Science is for People; Not for Itself

I am still puzzling over something someone said recently in a conversation forum I am part of:

"Technology is for People, Science is for Science".

This statement makes no sense on many levels.  According to the American Heritage Dictionary:

"Science: 1a. The observation, identification, description, experimental investigation, and theoretical explanation of phenomena...4. Knowledge, especially that gained through experience"

and from the same source:

"Technology: 1a. The application of science, especially to industrial or commercial objectives. 1b. The scientific method and material used to achieve a commercial or industrial objective..."

Technology and science have several features in common, and indeed they overlap in significant ways. Not so distinct as some might think.

Another practical objection: why would anyone take part in science if not for some reason that has something to do with themself? I'm not talking only about straightforward material objectives (although those apply) but also about objectives that have to do with creating, preventing, addressing, exploring change. Change in something. Something we care about. With that in mind, can you imagine science existing in a vacuum?

Let's say the writer holds to the related belief that knowledge should be pursued for the sake of gaining knowledge. It is hard for me, endlessly curious me, to argue against learning for the sake of learning. Because you never know when it might come in useful. Oops...useful. Useful, using, used. Knowledge for the sake of knowledge (and nothing else, not ever!) would mean no application of that knowledge, wouldn't it? Nothing Useful.

Or...still on the idea of engaging in knowledge acquisition through science for the sake of science itself...is that even possible? If I enjoy undertaking scientific inquiry, then am I not doing so in part for myself? Yes, I am. I wouldn't believe anyone who claimed otherwise. If I hate undertaking scientific inquiry yet take part in it anyway, then there is an even stronger personal motivation (unhealthy as it may be) at work here.

I am no Physicist, but I have read enough about quantum mechanics to understand that if one adheres to a quantum view of the universe, then it is virtually impossible (in fact, provably false) to claim that any scientific endeavor (however you choose to define or restrict the term) could possibly take place without interactions between those conducting the science and the objects of the investigation. Scientific investigation, science, cannot exist in and of itself and for itself.

Finally, let's talk ethics for just a moment. There is something creepy about claiming, in this globally connected (and often violent) 21st Century, that we humans should pretend (yes, I said pretend) that when we take part in scientific investigation or exploration or experimentation, that we can do so without societal repercussions. If we instead embrace the interaction of science with society, and the fact that we do engage in science for very human reasons, we have the opportunity to point that science towards positive goals and outcomes.

Interdisciplinary Computing Meeting 3: Day 1

This is quite the post for several reasons. I am in Washington DC attending the third Interdisciplinary Computing meeting. I posted about the previous two earlier this year [the January meeting, the April meeting] . When we were at dinner, I was sitting next to someone who is in the arts and telling him how I was very interested in finding an interesting project that crossed over computer science and the arts for a chapter in a future edition of my book. Well, I got back to my hotel room and discovered that the video card on my motherboard has gone out. So I am writing this post on a psychedelic smeary LSD reminiscent screen - and I can't really read what I'm writing. This is not exactly what I had in mind when I asked for a convergence of art and computing. Beware what you ask for! For the next two days I'll be writing this way, as a replacement part will be meeting me back in San Diego later this week. Meanwhile...have patience with the typos and lack of editing because I can't see beyond the pulsating purple and lime green.

So on to the meeting report.  As always, all of the comments in this post are my interpretations and reflect my perspective on what occurred. They are not any "official" pronouncement and there may be others at the meeting who have a different set of thoughts. If that is you, please chime in!

Today was the most incredible example of synergistic conversations that can come out of putting passionate widely divergent thinkers together. 

Two of our meeting goals (as laid out by our trusty leaders Boots Cassel and Ursula Wolz) are to identify the breadth that is Interdisciplinary Computing (IC) and how to Facilitate Interdisciplinary Computing. Lynn Andrea Stein from Olin College talked about the interdisciplinary nature of Olin, an engineering school that was able to design interdisciplinarity into itself in a holistic way in part because they were able to start from the ground up approximately 10 years ago. Valerie Barr from Union College, founded in 1795 and the first college in the United States to offer engineering programs, provided an interesting contrast as she spoke about her work with a large range of successful IC programs.

A common theme was the infusion of computing into courses outside the traditional curriculum as well as a major rethinking of CS coursework - both institutions are having great success, attracting more students into the CS courses and increasing diversity.

With the audience of CS faculty, arts faculty, education, math (and more) faculty chiming in and asking many questions the phrase came up: Hearts, Minds and Culture. All three must be addressed. Further discussions delved into what that means. At the faculty level, student level, institutional level.

We had two breakout sessions and in both I was extremely priviledged to sit with some of the most interesting and engaged people. We wrestled with tough questions such as:

Outcomes are important (we all agreed) as are Goals - should Goals come first, followed by Outcomes followed by metrics for assessing them, or perhaps should desired Outcomes be the starting point with the other items emerging from there? It turns out to be a fascinating way to turn your thinking on its head.

Verbs vs. Nouns. Several breakout groups  (including ours) independently came up with this terminology to describe how we must stop thinking in terms of Nouns (e.g. "content") and think in terms of Verbs (what do we want to DO, to have students DO). And if we make the mistake of framing Goals in terms of Nouns instead of Verbs, we will undercut the whole purpose of trying to be innovative and creative and flexible in our approaches among different departments. Noun (content) orientation can lead to "content wars" in many cases and a lose-lose situation, as opposed to a win-win situation in which everyone can find common ground.

Very interesting idea. Think in terms of Verbs - it makes sense that this orientation would lead to a greater chance of finding mutually beneficial modern ground among widely diverse faculty. Gets us away from the dreaded "coverage debates" many of you no doubt know too well.

I'm going to short change some of the day's activities a bit in order to keep this to a reasonable length for a post, but there is one last item that energized me so much I must mention it. One participant, during a full group discussion, asked the question: should we think of Interdisciplinary Computing as "corrosive"? Corrosive in that it breaks down institutional boundaries and structures? And if so, is it corrosive by its very nature or is it something that those involved would want to specifically focus on? Corrosive. Fascinating. That is such a vivid word. Think about that will you? 

The same person followed up with this thought: if Interdisciplinary Computing is indeed corrosive, then the theoretical ground of doing IC work changes. 

IC is rhizomatic he posited. I know what a rhizome is (in a general sense), but I had to ask for an explanation in the context of this conversation. He explained, (and I try to closely paraphrase) – you can’t teach what you want to teach from any one source. You break something and it will find its way around via  a different route.Wow... think on that one too won't you? This is what you get when you work with interdisicplinary minded people from different disciplines. 

Finally, my vocabulary was expanded even further in the context of IC when in a breakout session we were discussing the topic of forming and sustaining IC community. One member of our group brought up this idea, which we all latched onto: the notion of the Interpersonal as equally important to the notion of the Interdisciplinary. The importance of realizing that it is relationships between people that will make or break IC and that a strong focus on developing, supporting and maintaining interpersonal relationships among *people*, not just "disciplines" is vital. 
 

Interdisciplinary vs. Interpersonal. Put another way: There is interdisciplinary work but there are interpersonal relationships b/w faculty and we need to find ways to facilitate and support those relationships. Equally or possibly even more important. 

And finally, the most mind blowing IC vocabulary expansion  for my afternoon came with someone in our group suggesting we think about IC this way: as Inter-Epistemological.

What?

Inter-epistemological – theories and ways of knowing. The interconnectedness of different models of ways of working. 

In digging around for some definitions of "inter-epistemological" someone found a previously published paper with an eerily provocative title: 

“Moving beyond interdisciplinarity: Academic Reflexivity in an inter-epistemological research program, celebrating indigeneous knowledges: Peoples, Lands and Cultures” 

 Think about Interdisciplinary Computing (corrosive and rhizomatic) in terms of that phrase. 

From purple smeary-land, over and out for the evening. 

This post was updated on 11/10/11 to fix typos and add links.

Interdisciplinary Computing: Bumps and Holes in the Road

There are of course setbacks and challenges to implementing interdisciplinary computing and our group discussed those as well (if you haven't read the previous two posts, this is the third in the thread). As we had people with backgrounds past and present in biology, computer science, math, physics, music - performance and theory, architecture (not the computer kind), healthcare, there were lots of angles.

In our first morning discussion of these challenges, some themes popped out, just as they had with our discussion of positive experiences. Here is some of what arose for consideration:

Lack of common vocabulary. Specialties have their own lingo, buzzwords, abbreviations, and sometimes the words are the same words used by another field but with different meanings. Engaging in conversation with a specialist in another field can be an instant reminder about how much we have internalized and take for granted when we talk among ourselves.

Different perspectives on appropriate methodologies for research, assessment, reporting, project development. This is a huge topic. Simple to explain and discuss (but not necessarily resolve): is first person or third person expected in a formal write up? Not at all simple to resolve: is statistical or qualitative research desired or valid...what type of statistical or qualitative...how is rigor agreed upon? Really difficult: what does the other field actually *do* when they design and implement a program or project and can it be (should it be) fully understood by the participant from another discipline who works on the project?

Application level skill issues. This point follows up on the last point in the previous paragraph. One example: Discipline X wants to use software A; Discipline Y wants to use software B. Both have their well supported reasons. How to resolve the question to everyone's satisfaction? Similarly, programming and programming language issues can be "exhausting" as one person put it so well. What to use, how many to use, does it have to be a specific language? You know, we have these conversations even within computing; we exhaust ourselves talking about languages. When interdisciplinary teams tackle the language questions the discussion increases in complexity several orders of magnitude.

Trust. This is perhaps one of the biggies. Perhaps the biggest. People related experiences about the need to build trust between disciplines, between people at different levels of an organization, between people with different responsibilities.

Even when there is abundant goodwill on all sides trust has to be earned. It cannot be taken for granted or else some innocent blunder may set back or seriously damage a project. Sometimes, there are large silos that people work in and these have to be bridged. Note: lots of words were used, and I'm not sure which I prefer - bridging seems to convey the positive intentions of everyone in the meeting.

What is computing and/or computer science anyway? This is another topic where even within our own computing discipline(s) we do not always agree. Exhausting. Another exhausting topic. Members of our meeting related experiences about perceptions and mis-perceptions of what "it" is, and in particular how the word "technology" fits in. Similar stories have appeared on the SIGCSE list and many other forums.

I'm intentionally not repeating specific examples of the setbacks we discussed because I don't want to unintentionally embarrass anyone nor imo is it relevant for this post that is trying (with questionable success) to stay manageable in length. I want to focus on the high level issues.

A few summative related issues that lead to setbacks for interdisciplinary initiatives: the tension b/w tools and theory; specialists vs. generalists vs. interdisciplinarians (blogger thinks that is not a word... how timely!); pure vs. applied;  student majors vs. student non-majors. And the notable point that silos can occur within a department - not just between departments.

Challenges that were phrased as questions included:

How to help people in a partner discipline continue to use mutually agreed upon / developed concepts as their students move up within their curriculum? Problematic.

How to keep an interdisciplinary course from turning "light and fluffy" or just an exercise in tool use? If students don't have a quantitative background for example, how do you give them that background sufficiently to proceed with the course? Just adding a prerequisite or two or three doesn't address the problem head on.

Computer science as a discipline has our set of "big ideas". We can abstract them, but how do we then help other people to understand and want to work with them? (this harks back to the vocabulary, method and perspective challenges)

And to end on a LARGE note: there are a whole set of different challenges for the interdisciplinary team that is starting a program from the ground up vs. the team that is working within existing programs and major fields of study. Even more so when the collaborators consist of computer scientists and experts from the non sciences.

phew! Much of the above will not be news if you have been involved in interdisciplinary efforts. However! that is one reason why I chose to start the conversation several posts ago with the upbeat and positive side of this work. No problem is impossible to address in one way or another. But to do so we had to first lay them out and lay them out we did!

Interdisciplinary Computing: Finding Common Ground, Experiencing Joy, Tangible Benefits

I spent the day meeting with a group of 15 dynamic people from around the country from academia and industry, who are all passionate about and actively involved in some way with interdisciplinary computing. At the helm of our 2 day meeting: Boots Cassel from  Villanova University Computing Sciences and Ursula Wolz from The College of New Jersey Computer Science. This was the first of several meetings and we were there to begin an ongoing conversation about how to support interdisciplinary computing education. This was our "why are we here and where are we going" meeting. Day 1.

Boots made a comment early on that stuck with me: "We need to give as much as we get".  That phrase reflected the tenor of our conversation even as we wrestled with definitions, perspectives, categories, labels, experiences and visions. 

I previewed the question of what interdisciplinary computing is last week - imagine that conversation magnified, expanded and fueled by 15 never shy, highly experienced practitioners.

That is where the fun started, and continued...Around more delicious food than I can begin to describe (we'll see in a few days if I can still walk upright) we started off by  working to establish common ground and perspectives. Almost immediately we were directed into small breakout groups for sharing our best experiences with interdisciplinary computing, the setbacks we experienced, and what an ideal climate for interdisciplinary computing education would look like. 

It is always nice to start out on a high note, and considering that overall, the day was one big high note (I don't think I'm out on a limb by making that generalization) I'll share this post on part of our pre-lunch breakout conversation - the process of discussing some of our best experiences with interdisciplinary computing. 

Besides, I need to keep my head from exploding with the effort of trying to say too much in too small a space. 

Finding Common Ground. People shared their satisfaction and joy when faculty from different disciplines reached out to successfully work together, overcoming hurdles (different topic) and creating something - a class, a curriculum, a project, an internship, research, a job - that neither could have done without the expertise of the other - as equals.  1 + 1 != 2 Rather, 1 + 1 > 2  (I hope my tired colleagues don't take that literally and think all the food has addled my brain)

Finding Common Ground.  Between combinations (pick any) of universities, K-12, industry, disciplines, departments, various sciences, humanities. It is a cultural issue as well as a content issue.

There is clearly something wonderful that happens when people from across disciplines and associated cultures work successfully together. Aside from the practical point that it "looks good", it feels good, judging by the way people were telling their stories. A few of us did a little bit of hopping around in our seats and there was the occasional gesticulating of limbs.

Not only students, but faculty are able to view the world in a new way when a computing person and another disciplinary person successfully collaborate and break new ground. One approach, discussed particularly enthusiastically and with many examples by Bob Panoff from the non-profit Shodor, was the power of harnessing computing technology to find common ways to describe the world through modeling and bringing phenomena to life. Stories form in people's minds and the world takes on new meaning.

Someone pointed out that in these collaborations, we are forced to address issues, details and concepts we never would have thought of otherwise. 

Personally, I would prefer to say that I am "privileged" to address issues, details and concepts I would not have thought of or encountered otherwise. To me,  interdisciplinary computing, especially when it improves people's lives in some way, however small, is a constant exciting exploration and adventure.

Tangible Benefits to Students. Industry jobs are often (always?) interdisciplinary in some way so employers like students who have these skill sets through direct experience. For example, they work better on teams and can more easily shift to new areas within their company. 

Many new terms were tossed up for consideration just within this part of the conversation: convergence; intertwining, cross-disciplinary, multi-disciplinary, inclusiveness. 

A lot of good things to think hard and deeply about.

Contextualized Computing Taken to the Next Level

Something that is clear to me about The Nature of Computing perhaps needs to be tossed out there for wider consideration. Maybe you (being direct here for a minute) haven't thought about it the way I'm about to propose. After all, modern learning theories are all about how people perceive the world differently from one another! I'm talking about that Big Question: "what IS computing?"

If you are like me, sometimes you hear this topic come up and want to sneak out of the room quietly. Stay with me for a minute ok?

As I was writing my last post about the arguments for and against contextualized courses, I was thinking wouldn't it be great if all computing classes from CS1 up through the most advanced theoretical coursework were contextualized? Grounded in exciting real world use?

Then I started thinking about that question concerning "what computing IS". (don't touch that browser button just yet!)

I started mentally playing with the words "contextualize" "interdisciplinary" "integrated", all words I have used in recent posts - words used by different people in different...contexts (sorry, couldn't help that).

What do "contextualize" "interdisciplinary" "integrated" all have in common?

They have to do with making connections. Making connections between content and ... something. Something concrete, something "real", something (by my extension) interesting. Something beyond the abstract interestingness that many computer scientists and computing educators see in the raw content for its own sake.

Making connections throughout the curriculum. I like the sound of that as a catch phrase. That would be a productive way to think about making computing interesting to many more students (parents, legislators?). We know that computing underlies (or overlays!) so much in the world around us. Well, by making connections to it, we can  walk the talk in and outside of class.  Students, the public in general, don't have to take our word for it. From Day 1 it is just there. And it does NOT mean watering down our content or lowering our standards. That is a straw man argument. Really.

Consider: the redesign of a computing curriculum such that every class incorporates making connections to an outside world context.

Consider: that making connections is viewed as integral as any other aspect of the course.

What if a course that does not make significant real world  connections is considered a poorly designed course both from computing and pedagogical perspectives?

Take the above three suggestions as non negotiable givens. Suddenly everything looks different doesn't it? Radical idea?