Archive
DwI Method

■ How to influence user behaviour
■ 12 inspirational design patterns in poster form (plus 35 more)
■ Grouped into 6 ‘lenses’ giving different perspectives

Design for Behaviour Change: The Design with Intent Toolkit v. 0.9
Download the poster (it’s a 1.3 MB PDF) – now also includes A4 pages for each lens, for easier printing  [Alternative link]

***Please note***
This is an old version of the toolkit – the newer Design with Intent toolkit v.1.0 is also available and is much better!

 
 
 
 
 
 

Start with the problem

You have a product, service or environment—a system—where users’ behaviour is important to it working properly (safely, efficiently), so ideally you’d like people to use it in a certain way.

Or maybe you have a system where it would be desirable to alter the way that people use it, to improve things for users, the people around them, or society as a whole.

How can you modify the design, or redesign the system, to achieve this: to influence, or change users’ behaviour?

The design patterns

The Design with Intent Toolkit aims to help designers faced with ‘design for behaviour change’ briefs. The poster* features 12 design patterns which recur across design fields (interaction, products, architecture), and there are also 35 more detailed here on the website. Some of the names will be unfamiliar, but we hope the patterns and examples will be understandable, and inspire your own concepts.

Think about how you might apply the ideas to your brief, and what could work given what you know about the problem. If you get stuck, try combining ideas from different patterns: many real examples can be thought of as using two or more patterns.

The patterns are grouped into six ‘lenses’, each offering a different worldview on design and behaviour. The lenses allow you to ask “How might someone else approach the problem?” and ought to help you think outside your initial perspective (or your client’s):

Architectural lens

Errorproofing lens

Persuasive lens

Visual lens

Cognitive lens

Security lens

A different approach: using the patterns as questions
Nedra Kline Weinreich, author of Hands-on Social Marketing, has created a clever Design Approach for Behaviour Change worksheet based on the 12 patterns from the Design with Intent poster, by re-framing each of the patterns as a question. This is a great idea, turning the patterns into cues for you to think about relative to your problem. After working through the questions, you pretty much end up with a set of possible solutions.


What sort of behaviour are you trying to achieve?

See the next page…

*Lockton, D., Harrison, D.J., Stanton, N.A. Design for Behaviour Change: The Design with Intent Toolkit v.0.9, Uxbridge: Brunel University 2009 (ISBN 978-1-902316-6-1 print; 978-1-902316-63-5 eBook), http://www.designwithintent.co.uk

____________________
The Design with Intent Toolkit v0.9 by Dan Lockton, David Harrison and Neville A. Stanton
Introduction | Behaviour | Architectural lens | Errorproofing lens | Persuasive lens | Visual lens | Cognitive lens | Security lens

dan@danlockton.co.uk

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The ‘Design with Intent method‘, on which I’m working as the first part of my PhD, has been fairly sparsely reported on this blog. This is intended to be an innovation method for helping designers faced with “behaviour change” problems come up with useful solutions, or in situations where helping users to use a product or system more efficiently would be worthwhile. The ideas that have gone into it are (mostly) the ‘positive’ side of what we’ve discussed on the blog for the last few years.

The brief series of posts from last summer about getting people to do things in a particular order, which more recently got some attention from Kati London’s ‘Persuasive Technologies: Designing the Human‘ class at NYU’s Interactive Telecommunications Program (with some very interesting student commentary) was based on a relatively early iteration of the method. At some point, I’ll draw up a comparison between the iterations of the method, even if simply for my own clarity of mind – it’s helpful to record why I changed different aspects along the way.

The initial plan had been for it to be almost TRIZ-like in terms of ‘prescribing’ relevant design techniques to help achieve particular target behaviours. The first few iterations of the method thus took the form of a kind of hierarchical decision tree. Live|Work‘s very helpful advice to me last summer to reduce the prescriptive nature slightly by having a kind of illustrated ‘idea space’ led – in due course – to the version tested in the pilot studies carried out in late 2008 and earlier this year. What the studies showed, among other things (to be reported in the Persuasive 2009 paper!) was that many designers, when asked to come up with concept solutions, don’t really like working from categories and rules and hierarchies, even where they would be useful. Some do (and with impressively exhaustive efficiency), but many don’t: they preferred to use the method as a kind of well of inspiration, without necessarily using it in any kind of procedural way.

So – and there’s another reason for this, too, which I’ll be able to announce at some point – it seemed sensible to redesign the method to accommodate both modes of working: a ‘prescription mode’ for the more procedure-driven designer, and an ‘inspiration mode’ for the designer who prefers less bounded creativity (a bit more like IDEO’s method cards, but not quite as unstructured as the Oblique Strategies). The inspiration mode is essentially a very simplified, flattened set of design patterns loosely grouped into different ‘lenses’ representing views on influencing behaviour, but with no real structure beyond that. It’s more of a ‘toolkit’ than a method, and because of its relative simplicity it seems worth releasing to get some feedback without too much more work. The “eight design patterns for errorproofing” post from a few weeks back is a kind of preview of part of it.

On Monday morning, then, there’ll be a large poster available to download on the blog, and I’ll do a series of posts forming the online component of the toolkit. So please, feel free to comment, make suggestions for improvements or better examples, or pick holes in it!

P.S. I’m aware the blog needs a bit of housekeeping in terms of making the sidebar work properly again in IE, fixing the very out-of-date blogroll, and my appalling sloth in replying to people who’ve very kindly sent very interesting links and ideas. I will try to get round to it all soon.

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UPDATED (7 April): Here’s an ‘author version preprint’ of the paper, Influencing Interaction: Development of the Design with Intent Method [PDF, 1.6MB]. At some point soon this version of the paper will downloadable from Brunel’s research archive, while the ‘proper’ version will be available in the ACM Digital Library. ACM requires me to state the following alongside the link to the preprint:

© ACM, 2009. This is the authors’ version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version will be published in Proceedings of Persuasive 2009: Fourth International Conference on Persuasive Technology, Claremont, CA, 26-29 April 2009, ACM Digital Library. ISBN 978-1-60558-376-1.

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Claremont Graduate University - photo by Katherine H on Flickr

I’m pleased to announce that a paper I submitted to Persuasive 2009, at the Claremont Colleges, California (26-29th April) has been accepted, so I’ll be presenting ‘Influencing Interaction: Development of the Design with Intent Method’ on Monday 27th April.

The paper builds on the ideas I presented at Persuasive 2008 (the paper), detailing the development of the ‘Design with Intent Method‘, a ‘suggestion tool’ for designers faced with briefs involving influencing user behaviour, and the results of a series of pilot studies to test the usability of the method.

At the time of submitting the paper (New Year’s Eve, 6pm!), the pilot studies were still going on (poor planning by me), so (as the reviewers noted!) the paper’s conclusions are fairly weak, and there are quite a few revisions I need to make before submitting the final version: the next couple of weeks are going to require some fairly intense work in that vein. But it’s great to have been accepted: Persuasive 2008 was fantastic, incredibly useful in terms of meeting people and getting feedback on the proposed research, and I’m hoping 2009 will be just as good. The big-name speakers include BJ Fogg, originator of the Persuasive Technology field, Mihály Csíkszentmihályi (of ‘Flow‘ fame), and Brenda Laurel (author of Design Research: Methods and Perspectives, which I’ll admit I haven’t yet got round to reading, largely because of Nigel Cross’s review, but maybe I should find the time!). As always, though, it’s the chance to talk to and get to know other people working on similar problems, or offering a different point of view on the field, which is especially interesting.

The proceedings are going to be published by the ACM (last year’s were published by Springer), but I don’t have any more details at this stage. I’ll post a preprint version of the paper here once it’s ready, of course.

Many thanks to my co-authors: my supervisors Professor David Harrison (Brunel) and Professor Neville Stanton (Southampton) for their help, and Tim Holley whose insights into improving and using the method were extremely useful. Thanks too to all the other pilot study participants, and also to the Royal Academy of Engineering, who very kindly awarded an international travel grant to help me attend the conference. I am aware of the hypocrisy of flying halfway round the world to talk (in part) about influencing more environmentally friendly behaviour, and the cognitive dissonance is headache-inducing. Why there aren’t more live, online academic conferences, I don’t know.

Here are the abstract and ACM meta-stuff for the paper:

Influencing Interaction: Development of the Design with Intent Method
Dan Lockton¹, David Harrison¹, Tim Holley², Neville A. Stanton³
¹Cleaner Electronics Research Group, Brunel Design, Brunel University, Uxbridge, Middlesex UB8 3PH, United Kingdom
²Product Design Programme, Brunel Design, Brunel University, Uxbridge, Middlesex UB8 3PH, United Kingdom
³School of Civil Engineering & the Environment, University of Southampton, Southampton, Hampshire SO17 1BJ, United Kingdom

ABSTRACT
Persuasive Technology has the potential to influence user behavior for social benefit, e.g. to reduce environmental impact, but designers are lacking guidance choosing among design techniques for influencing interaction. The Design with Intent Method, a ‘suggestion tool’ addressing this problem, is described in this paper, and applied to the briefs of reducing unnecessary household lighting use, and improving the efficiency of printing, primarily to evaluate the method’s usability. The trial demonstrates that the DwI Method is quick to apply and leads to a range of relevant design concepts. With development, the DwI Method could be a useful tool for designers working on influencing user behavior.

Categories and Subject Descriptors
H.1.2 [Models and Principles]: User/Machine Systems – human factors, software psychology. H.5.2 [Information Interfaces and Presentation (e.g. HCI)]: User Interfaces – theory and methods, user-centered design.
General Terms
Design, Human Factors.
Keywords
Persuasive technology, behavior change, sustainability, energy, interaction design, design methods, innovation methods.

On other matters, I’m proud to say that Planetizen, the urban design and planning community and blog has named Design with Intent one of its Top 10 Websites for 2009 – a nice accolade given how broad the scope here is beyond urbanism and architecture! Some of the other websites recommended are well worth a deeper read – On the Commons, Digital Urban, Infranet Lab and Gapminder stood out for me.

Adding that Planetizen accolade to Six Revisions’ inclusion of the blog in its ’20 websites to help you master user interface design’, it’s clear that, if nothing else, the themes we cover here really do meander about over conventional disciplinary boundaries. It’s all about people interacting with designed systems, whether they’re concrete plazas, electric kettles or confirmation dialogues, and I’d like to think the similarities are worth investigating.

Photo of Claremont Graduate University by Katherine H on Flickr

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Go straight to the patterns

One view of influencing user behaviour – what I’ve called the ‘errorproofing lens’ – treats a user’s interaction with a system as a set of defined target behaviour routes which the designer wants the user to follow, with deviations from those routes being treated as ‘errors’. Design can help avoid the errors, either by making it easier for users to work without making errors, or by making the errors impossible in the first place (a defensive design approach).

That’s fairly obvious, and it’s a key part of interaction design, usability and human factors practice, much of its influence in the design profession coming from Don Norman’s seminal Design of Everyday Things. It’s often the view on influencing user behaviour found in health & safety-related design, medical device design and manufacturing engineering (as poka-yoke): where, as far as possible, one really doesn’t want errors to occur at all (Shingo’s zero defects). Learning through trial-and-error exploration of the interface might be great for, say, Kai’s Power Tools, but a bad idea for a dialysis machine or the control room of a nuclear power station.

It’s worth noting a (the?) key difference between an errorproofing approach and some other views of influencing user behaviour, such as Persuasive Technology: persuasion implies attitude change leading to the target behaviour, while errorproofing doesn’t care whether or not the user’s attitude changes, as long as the target behaviour is met. Attitude change might be an effect of the errorproofing, but it doesn’t have to be. If I find I can’t start a milling machine until the guard is in place, the target behaviour (I put the guard in place before pressing the switch) is achieved regardless of whether my attitude to safety changes. It might do, though: the act of realising that the guard needs to be in place, and why, may well cause safety to be on my mind consciously. Then again, it might do the opposite: e.g. the steering wheel spike argument. The distinction between whether the behaviour change is mindful or not is something I tried to capture with the behaviour change barometer.

Making it easier for users to avoid errors – whether through warnings, choice of defaults, confirmation dialogues and so on – is slightly ‘softer’ than actual forcing the user to conform, and does perhaps offer the chance to relay some information about the reasoning behind the measure. But the philosophy behind all of these is, inevitably “we know what’s best”: a dose of paternalism, the degree of constraint determining the ‘libertarian’ prefix. The fact that all of us can probably think of everyday examples where we constantly have to change a setting from its default, or a confirmation dialogue slows us down (process friction), suggests that simple errorproofing cannot stand in for an intelligent process of understanding the user.

On with the patterns, then: there’s nothing new here, but hopefully seeing the patterns side by side allows an interesting and useful comparison. Defaults and Interlock are the two best ‘inspirations’ I think, in terms of using these errorproofing patterns to innovate concepts for influencing user behaviour in other fields. There will be a lot more to say about each pattern (further classification, and what kinds of behaviour change each is especially applicable to) in the near future as I gradually progress with this project.

 

Defaults

“What happens if I leave the settings how they are?”

■ Choose ‘good’ default settings and options, since many users will stick with them, and only change them if they feel they really need to (see Rajiv Shah’s work, and Thaler & Sunstein)

■ How easy or hard it is to change settings, find other options, and undo mistakes also contributes to user behaviour here

          Default print quality settings  Donor card

Examples: With most printer installations, the default print quality is usually not ‘Draft’, even though this would save users time, ink and money.
In the UK, organ donation is ‘opt-in’: the default is that your organs will not be donated. In some countries, an ‘opt-out’ system is used, which can lead to higher rates of donation

Interlock

“That doesn’t work unless you do this first”

■ Design the system so users have to perform actions in a certain order, by preventing the next operation until the first is complete: a forcing function

■ Can be irritating or helpful depending on how much it interferes with normal user activity—e.g. seatbelt-ignition interlocks have historically been very unpopular with drivers

          Interlock on microwave oven door  Interlock on ATM - card returned before cash dispensed

Examples: Microwave ovens don’t work until the door is closed (for safety).
Most cash machines don’t dispense cash until you remove your card (so it’s less likely you forget it)

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Lock-in & Lock-out

■ Keep an operation going (lock-in) or prevent one being started (lock-out) – a forcing function

■ Can be helpful (e.g. for safety or improving productivity, such as preventing accidentally cancelling something) or irritating for users (e.g. diverting the user’s attention away from a task, such as unskippable DVD adverts before the movie)

Right-click disabled

Example: Some websites ‘disable’ right-clicking to try (misguidedly) to prevent visitors saving images.

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Extra step

■ Introduce an extra step, either as a confirmation (e.g. an “Are you sure?” dialogue) or a ‘speed-hump’ to slow a process down or prevent accidental errors – another forcing function. Most of the everyday poka-yokes (“useful landmines”) we looked at last year are examples of this pattern

■ Can be helpful, but if used excessively, users may learn “always click OK”

British Rail train door extra step

Example: Train door handles requiring passengers to lower the window

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Specialised affordances

 
■ Design elements so that they can only be used in particular contexts or arrangements

Format lock-in is a subset of this: making elements (parts, files, etc) intentionally incompatible with those from other manufacturers; rarely user-friendly design

Bevel corners on various media cards and disks

Example: The bevelled corner on SIM cards, memory cards and floppy disks ensures that they cannot be inserted the wrong way round

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Partial self-correction

■ Design systems which partially correct errors made by the user, or suggest a different action, but allow the user to undo or ignore the self-correction – e.g. Google’s “Did you mean…?” feature

■ An alternative to full, automatic self-correction (which does not actually influence the user’s behaviour)

Partial self-correction (with an undo) on eBay

Example: eBay self-corrects search terms identified as likely misspellings or typos, but allows users the option to ignore the correction

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Portions

■ Use the size of ‘portion’ to influence how much users consume: unit bias means that people will often perceive what they’re provided with as the ‘correct’ amount

■ Can also be used explicitly to control the amount users consume, by only releasing one portion at a time, e.g. with soap dispensers

Snack portion packs

Example: ‘Portion packs’ for snacks aim to provide customers with the ‘right’ amount of food to eat in one go

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Conditional warnings

■ Detect and provide warning feedback (audible, visual, tactile) if a condition occurs which the user would benefit from fixing (e.g. upgrading a web browser), or if the user has performed actions in a non-ideal order

■ Doesn’t force the user to take action before proceeding, so not as ‘strong’ an errorproofing method as an interlock.

Seatbelt warning light

Example: A seatbelt warning light does not force the user to buckle up, unlike a seatbelt-ignition interlock.

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Photos/screenshots by Dan Lockton except seatbelt warning image (composite of photos by Zoom Zoom and Reiver) and donor card photo by Adrienne Hart-Davis.

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Design with Intent Pilot Study

For the last few weeks I’ve been setting up and running the first few trials of the ‘Design with Intent Method’, the design/innovation tool I’ve (embarrassingly sporadically) talked about on the blog over the last year.

It’s essentially an innovation method to help designers given a brief involving influencing user behaviour. Based on describing the ‘problem’, the DwI Method aims to suggest appropriate design techniques (with real examples from different fields) to inspire concepts with the potential to influence user behaviour towards the ‘target’. The techniques suggested range from those which really would help users to those which probably don’t: deciding which approaches are actually worthwhile is part of the process… I won’t go into it too much here (yet) but hopefully the method captures or will at least address most of the arguments and caveats that we’ve discussed here over the last 3 years.

As it’s developed from a fairly simple box structure through a giant hierarchical tree (as in the corner of this poster [PDF]), to the current ‘idea space’ iteration partially visible in the photo above, I’ve ‘tested’ it plenty of times with myself and informally with colleagues, applying it to different briefs, but the current programme of pilot studies is the first time it is being tried out by ‘real people’, mostly recent design graduates or final-year design students. These pilot studies are primarily about assessing the usability of the method ahead of larger group studies assessing its usefulness – if that makes sense – but they still involve the participants applying the method to particular design problems and seeing what kind of concepts it suggests. So far, the results have been extremely interesting – I can’t say any more yet.

At some point, there will be an online version in one form or another, but for the moment, if you’re in the London area, are a designer or someone interested in behaviour change, and would like to participate in an individual pilot study session in January, please let me know – dan@danlockton.co.uk. There are only going to be a few sessions; they take about 2½ hours each, during the week, taking place at Brunel University (Uxbridge, end of the Piccadilly and Metropolitan lines) and bear in mind half the participants will be ‘controls’ and so won’t actually be getting the DwI Method at all. The most I can pay you for your time/travel is £10. If that still sounds attractive, get in touch! I’ll update this post when all the slots are filled.

Equally, if your company or design team would like to participate in a ‘full’ trial of the DwI Method sometime in spring 2009 – trying out the method on real problems – then please do get in touch too.

Dan Lockton

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This is a kind of exploration of some ideas I worked on a while ago as part of my research, and have only just come back to, in order to tidy them up a bit. I’m putting it online as a way – perhaps – to get some comments/criticism, and also to enable me to refer to it, if necessary, in future blog posts. If I’m honest, classifications and taxonomies fatigue me quite a lot; coming up with ideas and making and testing them is a lot more fun. But sometimes they’re useful. I hope this one is.

If we think about how products are used, it’s clear that changes can result from the products themselves changing, users changing their behaviour, or a combination of both.

At the University of Bath, Ed Elias, Elies Dekoninck and Steve Culley [1] have captured these possibilities with a 2 × 2 matrix (Figure 1), in which ‘new products’ and ‘old products’ are compared with ‘new user behaviour’ and ‘old user behaviour’.

Diagram by Ed Elias

Along these lines, it’s possible to consider technology change (via design) and attitude change (via education) as two routes to achieve overall behaviour change. Especially in the sustainable design field, the emphasis is often on one strategy or the other, even though the routes are by no means mutually exclusive, as the ‘Design for New User Behaviour’ title implies in the matrix.

Loughborough’s Debra Lilley, Vicky Lofthouse and Tracy Bhamra [2] describe three ‘solutions to limit socially and environmentally undesirable behaviours’: Educational intervention – which corresponds closely to attitude change; Technological intervention – corresponding to technology change; and Product-led intervention – closely aligned with Elias et al’s Design for New User Behaviour.

Further consideration of the possibilities in this area, and how to represent them, led me to the development of a ‘Behaviour Change Barometer’. This diagram attempts to illustrate somewhat more nuanced ‘cases’ of behaviour change, and which factors are present or absent in each case. It ought to be applicable to many kinds of behaviour change with products, not just environmentally-related ones; equally, read ‘products/services/systems’ for ‘products’ to allow wider applicability. The barometer metaphor is stretched slightly, but it seemed appropriate given that the diagram’s mapping change.

A Behaviour Change Barometer. Diagram by Dan Lockton

Table to accompany Behaviour Change Barometer. Diagram by Dan LocktonThe same information is presented in tabular form here: in essence, there are six variables involved, with the possibility space divided into quadrants.

The focus of my research is on the intersection of technology change and attitude change (Quadrant 3): the design of products (and systems) which, through new product behaviour, change user behaviour. Quadrant 3 will be discussed last here – before that, it’s useful to run through the other quadrants briefly.

Quadrant 1 Status Quo Diagram by Dan LocktonQuadrant 1: Status quo

In the first quadrant, no overall behaviour change results.

It makes sense to describe case 1b first – this is the absolute ‘no change’ case, where there is no change in the actual functions of the products (they might be new products, but they don’t do anything different to the old products), people use them in the same way they did before, and users have no understanding or mindfulness of the issues around behaviour change.

Case 1a describes situations where the products’ functions have been changed, but users make no use of this, and have no understanding or mindfulness of the issues involved (e.g. a washing machine offers a new ‘eco’ mode alongside the other settings, but a user doesn’t use it). Therefore no overall behaviour change results, despite product improvement.

In 1c, users have an understanding of the issues, and may be mindful of their behaviour and its impacts, but nevertheless don’t change what they do, and continue to use products in the same way as before – e.g. someone who knows that leaving a television on standby wastes electricity, but doesn’t act on this understanding. Again, no overall behaviour change results, despite improved user understanding.

This quadrant encompasses much current behaviour with energy-using consumer products – improved education and improved technology have raised awareness of environmental issues, and allowed products to be operated more efficiently, but if users don’t act accordingly, there will be no overall change in behaviour.

Quadrant 2 New user behaviour with existing products. Diagram by Dan LocktonQuadrant 2: New user behaviour with existing products

Educating users about the implications of their behaviour is generally done with the intention that users will follow through and actually change the way they use products (if they don’t change, this is 1c as described above). If this is successful – e.g. a campaign to persuade people to keep their car tyres inflated correctly to save fuel – then new user behaviour occurs with existing products, and no design or engineering changes are needed to the products. Overall, there is a change in behaviour.

The scope of this quadrant corresponds closely with much current government policy of using social marketing, public education campaigns and so on – employing persuasion and rhetoric to drive attitude change as a foundation for behaviour change. There are many ways that this quadrant could be subdivided into behavioural cases, but from the point of view of the current study, this won’t be explored further here.

Quadrant 4 Existing user behaviour with new product behaviour. Diagram by Dan LocktonQuadrant 4: Existing user behaviour with new product behaviour

Where new products themselves behave differently in use, yet allow users to maintain their existing behaviours, overall behaviour change results without users necessarily needing to understand the issues involved. No persuasion occurs. For example, compact fluorescent lightbulbs, from the user’s point of view, do not require any different user behaviour to tungsten filament bulbs, but in operation they always result in new product behaviour. A refrigerator door which automatically closes itself if left ajar does not, again, require the user to do anything different, but the product itself behaves differently to accommodate existing user behaviour.

This quadrant would include the major proportion of ‘eco-products’ available, most of which are designed to allow the user to change routines and behaviours as little as possible; there are many possible ways the category can be subdivided further according to various other factors.

Quadrant 3 New user behaviour with new product behaviour. Diagram by Dan LocktonQuadrant 3: New user behaviour with new product behaviour

In the cases described by this quadrant, both product behaviour and user behaviour change, resulting in an overall behaviour change. The behaviour change can be driven entirely by functional changes to the product, or by mindful user understanding, or by both, but the products are designed to lead to this. This is Design with Intent.

These are products that persuade, guide or force – influence – users to change the way they interact with them. A common factor is that there is a perceived affordance change with the product: it somehow indicates that a change in behaviour is needed (compared with quadrant 4 where there is no such indication). This quadrant is where my research is focused.

In case 3a, the perceived affordance change does not reflect actual functional change to the product, yet it influences users to change their behaviour. For example, a washing machine which gives users an ‘estimated cost’ for each mode still embodies all the same functions as one which doesn’t – the user can choose to ignore the recommendation, but is influenced to choose the most economical mode, and thus a change in product behaviour is likely to result from the change in user behaviour. This is where much of the Persuasive Technology research seems to fit.

3c is the case where a user need not think about the issues involved, but will still behave differently due to functional changes to the product – e.g. a washing machine which automatically determines the most efficient settings for a particular load, and silently carries them out, doesn’t require the user to understand what’s going on, but does end up changing the user’s behaviour (removing inefficient decisions) and thus the product behaviour changes too. These products have the potential to be complex, especially where automation is required, but need not be. Something as simple as removing an option from a menu changes the user’s behaviour (prevents him or her choosing it) but doesn’t require the user to think about it.

Finally, returning to the centre of the quadrant, 3b describes cases where user understanding, alongside functional changes to the product and perceived affordance change, lead to user and product behaviour change in practice: these are the real core of what this study is about and where, I hope, I’ll be able to make advances in understanding useful to designers and anyone else working in the field of influencing user behaviour. These are interesting products, potentially involving lots of factors and effects but not necessarily complex in themselves.

[1] Elias, E W A, Dekoninck, E A, Culley, S J. The Potential for Domestic Energy Savings through Assessing User Behaviour and Changes in Design. EcoDesign2007, 5th International Symposium on Environmentally Conscious Design and Inverse Manufacturing, Tokyo, 2007
[2] Lilley, D, Lofthouse, V, Bhamra, T. Towards Instinctive Sustainable Product Use. 2nd International Conference: Sustainability Creating the Culture, Aberdeen, 2005. Available here [PDF].

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