Rudders

design, design research, HCI, HCI/d, Human-Computer Interaction, Informatics, research, science, scientific method, Uncategorized

Research has the potential to move in many different directions. There are constraints, sure. But regardless of where one starts, multiple paths reveal themselves at each step. Choosing a path is crucial for making progress. Moreover, revisiting and refining the intentions motivating one’s travels down a particular path is important. There is always value in asking why we’re doing the work we’re doing. Asking and answering this question is like steering the rudder on a boat.

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Community Data & Water Quality

design, design research, HCI, hci research, Human-Computer Interaction, research, science, Uncategorized

Most of my blog entries are announcements of publications or generic thought pieces about topics of interest. One thing I’d like to do differently going forward is keeping track of current research projects here at Penn State University’s Center for Human-Computer Interaction (C4HCI) as way of providing some insight and value to folks outside of my network; especially members of community organizations, local government, and industry.

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Community Data & Water Quality. A current project underway here at C4HCI has to do with water quality data as a kind of community data around which different stakeholders could organize and act. There are already several groups in State College collecting and analyzing water quality data, and our working assumption is that this data could be made accessible and interpretable to a wider group of residents.

In my view, and in an ideal case, the outcome of such would be a more data literate citizenry confident and capable to engage with local government around water quality (and other) policy and decision-making.

Tonight we held the first meeting of what we hope will be a series of conversations and workshops with folks who work for and with different water quality collection groups in Centre County, including: ClearWater Conservancy, PaSEC, WRMP, and Trout Unlimited. The goal of the meeting was to share our vision for a possible project built around water quality data and to engage in a meaningful conversation about what a collaboration between our groups could look like. The meeting was great. Our group learned a lot about the kinds of data these different organizations collect and about some of the barriers to sharing/using the data that we had not yet considered. We even identified a possible opportunity for supporting (one of) their efforts to build out an online resource for community members to learn more about water quality issues.

Looking forward to more!

New Journal Article

design, design research, Informatics, knowledge production, knowledge tools, philosophy of science, research

Terrific (not-so-new) news! She Ji: The Journal of Design, Economics, and Innovation published an article I wrote with Erik Stolterman about whether knowledge claims could be a useful way to distinguish research communities from one another. Here is the abstract:

While much has been written about designerly knowledge and designerly ways of knowing in the professions, less has been written about the production and presentation of knowledge in the design discipline. In the present paper, we examine the possibility that knowledge claims might be an effective way to distinguish the design discipline from other disciplines. We compare the kinds of knowledge claims made in journal publications from the natural sciences, social sciences, and design. And we find that natural and social science publications tend to make singular knowledge claims of similar kinds whereas design publications often contain multiple knowledge claims of different kinds. We raise possible explanations for this pattern and its implications for design research.

… and a link to the article, which is freely available for download. I’d welcome any comments or feedback. This is part of a broader project investigating the transfer and interplay of knowledge in research communities.

Theoretical Adequacy in HCI Research

design, design research, design theory, hci research, HCI/d, knowledge production, theory, theory building, theory development, theory-practice gap

Theoretical adequacy is an concept that comes up in some form or another in various readings in the hci literature. More often than not, authors express concern that hci is currently (or soon-to-be) theoretically inadequate. But what does this mean?

What is theoretical adequacy? Is it the degree to which knowledge produced and published in a discipline is adopted and applied in a profession? Or does it refer to our production (or lack thereof) of scientific explanations of the phenomena we study? For the former, adequacy would be a high adoption and application of disciplinary knowledge in professions. And “theory” is really just another word for knowledge produced (primarily?) in a discipline. For the latter, adequacy could be a numbers game (how many theories do we produce?) or a utility game (do our theories have high scientific utility) or even an interest game (are the theories we generate interesting?).

Whatever meaning we choose, it seems reasonable to claim that theoretical adequacy is important. It seems important that we concern ourselves with the adoption of disciplinary knowledge in the professions (but maybe we should stop using the word ‘theory’ as shorthand for disciplinary knowledge since it does not describe all knowledge produced in the disciplines…). It also seems important that the theories we produce have a high degree of scientific utility or interest. But if I set out to address the applicability of disciplinary knowledge in the professions then I may set aside entirely my concern with scientific utility. Intention and meaning are intertwined, and this message gets lost in the literature.

We can’t hope to address theoretical adequacy without addressing its meaning.

the future of hci research

HCI, hci research, knowledge production, knowledge tools, peer review, philosophy of science, quality control, science, scientific method

My PhD advisor, Erik Stolterman, recently penned a blog post called hci research and the problems with the scientific method. It’s a good post and you should read it. It was motivated by a New Yorker article written a few years ago about the ‘decline effect’ in science, which refers to the phenomenon wherein at-first positive results of scientific experimentation decline over time. I’m simplifying here, but you can read more about it in the New Yorker piece itself or the Wikipedia page on the decline effect.

In any event, this article led Erik to speculate about the implications of this ‘problem’ with the scientific method for hci research, a field grappling with a dilemma that he describes as “[stemming] from a shared view that HCI is not really a scientific enterprise while at the same time scientific research is still valued and rewarded.” He then speculates about how hci will develop in relation to science and expresses optimism about where the field will go, and here is where my thinking picks up the thread.

His last paragraph makes me think about the possibility of greater diffusion of the field and what that means for something like ‘quality control,’ in other words, “the criteria to assess the quality of the work and the teams that carry it out,” in hci research. I’m using Gibbens et al.’s definition of quality control from their book ‘the new production of knowledge’.

Anyway, when he writes that hci research could move in the direction of science ‘or’ the humanities ‘or’ design, I wonder whether that means that one of those paths will be dominant. For instance, if hci moves towards a more scientific tradition, that could mean that the humanistic and design traditions become ‘lesser research traditions’ within hci research. And if one of the traditions becomes more dominant, then quality control seems like it might be less of an issue since science and the humanities, at least, have rich histories and rigorous ways of evaluating research contributions. This might not be so true of design research.

But of course there doesn’t have to be a dominant path, and maybe a dominant path is impossible in hci research. Say hci continues to diffuse towards each of the traditions and maybe even, as he mentions, towards some new ones. That there ceases to be a dominant approach probably means that quality control becomes more context-dependent, temporary, and fluid, descriptors I’m borrowing (again) from Gibbens et al.

With respect to the dilemma he describes, denying that hci is a scientific enterprise while simultaneously valuing and rewarding scientific research, i think the possible “diffuse” future encourages a resolution characterized by valuing and rewarding scientific research, humanistic research, design research, and maybe to spend more time thinking about the relationship between these different traditions.

Understanding Designing

design, design research, design theory, philosophy, theory, Uncategorized, writing

How can we achieve a deeper understanding of designing

There are many ways to answer that question. We can achieve a deeper understanding by engaging in a design process, by reading about design, by critiquing designs (or designing)… all roads of inquiry lead hopefully to one thing: deeper understanding. Achieving one step closer to a thing about which we’re curious. [I like the “step” metaphor, which is not mine, by the way. I once asked a friend why he’d been listening to Mozart for the last thirty years. He said, “Because each time I do I get closer to him.” Achieving a deeper understanding of anything puts us one (perhaps many) step(s) closer to it. But there are many ways to take the steps. So, how do you decide?]

How do you determine whether to design, read about design, critique designs, or scrutinize design theories? How do you decide whether to take a philosophical approach, a scientific approach, or a designerly approach? None of these are really easy questions, so don’t expect any easy (or for that matter well-formulated) answers.

I met Karl Popper for the first time last year. I know. 30 years old and I’d never read Popper before. Or Thomas Kuhn for that matter. Boy did I miss out. But no longer! Anyway, I’m still getting to know Popper but he and I have something in common. We’re both curious about what it means to “be” something. Popper was curious about what it meant for a theory to be scientific as opposed to something else. I was curious about what it means for a theory to be designerly as opposed to something else.

Our overlapping interests fit together quite nicely in a (thankfully still current) discourse within the design community about the relationship between design and science. You see, since design is a relatively new “discipline,” it is helpful to compare and contrast it with more mature disciplines like science in order to establish its “own” identity. Among others, I know at least the philosopher Martin Buber wrote about distancing and relating as methods for ascertaining identity. In what ways is design different from science (distancing) and in what ways is it similar (relating). If I had to speculate, I’d say that the pendulum is swinging towards relating at this moment.

But the relating questions asked, right now, maybe have less to do with what design and science have in common and more to do with how to negotiate the relationship between them. What can science do for design? What can design do for science? Maybe negotiate is the wrong word. Maybe optimize is better. Regardless, both are valuable questions. Both equally meritorious of answers. Both signify a shift in thinking about design and science not as competitors but as teammates.

It’s possible to use scientific and philosophical-scientific approaches to study design in ways that help the design research community attain a deeper understanding of the object of its inquiry. And this is how Erik Stolterman and I are going about it at the moment. In our work, we don’t suggest that what science has trumps what design has. But we are saying that science offers design something worthwhile and interesting.