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Explaining myself to technology product groups

I have a meeting tomorrow with a leader of a product group at a Silicon Valley-based household name. On the itinerary, I’m described as “a PhD student who has worked on use of social media and etc. by science and engineering research groups”. I’ve been asked to come up with a 3-5 minute introduction for myself. Here’s my rough draft:

Your itinerary shows that I’ve worked on social media use by science and engineering communities. Another way to think about what I do is to call it social computing for existing (or emerging) social systems. My work is with distributed teams, and it’s different from much of the existing ecommunity work because the teams I study know each other. They may not be close socially or geographically, but they are familiar with each other and have almost always met face-to-face. They’re working together toward some goal that requires them to collaborate (e.g. getting a new building technology to market) or benefits greatly from collaboration (e.g. getting through grad school). They span a variety of distributions — whether their offices are states or continents apart, whether their disciplines seem distant, and how they span the spectrum from novice to expert.

Two of the projects I work with now that explore the use of social computing by existing communities are the CI TEAM grant and KNOW SI. In the CI TEAM grant we explore how engineers developing and testing a new building material work together across institutional and national boundaries to establish standards for testing the material and for training new users of the material. The CI TEAM group uses a content management system with features somewhat like Yahoo! Groups to share their data and discuss it. CI TEAM builds on earlier large-scale scientific collaborations that used the same tools but had very different motivations and goals for collaboration. What I’ve found most interesting in these scientific research collaboration projects is how unlikely users are to adopt a technology specifically for their projects. Users love email and Excel but ignore wikis, archived email lists, and file repositories.

KNOW SI is a PhD student-led project with many goals. Mine is to use KNOW SI as a way to understand how people in organizations, such as schools, use available technologies to share information with one another. In KNOW SI, I helped set up an iterative series of wikis for use by the community, and we’re analyzing that use and preparing the next generation wiki. What’s surprised me here is how willing various groups are to use the same underlying technology. For example, doctoral students are all over the wiki. We’re our own audience though. The Research and Career Services offices have different audiences — master’s students and the public for two — but are exploring the same technology.

Together these projects provide a variety of settings for me to explore information and technology use in different kinds of collaborations.


So what did we say? Our talk notes from GROUP 2007

Ask and you shall receive. Here is the text from which Jude and I spoke during our talk at GROUP this year. We said more than is here, but you get the gist. Thanks to everyone who stayed off the beach long enough to see our presentation!

Slide 1: Title
Welcome to Twiki and WetPaint: 2 wikis in academic environments. If you’ve read the paper, you’ll know some of what we’ll talk about today, but most of our discussion will center around analysis we’ve done since the Note deadline. We’ll describe the process through which Twiki became KNOW SI and then tell you a bit about what happens (or happened) on each wiki, and we’ll end with a group of questions we’re planning to explore. What we’re presenting today is some history about those two wikis and some information about our theoretical work.

Slide 2: diagram of projects
TWiki and KNOW SI are part of a larger research project on organizational knowledge and the use of wikis. We’re not building just theory or just building wikis.

Slide 3: screenshots of lots of wikis
We chose to study these wikis because they’re likely places for users to find and share information about and relevant to their communities.

Slide 4: Meet the Twiki
Started in June of 2005 and first used by a single research group and a few master’s level classes, meet the Twiki. Twiki is still operational, but it’s only remaining active users are the research group that who adopted it. Not surprisingly, the sysadmin is in that research group. Libby got to know Twiki as a GSI (Michigan’s fancy term for TAs) for a course that used the Twiki.

Slide 5: 504 Twiki
That class kept discussion section notes and shared links and extra information on the Twiki. The most common complaint about the class as a whole was that the Twiki was “impossible to use” and “too confusing to be helpful.” That so many students felt strongly about something peripheral to their class clued us in more acutely to the twiki’s usability issues.

Slide 6: Special markup
required by the Twiki was at worst an insurmountable barrier and at best a mild nuisance for users. That class was during fall semester 2005.

Slide 7: Foosball (sept 2005)
Doctoral students, in general, were the most frequent editors of both wikis, and their wiki use started with the Twiki in September 2005 with the all-important Foosball Ladder information. We have a foosball table in our building, and we started tracking foosball competitions the same summer the Twiki was born. Other pages on the Twiki that started early include

Slide 8: Doctoral Resources (sept 2005)
Doctoral resources; a long page of resources for writing, getting funding, analyzing data, other stuff important to doctoral students’ work.

Slide 9: Conferences (nov 2005)
Another long page, this one about conferences that people from SI have attended. Each paragraph contains information about the conference including when it was last held, who’s gone, and what it’s about.

Slide 10: Field prelims (summer 2006)
A small group of students working on their prelims used the Twiki to keep each other up to date on progress, to share time lines.

Slide 11: Fishing for info
Doctoral students were frequent Twiki editors; most Master’s students disappeared after their classes ended. PhD students used the Twiki to tell each other about their work, to share info about conferences, and to archive community information like foosball prowess. A little over a year later, some students

Slide 12: Eating food
were eating food and talking about wikis. Discussions for a new, more usable, easier to find wiki began. Isn’t that the way many interesting projects start? Anyway, it was time for a new wiki platform.

Slide 13: WetPaint
we chose WetPaint as the 2.0 platform because it promised to be ridiculously easy to use and sported a WYSIWYG editor reminiscent of our favorite (or not so favorite) word processor. The WetPaint wiki also got a new nick name – KNOW SI – Knowledge Networked on a Wiki for SI.

Slide 14: KNOW SI
KNOW SI started with seeds – content grabbed from the TWiki’s active, public, whole community pages such as

Slide 15: Conferences (KNOW SI)
Conferences, and

Slide 16: Doctoral Resources (KNOW SI)
Doctoral resources. This page has grown

Slide 17: Doctoral resources navigation
into a large section that now has 14 pages including

Slide 18: What I Learned
What I learned – a page started by a doctoral student who had defended and accepted a tenure-track job. He enlisted other recent grads to make an interesting page of advice.

Slide 19: Papers by SI Students
Papers by SI Doctoral Students – a one-stop shop for finding papers we’ve written; skimming it gives you a sense of the breadth of work we do at SI. The papers page is an example of a kind of behavior that’s been used a few times to generate wiki content – a student sent out

Slide 20: Emilee’s email
an email letting people know the page existed and offered to post others’ papers.

Slide 21: Papers original version
That email generated this first version – 1486 words.

Slide 22: papers history
Then, the page grew as more students added their own papers. Other KNOW SI pages such as a blog list and auto mechanic recommendations started similarly; one person got a bunch of information from many people, created a page, and then let it lose for the community to update. We’d seen the same thing with the original doctoral resources page on the Twiki; this one just gets a lot more action.

Slide 23: question marks
So that whirlwind tour shows you some of what we see on both wikis. What does any of this tell us? People are using the wiki, or at least trying, to do a number of things including

Slide 24: What I learned; Conferences for SI Types
Give advice

Slide 25: Foosball, basketball, grilling
Store, or point to, information about activities in the community

Slide 26: Good Mechanics
Aggregate and store information

Slide 27: making sense of wiki use
A couple theories help us analyze those behaviors – one of them is transactive memory.

Slide 28: Transactive memory
In this project we look at transactive memory as part of organizational knowledge

transactive memory – a theory of organizational memory, by Wegner (1986) that suggests knowledge within an organization/group is distributed among the group and that individual members can serve as memory aids to each other. One key to transactive memory is being able to build a shared understanding of “who knows what”. For instance, if I wanted to get baseball tickets in Michigan, chances are likely that I will turn to Libby for help because I know that she is a major baseball fan.

Slide 29: Newcomers and knowledge sharing
Such anecdotes and informal knowledge sharing are essential for newcomers to academic communities. Academic communities are highly dynamic environments with a high turnover of members every year or even semester. By knowing “who knows what”, newcomers know who to approach for particular pieces of needed information.

Slide 30: Who knows what
One example of how the wiki supports this kind of “who knows what” investigation is that it keeps track of the authors of its content. For newcomers looking to learn about student organizations, the history of that particular page can tell them something about who might know about a particular organization.

Slide 31: Takeaways
We have two important findings from this first part of our study – people will use a wiki to share information relevant to transactive memory; they’re more likely to use it if it’s easy to use and you give them time.

Slide 31: What’s next?
We’ve been careful to this point not to generalize from the use within SI, a bounded academic environment, to organizations in general or public wikis broadly. At this point, we’re not prepared to make broad claims about wiki use in organizations. Rather, we’re using the data we and theory we’ve generated and used thus far to move us along to another iteration and more chances to study organizations.

Slide 32: Questions?


ECC Trivia: slump test

I spent about 3 hours with the students in the ACE-MRL lab this morning while they mixed and poured some engineered cementitious composite. I learned lots of things, but right now, I’m offering you this linguistic tidbit: slump.

In this case, slump refers not to the Hawkeye football season or some other sudden, severe decline in value but to a kind of test performed on concrete. In the slump test, fresh concrete is poured into an almost-cone, someone pulls the cone up, and then someone measures how far from the center of the cone the concrete ends up. Basically, you make a pancake of concrete and measure its radius. The results of a slump test tell you something about how “workable” the concrete is – how easily you can “place” it in a structure or form of some kind. It also tells you how cohesive that mix is.

So there you go. Today’s bit of flexible concrete trivia is “slump.” Pictures to come!


Paranoia and the public blog

The Chronicle forums have a somewhat popular thread in the job hunt category in which someone asked whether search committee members read candidate’s blogs or check their records on RateMyProfessor. I’m not generally paranoid about my online persona – as evidenced by the “me on x” links in the navigation – but I sense a higher level of paranoia among academic job seekers.

When I think about what about my blog sends the wrong or an undesirable message, I tend to focus on how the Kiwi WordPress theme I use doesn’t actually work. I’ve made some adjustments to the theme, but I haven’t spent hours making sure the “Recent posts” section on a blog entry page is providing some useful set of links. Yes, I have the technical skills to fix that. No, I don’t think doing so is worth my time. A mistaken calculation? Time will tell. Maybe when I’m more explicitly on the job market making my blog work perfectly will be a higher priority for me. I hope that the rest of my blog demonstrates that I care about things such as civil rights, gadgets, collaboration, sustainability, and travel (not necessarily in that order). I do care about those things, and I write about them occasionally.

I expect to see an increase in the pace at which I blog, and I wouldn’t be surprised if I start to blog more about my dissertation than I have to this point. It’s tough to decide how much of the proverbial sausage-making to describe here. I don’t want my blog to dangerously oversimplify the process of dissertation topic-selecting and eventual research, but I’m also pretty sure search committees don’t need to know every time I doubt myself or my research. I’m human, and that much is clear from my work – whether on my blog, in the classroom, or in peer-reviewed publications and conferences.

Happy Halloween!

Update: I removed the “Other Recent Posts” part from the single post view. Apparently blogging about my irritations with the Kiwi theme gets me to edit it.


Learning Sciences should be about more than learning science!

My research group (Stephanie Teasley, Eric Cook, and Jude Yew) and I are proposing a workshop for the International Conference for the Learning Sciences (ICLS 2008). We’re hoping to get a group of people together to discuss learning as it occurs outside classrooms and other formal and semi-formal instruction environments. I’ve been frustrated with learning sciences events and publications in the past because they seem to focus too narrowly on classroom learning – especially middle school science and math classrooms. Thinking of learning, rather than instruction, seems an important distinction, and the learning sciences community ought to stake a broader claim. Not only are we studying learning outside the laboratory, we’re studying it outside contexts explicitly established for learning.

For example, I consider myself a learning scientist; I elect this moniker because I’m interested in how adults learn in their professional environments.

  • How do civil engineers learn to design with a new building technology?
  • How to doctoral students learn the lay of the land in their new schools?
  • How do communities capture and represent the knowledge that resides in them?
  • What does the way organizations use wikis tell us about what knowledge they value?

These questions and more ought to be part of the Learning Sciences even though I didn’t mention minors, teachers, curriculum, or standards once. Hopefully our workshop will get accepted, and it will become a welcome respite and energized conversation for others frustrated by the science classroom focus of today’s learning sciences.


Transformation of practices

Here’s some text from a recent proposal draft (I’ll add citations later). I’m still editing the document from which these are excerpts, but the people have spoken, and they asked for drafts. So here you go. This is what I’m working on now.

Much of the research on practice focuses on how it may be transfered from one firm to another, from one
person to another, or from one group within an organization to another part of the same organization.
This study builds on those literatures, but asks a different question – how do networked practices change when
one or more parts of the network change? Instead of exploring a sender-receiver model of transfer of practice,
this study explores scenarios in which the source and target of a new practice are the same. Instead of focusing
on practice within a single community of practice (CoP), this study explores how multiple, interacting CoPs
influence one another. To refer to the set of changes that occur in the network, I use the term transformation
of practices. The following describes relevant terms and literature and proposes a study designed to produce
data necessary to describe the processes involved in transformation of practices. The plural of ”practices” is
necessary here; that I explore the relationships among communities of practice and their impact on one another
sets this study apart. The goals of the study are to describe the network of actors in such a way that enables us to understand the
practices in which those actors engage and how those practices relate.

The transformation of practice seems like a learning and coordination problem. First, someone must develop a
new material or method – broadly a new technology – that is a candidate for adoption by the network. Then, the
technology must be successfully adopted by a number of communities within the network. This sounds much
like Rogers’ diffusion of innovation work, but there still he described the uptake of innovations by people
engaged in the same kind of work. Here, the problem is a little different in that many communities are pursuing
a common goal, a technology with the potential to change how that goal is achieved is introduced, and each
of those already distinct practices must adjust to account for the new technology. This proposal describes a
study that focuses on a case of a transformative technology – engineered cementitious composite (ECC) – and
the resulting transformation of practices within the civil infrastructure building network.

Notes:
I want to be able to talk about something like a network of practice (NoP). Brown and Duguid characterize
NoPs as members sharing a common practice but not needing to coordinate their work. I’d rather think of
an NoP as members needed to coordinate work but whose practices are not the same. The members have a
common goal (e.g. build a bridge) but none of them do the same thing (e.g. design bridge vs. pour concrete).
This kind of activity seems more networked to me than Brown and Duguid’s characterization. However, I don’t
want to use NoP if a big name already did and means something different from what I mean. What else could
I call it? I’m thinking of practice at a higher level of granularity, maybe? Maybe I mean ”system” and not
”network”?


Phenomenologist = me?

I had an interesting meeting with Gina Venolia this morning during which she used the term “phenomenologist.” I haven’t heard that term in a while, but it was a welcome utterance for sure. Gina and I were talking about knowledge – how it is used in teams, how it moves among people, how it gets captured and embellished in boundary objects. I was somewhat surprised to have an 80 minute conversation with a Microsoft Researcher and not have the topic of software developer (as a researcher’s objective, not as an area of study) come up. I have tremendous respect for much of the work in which Microsoft Research people I know engage, but I’ve always read it as having an eye to what Microsoft might develop for sale next. Not in a bad way, just in a way that’s very different from the product agnostic approach of academic research. Gina seemed welcoming of my phenomenologist tendencies (to study phenomenon with an eye to describing them) and unphased by my explanation that I no longer spend much energy thinking about systems I could build. The idea that I wouldn’t have to spend all my energy thinking about how to build a technical system using the knowledge I learned studying a phenomenon makes me more excited about doing just that. Funny how reverse psychology (or something like it) works, eh?

Gina’s work with and about software development teams and their mental models of code and my work with vaccine developers and civil engineers had a number of remarkable similarities. We both had stories to share about the development and use of boundary objects and how they require embellishment by a human in order to be useful. We both focused on the knowledge activities in these domains – those activities where knowledge is used, shared, clarified, developed, transformed.

Those 80 minutes were another welcome occasion for me to talk about my work with someone outside my lab, and that activity always serves to help me refocus and refuel. It’s easy to forget why something is interesting or significant when one is in the thick of it, but such meetings provide opportunities to talk about the forest through the trees. Sigh. Lovely.


From May – a found post (networks, communities, practice)

Here’s a little blog post from a couple months ago that hadn’t made it off my laptop and into the world. I’ve edited it a bit, but most of the text is from May. I was reconsidering the communities of practice literature.

The project I’m currently funded on is ostensibly about facilitating the implementation of civil infrastructure. When I was first presented with the project, the part that seemed most interesting to me was the “transfer of practice” (TOP) problem. The TOP problem goes something like “it’s difficult to move practice from research labs to the real world.” Sure is. I looked forward to working on that problem. As I got into the project more, my focus changed. It seems like now the problem is not so much how do we move a practice from over here in research land to over there in construction but rather, how do the practices of civil infrastructure design and construction change when the materials available change?

Engineered cementitious composites (ECC) have the potential to change the practices of civil infrastructure design and construction. I don’t know enough about that design and construction to yet know what the possibilities are, but I get the sense that they are big and dramatic. Iron and steel certainly made a big difference. Concrete, the rigid kind, is sure important. Imagine what happens when you change the tools again! At least, that’s what I’m imagining. With a little help from my colleagues, I’ll do some more definitive imagining.

So what does any of this have to do with communities of practice (COPs)? The problem of TOP is something like moving a practice from one community to new individuals. Here, I’m describing what happens when new people learn about ECC and start to learn how to work with it. It’s tough to make — the recipe is incredibly precise and the underlying theory is important — and it’s deceptively similar to regular concrete. To solve TOP, you simply send that newly trained person off in to the world, much like a PhD from the lab at Michigan is now off in the world getting his company to use ECC. Obviously I’m oversimplifying here, but you get the idea. By characterizing the problem of developing new infrastructure as a TOP problem, we make the research lab and its practices the goal, and the “real world” and its practices the target. This could even be a transfer practice from one community to another problem.

However, that’s not what I think is going on. Rather, I think the communities of practice involved are a little broader than that TOP conception allows. I don’t think the problem is one of trying to ease the problems with throwing ECC over the wall between lab and field. The really interesting problem, I think, is how does a change in practice within the civil infrastructure design and construction community happen? Much of the existing COP literature is about moving practice from a community to an individual. What about changing a practice within the community? How does that happen?

To start to answer those questions, I’m off to explore a variety of literatures including innovation (generally), innovation (in construction), organizational change, apprenticeship, public policy and infrastructure, and standards development and negotiation. That’s just to get me started. I’m likely to blog about this quite a bit in the near future as I try to figure out what I think is going on, or rather where I think something interesting is going on. In doing so, I hope to avoid the plague of reductionism against which Latour warns. Instead, I’m looking for the details of the network of forces at work in these communities and affecting their practices.


Re: The New College Try

In Monday’s New York Times, Jerome Karabel of UC-Berkeley contributed an interesting Op-Ed piece called “The New College Try.” In it, Karabel rails against the top tier universities in the country (and the systems that support them) for failing to provide access for low income students. As an Alumni Schools Committee co-chair, I spend quite a bit of time thinking about college admissions and even talking with high school seniors during their application process. At the June meeting of ASC chairs, I was disappointed to witness some of the privilege perpetuation that Karabel describes. The University of Chicago provides some advantage for the children of graduates, and probably of big donors, but it is working to provide some admissions (and tuition payment) advantages for lower income applicants as well. I’m anxious to see if those efforts are fruitful. Karabel recommends a lottery system for 5-10% of an entering class where applicants who met some high academic threshold would then be selected at random. Schools could then compare those students’ performance to the other 90-95% to see if their admissions processes were good predictors of academic success. That certainly sounds like an interesting study to me.

While I recognize that there’s a problem of access for low income students to top tier universities, focusing on the problems at that point obscures a greater problem – impoverished academic opportunities throughout their school lives for low income students. I’d probably add rural students to the mix too, given the shared problems of securing funding and attracting the best teachers that low income urban schools and rural schools share. Without opportunities during elementary and secondary school to discover their academic interests and strengths, students will not be able to compete come time to apply for college. Poor schools – those that don’t challenge students, that have deteriorating physical resources, that have no community support, etc. – are likely to produce poor students. I wish I had solutions to that particular problem, but I don’t. Perhaps Karabel’s column and its challenges to top tier schools will help remind readers and others who can make a difference that the problems of access are central to our problems of education.


Good question, Dan

A reporter from the Chronicle of Higher Education covered the NSF Symposium about which I complained in Argh. Again., and you can read his story online – What’s So Super About Supercomputers, Anyway?

His story doesn’t answer the question, but it does get some computer scientists on record saying essentially that CS isn’t the be-all end-all some might have us think. “Computing is a means to an end.” Well said, Clas Jacobsen. Well, to many ends, maybe.