work. However, he does not see any need for more than two machines. E maintains similar file structures on the two machines – but no attempt is made to match/synch the content. One machine does not back up the other. He states that this is to reduce the cognitive load in locating files: they are in the same position in a hierarchy on either machine. User E has two main scenarios of use. The first discussed was focused on gaming activities: he plays a lot of World of Warcraft – an internet-connected, multi-user roˆle playing game. This game is played in full-screen mode on the desktop machine, with the laptop used to run additional functionality needed for effective play: VOIP and text chat, to allow him to synchronize actions with others, and a web browser, which he uses to view reference material. In addition, he will run anything else he feels he needs on the laptop, in order to keep the desktop machine as uncluttered with other processes as possible. He reports that he does this in order to get the best possible performance from the game application. The second scenario concerns his work approach. E codes on the laptop, and also runs MSN and Skype there. It is worth noting that he reports having in excess of 120 Skype/messenger contacts, of whom 15–20 are high usage. In this scenario, he uses a web browser on the desktop, to refer to documentation and so on. He reports that he often has a lot of tabs open in the browser, but does not like too many windows open – and if he does have multiple windows, then he has them overlapping so he can flick between them, and does not minimize them into the dock (similar functionality to the Windows Taskbar). Note, however, that he finds it much easier to flick between overlapping open windows on one screen than having the windows on separate screens. He will also use the desktop machine

for document preparation, citing the additional screen size as the main reason for this. If this word processing requires more than one window open, he has them all onscreen and overlapping, eschewing the dock again. When word processing, he likes having the messenger application open on the other machine, since he is actively encouraging interruption, and the visibility of the application means it is easy for it to grab his attention when a contact messages him, or for him to see a new contact come online and hence instigate a conversation. This visibility and potential for interruption is enhanced by the application being on a separate monitor with more open screen estate. However, E reports that he likes being able to turn to that machine and just start typing, without having to manoeuvre the mouse and select the application: this functionality, important to User E, is only possible because of the additional caret position and foregrounded process offered by the second machine. This ability to use more than one application in the foreground crops up numerous times in E’s descriptions of his usage – being able to select applications and focus by a physical switching to different keyboard appears to be much less cognitively demanding for E than managing this on one machine. In both scenarios, he sticks rigidly to the allocation of activities to the specific machines. For each of these scenarios, however, he actually describes them as ‘tasks’ – so there is a ‘gaming’ task, and a ‘programming’ task, and a ‘document processing’ task – and for each of these tasks there is a set of applications and resources that he uses, each of which is allocated to a specific machine and which stays on that machine (only when really pressed in questioning could he recall this breaking – when programming, if he had more tabs open than could be easily displayed, he might use another web browser on the laptop as well as the default desktop). Notice, however, that the allocation is not application (machine) based: for example, depending on his ‘task’, the web browser will be on either the laptop or the desktop. He can and does use both machines for email, checking email only once a day, at the end. He downloads email only onto the desktop machine (using webmail from the laptop) around 10 emails per day. His rationale for this different treatment of reading email has a wider application: he wants to keep the laptop ‘clean’ with no superfluous material on it, and so keeps copies of emails on the desktop only, and downloads new applications onto the desktop – only if they get sufficient use will they migrate to the laptop, and then only the latest version – older versions may remain on the desktop machine, but never the laptop. User E comments that he hardly ever does one thing at a time – a single machine feels like it forces a bottleneck in his activities – though he is aware that it is not likely to be a computational bottleneck as much as a cognitive one. He says he views the two machines as a single resource – and has no notion of ‘main machine’. This corresponds with his ‘scenario’ approach to application (machine) allocation, in that both are used to support any one scenario,

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but in different ways depending on the scenario. In terms of E’s projection of cognition the patterns of usage reflect several overlapping concerns with functionality. The resources have to be managed as resources (the laptop needs to be kept clean), but they also (and at the same time) serve constituent functionalities in larger resource allocations which are aggregated for the scenarios. E’s Projected Cognition is thus multifaceted in a complex way not found in A’s account of resource allocation. 4.3. Multiple monitor usage When looking at users of multiple computers we do of course see multiple monitors. This is not technically necessary; many users have switches to allow one keyboard mouse and monitor to be used for several computers. Nonetheless, when looking at multiple computer usage one needs to be aware of the potential for patterns of behaviour to emerge that correspond to those already noted for users of single computers with virtual desktops and/or multiple monitors (Henderson and Card, 1986; Czerwinski et al., 2003; Hutchings et al., 2004; Hutchings and Stasko, 2004). Grudin (2001) studied how computer users work with two monitors and Ringel (2003) looked into the use of virtual desktops. Both reported the allocation of tasks to screens/desktops with the clear intention of keeping separate various activities. What is clear from accounts of such configurations is that the users report managing the detail of the work using monitors/screens to isolate activities, although the words used differ (task:subtask, primary:secondary, and so forth). It also appears to be the case that mental mapping of the screen estate is sometimes distorted to put greater distance between the focus of activity and distracting stuff on the periphery: ‘‘. . . I’ll usually have it in the far right hand corner (of the monitor on the right), because to me this is the farthest stretches of my desktop’’ (quoted in Grudin (op cit)). Multiple monitors and virtual desktops, working with a single computer, provide good opportunities for the distribution of activities with the intention of making the ‘more important’ at any time more prominent or foregrounded. However, in all these cases the user’s computational resources will be organized with the intention of focussing on a specific task at a specific time. The general purpose machine will be configured for the task (with or without subtasks) and their intention is expressed in that configuration. This is not to say that the Projected Cognition in such settings is somehow ‘simpler’ than that found with users of multiple computers. It is different because task switching is managed differently (see the discussion below). 4.4. Summary of observational studies We see from these case studies and reports that the users of computers solve the multi-tasking task, or they manage the configuration of a general purpose tool-set for specific

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tasks, in different ways. Multiple monitor users of single computers are much more at ease with reconfiguring the tool-set, knowing that they can switch to a different configuration with relative simplicity and without a strong sense of re-configuration itself being another task. For them it seems that the projection of cognition is into each task (noting that these tasks may actually be quite complex, involving two or more applications between which the user has to switch). It seems plausible to conjecture that the multi-monitor users are simply more practised at managing re-configurations required for task switching. Alternatively, or even in addition, their conception of tasks may be at a finer granularity and actually focussed on specific applications (document preparation, slide presentation, code writing . . .) with ‘‘other tasks’’ taking place elsewhere on the screens. These users do appear to equate tasks with applications in the reports offered by Grudin (op cit) and Ringel (op cit). Projected Cognition is, for these users, the foregrounding of specific applications and the implications they derive from that (so if they return to the screens after a break they can see which application is fronted and thereby what they were doing earlier). In contrast, the users of multiple computer configurations have a more complicated notion of task. Whether ‘‘gaming’’ or ‘‘doing admissions’’ the people concerned appear to need several applications running simultaneously, with locally determined foci but always within the overall task identified as such. For these users the Projected Cognition is found in the overall configuration (which machine is doing what, for example, in the case of User A above). The intention which is projected is thus ‘larger’ in scope, with more understanding of context by the user (who is aware of a set of resources available for the overall task). However, the allocation of resources to tasks may not be as well-structured as intended, so for A, at least, it seems the Projected Cognition reflects the projection of their will, not their skill, and this surfaces as apparently extravagant use of resources at the expense of skilled management of software applications. 5. General discussion In this section we will consider Projected Cognition, computer usage and design implications. In the next section we will draw some conclusions and look at implications for further work. 5.1. Computer usage and Projected Cognition Office computers, as general purpose machines, get used for a variety of tasks and activities. These may well increase in variety and complexity as the machines and screens become cheaper and the software more varied and specialized. Users will, we suggest, increasingly migrate to multiple monitors to assist multi-tasking in the office environment, with ready switching between applications, especially when these are clearly identified with tasks. Such

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configurations allow projection of cognition in readily recoverable (application focussed) ways. Computer supported cooperative working is supported in such environments because the participants can read the intentions of their colleagues and ‘follow’ what is going on, because they can see which application is in use, and hence which task is likely to be foregrounded. Some users may prefer to use multiple computing resources and project their cognition onto these resources in ways that make sense to them (permitting ready task switching between complex conceptions of task). However, their projection of cognition is not obviously readable by others and CSCW is not readily supported except insofar as any single computer comes to resemble the resource available in a more conventional setting. We recognize that User A’s research machine is a much more conventional resource when considered in isolation, and available for cooperative working as such. But User A’s projection of cognition generally within the office is not that clear and certainly not available to another colleague as a totality or general context when A is working with that colleague at the research machine. It is thus the case that A’s Projected Cognition is generally inscrutable. The point is that the projection is clear (enough) to A but may not be clear to others, nor need it be. The separation of complex intentions across space and machines makes it much easier for a visitor or co-worker to read specific intentions, but not the whole configuration. Indeed, User A reports that both his ‘‘research machine’’ and the ‘‘Admissions PC’’ are used in typical CSCW manner with a co-worker seated alongside. Remote cooperation is also cited for both machines whereby (i) the G5 is accessed by colleagues and used cooperatively with results being posted in a shared space; (ii) the PC is one of several in different offices with access to a remote admissions database which co-workers can access and work on cooperatively using the telephone for spoken discussion of the shared data. Both User A and User E reveal complexity of task conception and thus necessarily of resource allocation. Conventionally we might expect to see a single powerful computing resource, with appropriate monitors and software, available for meeting all functional needs (but with a great deal of application switching when changing from, say, admissions to lecture preparation). User A prefers a solution which allocates multiple copies of software to multiple computers (along with special purpose software on some computers) in order to permit multiple offerings of specific functionalities. User E’s scenario based allocation is interesting in that the complex functionalities required are served by just two machines, but in different configurations for the different scenarios, with relative straightforward switching between the two – the projection is quite dynamic. Both users project their intentions at the level of task description they use in discourse with others. They do not relate their tasks to single applications (there is no ‘Admissions’ application, and for E the notion of gaming goes beyond the specific software for the game itself).

5.2. Projected Cognition and implications for design We have noted above that there is a need to understand how to design systems and interfaces to support Projected Cognition and its utilization. Users want to do things with their computer resources and they need the expression of their intention to be matched by the way the resources present themselves. It seems that for many a single computer and screen achieves this – where the intentions are expressed rather single-mindedly in ways matched to single applications. Suites of software permit related applications to present functionality in ways considered a good match to the intentions of the users. However, as experience with computer resources increases it becomes apparent that some users find task switching is increasingly a task itself. A good example here is the file history system in, say, a word processing application. The listing available is simply a chronological ordering. But if using the word processing application is no longer a major task, and has become instead an activity which is just a subcomponent of several other tasks, then the user really needs to have subdirectories, or ‘projects’, or some sort of organizational structuring in the file history to make available those files relevant to the real task, not the word processing task. The same story can be told in relation to spreadsheets and databases. Indeed, in the latter case it would be good to be able to have directory structures/organizations in the set of queries available in relation to a single datatable resource. Such a resource may serve several major tasks (‘using the database’ is no longer a task of any interest – the intention is ‘what it is used for’, not ‘that it is used’) but the queries just appear listed in alphabetical order (one has to resort to creating structures using numerical prefixes). 6. Conclusions We are claiming in this paper that the conception of Projected Cognition is a useful extension to the wellreported concept of Distributed Cognition. We believe it adds clarity to observational work to be able to consider user intentions. In complex situations users may not project their cognition coherently and this can make analysis of observed behaviour difficult, but it is our view that more conventional accounts of Distributed Cognition cannot yield insight or clarity in such settings. In the case of User A we wonder how a sensible account of his office set-up could be delivered in terms of Distributed Cognition as conventionally conceived. User E’s scenario based approach to computer use is complex and dynamic and not readily presented without Projected Cognition. The notion of Projected Cognition that we have introduced and illustrated has utility beyond analysis of comparatively esoteric office set-ups. After all, most computers have just one screen, and most people use just one computer. Where people use more than one computer familiarity is provided through deployment of a common

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operating system (PC users in offices may have a PC at home, and be comfortable using a PC in a public library or an internet cafe´: they all run a Microsoft operating system and familiarity with its utility is plausibly assumed). For the majority of people tasks are also plausibly identified with applications – that is what applications are all about! However, as familiarity with applications increases, and as tasks become more varied and complex for any individual, so it is that mapping tasks to applications will become more complex because the tasks will have to be considered in terms of subtasks/activities and these will have to be related to applications. Such users will, we consider, project their intentions onto their resources. They will configure the resources to suit their needs in ways which are considerably more complex than, say, tailoring menus to suit personal preferences. However, it would be a mistake to assume that Projected Cognition is only to be found where complex resource configuration is found. The difficulties faced by more conventional users may be readily understood through consideration of the Projected Cognition displayed by such users. User-centred design, therefore, is about providing for Projected Cognition with single users of individual machines with single screens, as much as it is about providing for users of complex office equipment provision. Conventionally it is often assumed that making systems more accessible means making them more ‘obvious’ in some sense (similarity to other systems, or whatever). What we learn from considering Projected Cognition is that users may want to project intentionality onto their systems and thus usability is as much concerned with providing for and supporting such projection. The question here is whether a user’s conception of a task is projected in detail sufficient to cause usability issues when ‘trivial’ details of application configuration are ‘wrongly’ set. This can be contrasted with a user who reads the applications’s functionality into their task conception, modifies that, and is effectively influenced by the Distributed Cognition recoverable from the application. This is likely to be a fruitful theme for extending and reanalyzing usability conceptions and studies, as well as conducting new studies. One ‘take-home’ message from the work reported here is that support for task complexity within a single computing resource needs to become much more sophisticated. One could envisage some sort of project-based application harness which loads in a whole set of applications, with preferences, resources, etc., all at the click of a button. Note, this is not the same as having different windows/panes open in given applications; one actually needs the applications to be open in multiple, different, instantiations each with its own, task-specific, preferences and history. This is currently only easily achieved by switching to the use of multiple computers.2 However, it should be recognized that the 2 As these resources get cheaper this might become simpler than complex interface software to support complex task switching. Alternatively, if futuristically, widespread deployment of virtual machines for personal use might serve the same ends.

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problem is not entirely technical. As users become more familiar with applications, and as work-practices become more fluent, the desire to project complex task conceptions onto the resources will increase. But, the Projected Cognition will become more individual because the tasks will become less routine and application bound. In short, work will be less patterned by the machines available to support it. This means that design of software and systems has to become concerned for individual cognitive style in ways more complex and subtle than, say, simple menu tailorability. The above points are open to empirical investigation. Where a user can be put in a situation such that they have to use a multiplicity of resources to accomplish a complex task, their resource configuration can be monitored/ observed and their account recorded. More realistic (large, comprehensive, time-consuming . . .) empirical/ethnographic studies can be undertaken within groups of people doing the sorts of things done by User A and User E above. User A is not the only Admissions Tutor in UK; how do others manage the resources for this task? And of course we should not neglect the language used in accounts of complex resource management – terms used earlier in relation to Projected Cognition include ‘imposition’, ‘allocation’, ‘intention’, ‘will not skill’, and we might expect users to talk in terms of ‘getting the computer to do what they want’ and suchlike, instead of in terms of ‘using the machine to do x’, or ‘ being trained to do y’, or whatever . . . (which might thereby imply ‘simply’ operating the machine for its identified purpose). Indeed there is a whole domain of related issues to be considered in the ‘deskilling’ versus ‘reskilling’ debate surrounding the introduction of computerized equipment in replacement of equipment dependent on human skill (computerized machine tools in metal workshops, for example) – but that would take us beyond our remit here. Suffice to say that ethnographic and empirical work informed by, and illuminating of, the notion of Projected Cognition is possible just as it has been for the original, and broader, concept of Distributed Cognition. The second take-home message is that whilst individual users will probably increasingly become comfortable projecting their intentions onto complex resources it is not so obvious that cooperative working will be fostered. The reasoning here is that as we saw with User A the Projected Cognition in complex resource settings will be more individual and less patterned by the structure/requirements of any applications. CSCW is often helped by co-workers having familiarity with the same applications – an application serves to support a shared context. Where activity is not predicated so strongly on use of a specific application the opportunities for conventionally patterned CSCW seem weakened. One way forward would be to ensure that for CSCW the users work within a more conventionalized format of resource configuration – specific applications on specific resources. A’s use of a PC for admissions means that his admissions co-workers can work with him without

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attending to the rest of his Projected Cognition in his office. More fancifully, perhaps, support of complex resource allocation could itself become more regularized and ‘application like’. However, this poses different problems (establishing and then supporting the conventions required). This too is open to empirical study – the readiness with which a group of co-workers take to the availability of application harnesses for systematizing the co-ordination and configuration of resources would be a measure of the value of the insight that such things are needed. Different styles of harness (with varying user control) could be trialed in experimental settings and multi-computer and multi-monitor usage could be compared. As before, a major difficulty is that the tasks being undertaken have to be realistically large. Additionally, the development of effective harnesses is probably non-trivial. The overall take-home message, however, is that Projected Cognition is a worthwhile extension to the general notion of Distributed Cognition. Users do things with intent, and often it is important to them and to others working with them that the intentions are clear, and readily supported. In the general case, therefore, systems and interface design need to develop in ways which permit the user’s intentions to map clearly and recoverably onto the resources. One is reminded here of Norman’s ‘Gulfs of Execution and Evaluation’ (Norman, 1986; Abowd and Beale, 1991) but the focus is now broader. We are no longer concerned to make sure that mouse movements map well onto the screen, or whatever, but rather to ensure that a user’s conception of the task of, say, booking a holiday trip, is well matched to the suite of resources available for that without distractingly frequent switching between task components or details. References Abowd, G., Beale, R., 1991. In: Diaper, D., Hammond, N. (Eds.), HCI’91: People and Computers VI. Cambridge University Press, pp. 73–87. Bærentsen, K.B., 1989. Mennesker og maskiner. In: Hedegaard, M., Hansen, V.R., Thyssen, S. (Eds.), Et virksomt liv: Udforskning af virksomhedsteoriens praksis. Aarhus Universitetsforlag, Aarhus, pp. 142– 187. Bannon, L.J., 1995. Issues in computer supported collaborative learning. In: O’Malley, C. (Ed.), Computer Supported Collaborative Learning. Springer-Verlag, pp. 267–281. Beale, R., Edmondson, W., 2007. Multiple carets, multiple screens and multi-tasking: new behaviours with multiple computers. In: HCI2007, BCS, Lancaster, pp. 55–64. Brown, B., Green, N., Harper, R., 2002. Wireless World: Social and Interactional Aspects of the Mobile Age. Springer, London, New York. Czerwinski, M., Smith, G., Regan, T., Meyers, B., Robertson, G., Starkweather, G., 2003. Toward characterizing the productivity benefits of very large displays. In: Rauterberg, M. (ed.), Human– Computer Interaction – INTERACT’03, pp. 9–16. de Le´on, D., 1999. Building thought into things. In: Bagnara, S. (ed.), 3rd European Conference on Cognitive Science. Siena, Italy, pp. 37–46. Edmondson, W.H., 2001. A taxonomical approach to special needs design in HCI. In: Stephanidis, C. Proceedings of HCI International, held in

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