Computers, creativity and learning

Blogging again

I'm blogging for Communications of the ACM again after a break of four years! I got bored writing business cases and REF self assessments. Here is my first post about what children want to know about computers.

In memory of my PhD supervisor, Jon Oberlander

This week Jon Oberlander died. Jon was professor at University of Edinburgh School of Informatics.  He was my PhD supervisor between 1998 and 2001, and recently our paths had met once more on the City Deal project on data driven innovation. 

I find it hard to believe that Jon is gone, because he was one of the most vividly alive people I ever met. He had liquid silver intelligence and extraordinary energy. I have had the good fortune to meet a lot of highly intelligent people over the years (a perk of being an academic) but he was exceptional.  I remember him at my viva, nodding vigorously, encouragingly, almost bursting with the effort of remaining silent while there was an interesting discussion to be had. He said a couple of times after I graduated that he didn't supervise my PhD, so much as witness it. I took this as a Jon way of saying that I was quite an independent student. But now I wish I had told him how glad I am to have had him as a supervisor and what it means to me.

One of my other colleagues was joking yesterday about how universities are getting a lot of bad press in the UK at the moment - "everyone hates universities", he said. But I don't. I feel very lucky to work at a university - at Edinburgh in particular - and that is because Jon taught me by example to love the best of academia. He loved ideas. They would come tumbling out of him, playfully, seemingly effortlessly. He would listen intently, pounce on new ideas and generously share them with colleagues. He connected people. He revelled in knowledge. I get to do all of these things in my job every day. All I need to do is remember once more why I work as an academic, and avoid being swept away by the flotsam and jetsam that goes along with it. This lifelong deep appreciation of creating and sharing ideas is the most wonderful gift and legacy from my PhD supervisor. Thank you, Jon.

Back again

Well that was a shockingly long time since the last post. One thing and another have conspired to keep me from blogging without me really noticing I had stopped until I got a message yesterday from one of my former students asking after me because my blog was quiet. 

Since I last posted in April, I have moved from a computer science department to a School of Education to become a professor of Digital Learning. You might think that as I professor I would have all the time in the world to blog, but not so. In fact my days are taken up with eating scones and playing tiddly winks. It is a culture shock in many ways. I have moved back to a giant and rich university, I work in the centre of town again and my colleagues are no longer eccentric computer scientists. My new colleagues do things like telling seminar speakers how much they enjoyed the talk instead of savaging them with obnoxious questions. Admittedly they then may impenetrable remarks about Foucalt, but I can overlook that. They tend to be respectful of one another and constructive during meetings as well, which is refreshing. My favourite two new words are "criticality" and "under-theorised". Not sure what they mean exactly, or what "sustainability" means with respect to education but I am sure I will find out one day.

What are professors meant to do all day? As far as I can see it is a bit like being a PhD student except the pay is better and you know how to do research already. I suspect it would be quite easy to get bogged down in doing Big Important Things but I am trying to avoid that because it would be a shame to waste the opportunity to immerse oneself in research. Here are some things I am working on:

• Co-editing a book on modern statistical methods for HCI with Maurits Kaptein (due in Sept this year). This is great - somehow we managed to convince a lot of very clever people to write chapters about how to escape from the curse of null hypothesis significance testing. It's got running examples with R code and everything. For those of  you who followed my increasingly irritated tweets last year about our article on poor stats methods in HCI getting rejected from 3 HCI journals in a row, this is what we did next. We got a book contract with Springer and a host of respectable statisticians on our side and by golly we will take the HCI world by storm with our nerdiness.  We'll fight 'em, one underpowered study at a time.
• Learning about realist evaluation and logic modelling from the wonderful Ruth Jepson and using these methods to make sense of the randomised controlled trial we ran on our exergame last year. I'll post more on  realist evaluation shortly, but it in a nutshell it takes all the complicated real world messy bits you meet during socially useful HCI studies and gives them a big hug instead of ignoring them.
• Working with Quintin Cutts, Kate Farrell , Andrew Manches and others to map a progression of how computational thinking skills develop from early years up.
• Still developing and evaluating technology for children with BrainQuest (an exergame to enhance executive function and Critter Jam which is an exergame which does not make you any smarter but does make you tired)

And lots and lots of other things besides which I might write about one day. 

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When boys get the toys

[cross posted from http://www.theguardian.com/higher-education-network/blog/2013/dec/18/research-council-sandpits-funding-decisions]

There aren't a lot of women professors around, particularly in science and engineering. Figures from the Higher Education Statistic Agency (HESA) indicate that only one in five professors are women, even though women make up half of the rest of the academic workforce. There are many reasons for this, but here's a contributing factor which deeply irritates me: research council sandpits.

These are five-day intensive residential workshops at which research consortia are formed and large sums of research funding are allocated. They are fairly brutal events by reputation – disturbingly the phrase "tribal behaviour" crops up in one description of how the sandpit model was developed.

Imagine a literal sandpit of bespectacled professors hitting each other with plastic spades and chanting "But I want funding!" as they kick sand into each other's faces. I imagine this scene because I've never actually been to one. Why? Because I don't have the luxury of spending five nights in an expensive hotel indulging in tax payer-funded intellectual play.

I spend my time at home, building real sand castles with a lovable yet demanding three-year-old. Other academics will be helping their children with homework, doing the laundry, cooking the dinner, attempting to find their elderly mother's heart pills, visiting their grandfather in his care home or quite possibly doing all of these activities at once.

There are many people who balance caring responsibilities with working. Currently, one in eight adults care for adults with ill health or disability and 58% of these carers are female. In the UK, 48% of women with one child under six-years-old work part time (in comparison to 5% of men).

Attracting research funding is a key activity for those who wish to advance their careers, and the last thing women academics need is another barrier to promotion (or indeed male academics with caring roles, who are also affected by this issue). It is deeply puzzling to me that Research Councils UK funders, who claim not to discriminate among applicants for research funding , persist in this model of allocating funds.

In my field, the Engineering and Physical Sciences Research Council (EPSRC) states that "sandpits inadvertently can suffer from a low female participation", as if this was not a direct consequence of the way the event is organised. The Economic and Social Research Council (ESRC) at least "appreciate that some people will have caring roles that make it difficult to commit to the residential nature of the sandpit". Having acknowledged this problem, it goes on to propose the non-solution of asking your employer to fund childcare costs, or discussing flexible arrangements around hotel accommodation.

Maybe I am suffering from a lack of imagination, but I can't see how this is meant to work in practice. How are we to reconcile part-time flexible working routines with a working week away from home? Are toddlers meant to be locked in the hotel room by themselves while academics brainstorm about transformative research? Do elderly relatives get a bucket and spade and join the sandpit? Who is going to pick up our children from school when we are 400 miles away for five days straight?

A long suffering partner with a flexible employer is presumably part of the funders' rather hazy picture of family life for academics. I am lucky to have such a partner; others may not. In any case, a caring role goes beyond meeting the financial costs of childcare or the logistics or arranging meals for a disabled parent. It is about being present when people need you most: to provide comfort, help and love.

In the past financial year, EPSRC alone spent £218,000 on sandpit running costs, and allocated £19.4m on research to be funded from sandpits. This is 2.5% of EPSRC's budget commitment for the year for research, as revealed by a freedom of information request in November 2013. This is a low proportion of its budget, but a large amount of money in real terms. What's more, the success rate for getting funding is presumably considerably higher for sandpit attendees than responsive mode applicants because there is a smaller pool of people competing for a pot of money.

The most frustrating aspect of the sandpit model is the lack of compelling evidence that it results in better funding decisions, more innovative ideas or higher quality research. Rather than providing such data, EPSRC's explanation of why they use sandpits includes such soundbites: "The IDEAS Factory Sandpit mechanism is unique and has already shown a universally positive impact for those attending."

The impact on those unable to attend is not mentioned. The lack of inclusivity seems unnecessary. What's wrong with writing proposals and having them evaluated on scientific merit? Is the extra Lord of the Flies-like intensity in sandpits really advancing scientific knowledge?

EPSRC is very proud of its model: "The IDEAS Factory Sandpit has emerged as a shining EPSRC innovation invention, copied far and wide across continents, funding agencies and multinational corporations," writes organisational psychologist Bharat Maldé on the council's website.

But what of all those carers across continents who have found it more difficult to succeed at work because of this fad – and the British taxpayers who funded it? At some point, funders must realise it's time to grow up and climb out of the sandpit.

Be a giver not a taker

[I published this on the thesis whisperer blog a few weeks ago but I think I forgot to publish it here].

How much do you help people as part of your day to day job? If you’re an academic, do you try to hoarde every precious minute for your research, or do you shower your time upon students like confetti?

Or, like me, are you conflicted about it?

Adam Grant’s book Give and Take considers the question of how much time employees spent helping others, making the case that highly successful people are often what he terms “givers”.

A giver is someone who gives freely to others – of advice, help, contacts, time – without any expectation of return. A taker is someone who tries to get as much from other people as possible without paying back, whereas a matcher aims to trade evenly.  If you want to find out what you are, try the assessment here.

I was a giver. Most of the time. But not during marking season.

According to Grant, takers can crash spectacularly when their colleagues realise their selfish attitude and start to resent them. Perhaps, contrary to expectation, though, some givers can be very successful even though they spend a lot of time helping others.

Grant would say that if you interpet your job as a zero sum game, then you expect to lose out if you help others. But if you have a generosity approach, then you believe that everyone benefits if everyone does more favours to others. The favours don’t need to be reciprocal: if you think about it as a “pay it forward” arrangement, you give freely and perhaps you’ll benefit from the help of a different person in the future as there are more favours being done overall.

The question is how can givers avoid being trampled on like savannah grass under elephant’s feet? How can an academic maintan her internationally leading research profile and still find time to help the first year undergraduate with his essay?

In the last year I have spent a lot of time trying to improve the relationship between staff and students in my department. A lot of what I have done is nudge my research active colleagues very slightly to spend more time on teaching even if it means a little less on research. This translates pretty much towards more of a focus on giving. Without teaching, most UK universities would go under. Students pay our salaries. But we’re promoted according to our research record, which on the face of it doesn’t encourage us to spend more time giving/teaching.

It’s easy to see why teaching is giving – the sharing of knowledge and experience, dispensing of advice and tissues, writing of recommendation letters. It’s harder to see research as giving unless you do medical research or something else useful. My field is computer science which makes it harder to portray our research as a selfless dedication to humankind. We’re mostly in pursuit of the glory of high h-indices and large grants. (An honourable exception is my student Andy Macvean who tries to make fat kids thin with iPhones. And in my own defense, I have spent a lot of time helping the little children with computers).

Part of the problem is time pressure, of course. Academics are incurably busy. If you use a productivity system like Getting Things Done, you’ll notice that it doesn’t advise you to set up a folder for “Helping folk” and consider who to help as a next action. (but you could, actually).

Grant advocates the five minute favour rule which in essence means that if you have an opportunity to help someone and it only takes five minutes, go ahead and do it. For academics this could make a huge difference to a student’s learning or well being. What can you do in five-ish minutes?

• Advise a student on what course to take.
• Direct a depressed student to the counselling service.
• Write a brief recommendation letter.
• Give feedback on an essay draft. (Think you can’t do that in 5 minutes? You can if you ask the person to tell you the MOST important aspect they want feedback on).

Another tip is to bundle all your favours into a block and do them as a batch because apparently it’s more satisying that way. Presumably less disruptive to your research too.

Giving refers to helping colleagues as well as students of course. I heard recently about an early career research who was advised not to spend time helping develop the career of her PhD students on the grounds that in four years time they would be competing with her for grant funding. I’m glad to say that she thought this was nonsense. Like me, she considered that in helping a student become employable she was making a future for herself filled with trusted and loyal colleagues.

Mentoring is another powerful way to help colleagues. I’m sorry to say that I attended an ACM Women’s Breakfast a month ago where a female speaker recommended only asking powerful male colleagues to be your mentor on the grounds that women won’t help other women. I think this is complete bollocks. I have been fortunate to have some very helpful women mentors and I try pretty hard to help other women.

If you’re worried about people taking advantage of your good nature (like by dumping their teaching responsiblities on you while they swan off to a high powered conference) you could adopt the generous tit for tat strategy. Your default behaviour is to help people without help of reward. If you notice a taker who is treating you badly, you then start to trade favours evenly with them as a matcher would, with a little leeway for forgiveness.

So go on, give giving a try today! Everyone wins.

On the pleasures of teaching computer science students

[cross posted from my CACM blog]

Yesterday was the most important day of my work calendar. We awarded degrees to 50 computer science students, thus fulfilling one of our main purposes as academics. I had the pleasure of telling some of the top students their marks in person. I’ve been doing this job for a good few years now, but I still can’t quite get used to the buzz I get when students hear that they have succeeded. Their faces are pictures of incredulity, joy, but mostly relief that they made it. I am proud to have played a small part in their learning journeys.

We often interview students as part of our selection process into the first year, at the start of their journey. That can be extremely revealing. It’s quite a daunting situation for some teenagers to find themselves in a room with an unknown adult and try to talk their way into a university course. From time to time, though, the young person’s sheer passion for computer science shines out through the shyness.  One chap this year was carefully cultivating an air of teenage boredom until we stared talking about computer games development, when he revealed his awe and reverence of his game development heroes (who no doubt were bored teenagers themselves once).  Another candidate, the first member of his family to apply to university, spoke fondly of how he put his first computer together with his granddad when he was eight years old. School students at our Turing birthday party last year were delighted to talk to our students about their programming projects, as they said their teachers didn’t understand what they were working on. I strongly remember one of our current PhD students almost dancing with excitement when he got to talk with one of the professors about Open GL. He had been teaching himself for years but now he had someone else to talk to about his favourite topic. He had come home. 

As academics, our role is to teach the foundations of computer science while fuelling - rather than dampening - this passionate geekery. We try to fan the flames of geekery in those who have never had the good fortune to experience it before. It’s hard for us to do this, and even harder for the students to keep motivated throughout the long journey to graduation. To get a CS degree at my university, you need to pass 32 different courses, picking up 480 credits on the way. On each of these 32 courses, there are possible ways to slip up: course work whose spec you cannot fathom, compilers which hate you, unit tests which spontaneously fail just before the deadline, exams in which your mind goes inexplicably blank. Many students also have the hurdles of young adulthood to deal with too – a potential mixture of financial hardship, leaving home, relationship break ups, bereavement, or mental health difficulties.

In spite of all this, the students get through it. They learn where to put their semicolons. They grasp how Quick Sort works.  They sort out their matrices and master the halting problem. They fall in love with APIs and engrave comms protocols on their hearts. They learn how to write, how to present their ideas, how to think. This is a privilege to witness. Academics really do have the best job.

Nerdy strutting: how to put women off the tech industry

[cross posted from CACM blog]

As the twittersphere erupted over Donglegate last  week, I was attending a workshop on career development for women in IT. There is a striking contrast between the collegiate, supportive environment of the workshop and the howling hounds of fury which were unleashed by the crazily escalating interactions between participants at a developer conference.  In short (because I don’t want to get lynched online myself), a female conference attendee tweeted photographs of male audience members who she said were telling off colour jokes. A storm of vicious discussion blew up online, and two of those involved lost their jobs. I bring up this news story because one of the main barriers to women in IT which workshop attendees identified was the aggressive  behaviour of male colleagues either in person or online. Behaviour doesn’t have to be explicitly offensive to make colleagues feel uncomfortable; there are many ways to exclude people in a workplace.  Further, although this was a gathering of women, the sort of behaviours were discussed were likely to make lots of people miserable, regardless of their gender. We decided to nickname some of the behaviour which makes us feel uncomfortable as "nerdy strutting", and our ensuing laughter at the phrase helped us to feel better about it.

What is nerdy strutting? Garvin-Doxas and Barker (2004) refer to "strutting" as a style of interaction where  people show off their knowledge by asking questions carefully designed to demonstrate that they know a lot about the topic, and quite possibly that they know more than everyone else around them. The problem with this in a learning situation is that students who lack confidence assume that they are the only person who doesn’t understand, and quickly feel even more demoralised.  An example might be of a student interrupting the lecturer with a fake question of the sort "But wouldn't it be better to use a function to do X?" I say fake question, because the strutter knows the answer already but is merely trying to show that they know this advanced concept which has not yet been covered. Or if another student gives an answer, a strutter might say "But wouldn't it be more elegant to do X?" Garvin-Doxas and Barker studied computer science classrooms, and found that often female students were put off by male strutters.  A related off putting behaviour, identified by a workshop participant, was the sort of answer you see on discussion forums where an answer tears apart  the question, castigating the foolishness of a naive solution attempt.

I have noticed some fascinating behaviour among ultra nerdy students at seminars where they are so anxious to illustrate their technical worth to the speaker that they emit giggles, snorts and chortles of derision at the mention of seemingly arbitrary technologies. It is a  weird phenomenon.  Somebody outside the charmed circle might be baffled as to why the very  words "Prolog" or "Visual Basic" or even "Internet Explorer" evoke such mirth.  "It was awful", says the speaker, "he was trying to deploy his Rails app with Apache httpd running Ruby using Fast CGI".  If you don’t happen to know what Fast CGI is, you’re going to wonder why people around you are creasing up. You'll feel excluded.  (I don’t know, by the way, and I don’t care.  I asked a genuine geek  to provide me with an example to use for this article.)

You might be wondering why it’s a problem if people feel excluded by nerdy strutting. If so, the Computer Weekly’s Women in Technology report, may change your mind. It reports that only 1 in 7 people in the tech industry (in the UK) are women, and that a masculine culture is identified as problematic by both male and female participants. Fixing strutting, therefore, may be part of the solution to a male dominated industry. Further, it might also make work places more pleasant and productive for all employees.  So what can we do to address it?

1. Are you a nerdy strutter either by accident or by design? Think: do you really need to show off? If the need overwhelms you, can you thinkof a way to demonstrate your knowledge which doesn't belittle orbefuddle others? If you're trying to help is your advice going to makes the recipient feel better or worse?

2.  If you get strutted at... draw attention to discourtesies. Try
commenting "Thanks for your input, but I don't feel that your
criticism of my approach was very helpful there". Or calmly ask "why's
that funny?" My intuition is that it is easier to combat this kind of
behaviour face to face than online because it's harder to look someone
in the eye and keep being an asshole (in the sense used by Robert Sutton).
3. If you witness strutting (particularly for CS instructors but also for team leaders)...don't just let it go.  That is, if you're sure it's strutting rather than a
genuine quest for knowledge. You don't necessarily want to embarrass
the strutter who might have social problems already.  But you do need
to help the majority of the class feel at ease. Put the comment or
question in context. Point out if you expect the class to know the
topic in such depth for assessment. Explain the joke if necessary.
Demystify it. Help everyone to feel like they belong.

 

Garvin-Doxas, K. and Barker, L. J. 2004. Communication in computer science classrooms: understanding defensive climates as a means of creating supportive behaviors. J. Educ. Resour. Comput. 4, 1 (Mar. 2004), 2. DOI= http://doi.acm.org/10.1145/1060071.1060073

How to get a paper accepted for Interaction Design and Children

[edited after doing another review!]

You may have read my last post and concluded that a) I am on some kind of crazy power trip b) I have just served on a Programme Committee as an associate chair or c) that it is Friday afternoon. All three are true, and as I have been doing nothing but reviewing and marking all week, I feel like writing instead of reading. Here are my thoughts on how to get a paper accepted in IDC which I hope might be useful to authors for future year. [IDC notifications and reviews will be out on Monday and this post does not contain spoilers!]

Interaction Design and Children is a conference series entering its second decade, a fact which makes me feel old as I attended the first one as a post doc. As the years have gone by, the conference has become increasingly popular and standards have improved. This year we moved to a system where Associate Chairs are responsible for checking review quality and writing meta reviews. This is another step towards being all grown up and scientifically mature.  This year 28 papers were accepted (some with shepherding), which is about 30% acceptance rate. (For comparison, CHI 2012 had an acceptance rate of 22% in 2012, but started out 20 years ago with 45%.) Having reviewed papers almost every year for IDC, papers co-chaired in 2007 and acted as AC this year for 10 papers I feel like I have a handle on what is expected. Here are some thoughts to help new authors planning a submission in the future.

1. More than cute systems.  The days when you could get published at IDC for developing a cute system for cute children are hopefully gone. You'll need some kind of evaluation with kids, and more than just testing it on your neighbours' children and reporting that they thought it was "awesome".  If you just have a cute system, a demo might be more appropriate.
2. More than involving kids with the design. In my view, we should also be past the stage where a paper gets accepted simply because the paper used kids as design partners. There is certainly a place for critically evaluating design methodologies or introducing new methods for working with challenging user groups. But the paper needs more of a contribution than finding that the kids provided useful suggestions for the design.
3. Describe the design of the software/technology. I want a screenshot!It ddn't occur to me to include this one the first time, because it seems obvious to me as a computer scientist. But I have now reviewed several papers, possibly written by psychologists, which report results extensively but not the technology which was used. For the results to be interpretable we need to know about the design features of the software which was used in the study.
4. Methodology is important. Choose your methodology carefully, and execute it well. In my experience, IDC doesn't particularly value quantitative over qualitative methodologies. I don't think reviewers really have physics envy and want to see lots of numbers. So you don't need to put stats in just because you think they are expected. What matters is whether the method matches the research questions,and whether the conclusions can be supported by the evidence the methods produced. Pick a well estblished and documented methodology and a set of of commonly used measures. If you are going to include stats then please make sure you get them right! You can see my previous rants about this here and here.  In short: don't bother with stats on small sample sizes, don't use t-tests or ANOVAs on likert data, report effect sizes, be careful about drawing conclusions when you have low power. Don't do multiple comparisons without applying post-hoc corrections, and don't throw in co-variates without good reason. (See also Simmons, J. P., Nelson, L. D., & Simonsohn, U. (2011). False-positive psychology: undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychological science, 22(11), 1359–66. doi:10.1177/0956797611417632)
5. Rich description is more convincing than weak stats. As a more specific version of the above point, if you have access to only a small number of participants, but feel there are still valuable points to be drawn from your study, consider a rigorous qualitative methodology instead of statistics. In some sub fields, it is difficult to find large numbers of participants (such as when working with children with autism or those with particular medical conditions). Rigor is the point here: don't just informally describe what the participants did, but use a well known approach such as case study analysis or grounded theory to systematically draw a picture of the participants' experiences in some depth.
6. Try to use well known measures such as questionnaires rather than making up your own questions or tests.
7. Let the kids speak for themselves. It's generally frowned on to have teachers or parents' views to be used a proxy for kids. Gather data directly from the kids unless there is very good reason not to.
8. If using quantitiative methods, state your hypotheses clearly and base them in the literature. I'm looking for a match between the findings of previous studies reported in the literature, and clearly stated directional hypotheses (ideally with effect size predictions). Instead of "There will be a difference in children's attitudes to geography after playing with the Amazing Jupiter Robot", go for "The geography scores of children who played with the Amazing Jupiter Robot will be 10% higher than the control group". Where did you get that prediction of 10%? You got it from Robertson (2012)'s work on the Amazing Mars Robot which reported similar effect sizes.You didn't pluck it out of the air. For a set of prompts for critically evaluating your article, see p79 of Dienes, Z. (2008). Understanding Psychology as a Science: An Introduction to Scientific and Statistical Inference (1st ed., p. 150). Palgrave Macmillan. To be completely honest, I have never reviewed or read a paper in CHI or IDC which does give effect size predictions. I would like to, though. Please make my day! If you can't do that, at least specify the direction of the hypothesis: "Users who play with the Amazing Jupiter Robot will perform better on standardized geography scores than control users". Don't sit on the fence. The more specific the hypothesis, the more informative it is to have to supported (or disconfirmed). Also, don't introduce new variables into the experimental design without having a good reason from the literature. Gender or social class might be easy to get data on but please have a good theoretical reason for believing there are likely to be differences according to such groupings.

I'm sure there are many more tips which other IDC bods could suggest, but that seems enough to be going on with for now.

I am the meta reviewer. I see into your soul

Authors: I am the meta reviewer. I see into your soul. I scrutinise your literature review.  I inspect your evidence. I evaluate your claims. I consider your conclusions.

Reviewers: I am the meta reviewer: I see into your soul. I judge your accuracy.  I evaluate your expertise. I doubt your motives. I witness your inexperience.

Programme Commitee: We are the meta reviewers. We save souls. We guard standards. We argue, defend and justify. We shepherd papers for the good of the community. We are time starved, weary eyed but truimphant. Science has been served once again.

Motherhood and HCI - call for papers

I am excited because we got a workshop proposal accepted for CHI 2013 on Motherhood and HCI.Write a position paper! Come along! It'll be fun!

Here's a previous post of mine about interface design issues for breastfeeding mothers, written, as I recall, while feeding a sleeping and very heavy baby.

 Call for Participation: CHI 2013 Workshop on Motherhood and HCI Important Dates 11 January 2013: Workshop Submission Deadline 8 February 2013: Notification of Acceptance 27/ 28 April 2013: Workshop held in Paris, France Website: http://motherhoodandhci.wordpress.com/ *********************************** Becoming a mother and the experience of being a mother are increasingly influenced, mediated and invaded by technology and digital interactions. We invite the CHI community to grow and nurture the emerging topic of motherhood and HCI and explore how the lens of “motherhood” changes implications for design, development, and notions of care through participation in the CHI 2013 workshop “Motherhood and HCI” (http://motherhoodandhci.wordpress.com/). This one-day workshop will address research and design issues relating to technology use associated with the processes and experiences of conception, pregnancy and infertility, labour, childcare and the mother’s work in the family and home. Topics include (but are not limited to) the experience of motherhood, technologies for supporting mothers, and perspectives on the role of the mother, as well as everyday practices relating to technology and motherhood. We invite non-mothers,mothers and mothers-to-be to participate in our workshop through the submission of a 2-page position paper in CHI Extended Abstracts format that describes the authors experience engaging with a specific theme, or challenge involved with designing, using, or evaluating technologies that relate to the concept or experience of “motherhood”. We positively encourage submissions from a diverse range of participants, perspectives and disciplines. We also encourage active participation from industries already engaged in the design and development of technologies for motherhood. Submissions will be selected based on their originality, quality and ability to promote discussion amongst the community. Submissions and questions should be directed to [email protected]. More details can be found at: http://motherhoodandhci.wordpress.com/. At least one author of each accepted paper must attend the workshop. Please submit your position paper by Friday 11th January 2013. *********************************** Workshop Organisers Madeline Balaam, Newcastle University Judy Robertson, Heriot-Watt University Rebecca Say, Newcastle University Geraldine Fitzpatrick, Vienna University of Technology Gillian Hayes, UC Irvine Melissa Mazmanian, UC Irvine Belinda Parmar, ladygeek.com