Is Canada losing the lab-rat race?

Good article in Saturday's Globe and Mail by Erin Anderssen and Anne McIlroy.

Ariana Rostami ranks chemistry and biology as her favourite classes. She gets top marks in her advanced Grade 11 courses and is happy to discuss quantum mechanics. But ask her about a career in research and she grimaces as though someone suggested locking her in a dark closet.

Which is only a slight exaggeration of how she and many of her fellow students regard the scientific enterprise - they picture long, lonely nights exiled in a lab, isolated from other humans, continually begging for funding.

"Look up 'scientist' on Google," the 16-year-old says, "and you will see someone in a lab coat." At the moment, she is considering something with more immediate results, such as physiotherapy.

*snip*

How do you change education systems that often drive students away from science and build a national culture in which the best young minds naturally envision themselves as future Nobel winners and not ostracized, penny-pinching lab rats?

Just ask the students in Ottawa if they can name a Canadian scientist. "Only if he's dead," jokes Shadman Zamau, 16, before volunteering Alexander Graham Bell - whose invention of the telephone is now more than 130 years old.

It's a very eye-opening article on an important issue -- attracting young people to science research careers. There's a very interesting tension, here, of course. You always want the best and brightest to pursue research careers. But there are many things that are discouraging them.

First of all, actual career prospects are mixed at best for academia. Salaries are often only mediocre after a very long apprenticeship. Compared to other careers like medicine or law, this is definitely to science's disadvantage.

Second of all, scientists have a very low media profile and what there is of it is very poor. Again, compared to medicine and law, what's the profile of science on TV or in the movies? Pretty well the only positive images are in the CSI shows, and those are more crime shows than science shows.

Third of all, science has a low social profile in Canada. When you look at how it's published (especially the major commercial and academic houses, which virtually ignore science and what's happening at NRC Press), how it's featured in newspapers and other media, what the various governments actually do as opposed to what they say they're going to do, it's hard not to argue that we're getting the national science infrastructure we actually want.

Interestingly, the one argument that doesn't resonate with me is the idea that science is poorly taught in high school and that discourages students. I went to high school, and all the subjects were taught poorly, not just science. I had good science teachers and bad science teachers. But the exact same thing was true of the other subjects as well -- there were good and bad teachers.

Anyways, read the article. It makes these points in much more eloquent detail that I can.

BTW, I can't help seeing this particular quote in the article as a clarion call for more Canadian science blogging:

Success breeds success, he says. "As a nation, we expect our hockey teams to win because they always have. If you are good as a nation at something, there are role models for young people coming through."

Scientists themselves accept some of the blame. Samuel Weiss, who won a prestigious Gairdner Award last year for his discovery that the adult brain can produce new cells, says Canadian scientists have to get better at thumping their chests.

"As scientists, we are way too reticent to tell the story and engage the community the way scientists engage the community in other countries. ... We'll point to government, but I don't know if we have made the case about how important science is."

Science Education in Computational Thinking

Just like last year, Eugene Wallingford (CoaSL interview here) of the blog Knowing and Doing has written up some pretty detailed workshop session reports from the 2008 NSF Workshop on Science Education in Computational Thinking. Here's his Table of Contents post, which I'll be reproducing below along with some excerpts from each post.

Primary entries:

• Workshop 1: A Course in Computational Thinking -- SECANT a year later
  

  Teaching CS principles to non-CS students required the CS faculty to take an approach unlike what they are used to. They took advantage of Python's strengths as a high-level, dynamic scripting language to use powerful primitives, plentiful libraries, and existing tools for visualizing results. (They also had to deal with its weaknesses, not the least of which for them was the delayed feedback about program correctness that students encounter in a dynamically-typed language.) They delayed teaching the sort of software engineering principles that we CS guys love to teach early. Instead, they tried to introduce abstractions only on a need-to-know basis.

  
  
  
• Workshop 2: Computational Thinking in the Health Sciences -- big data is changing the research method of science
  

  In addition to technical skills and domain knowledge, scientists of the future need the elusive "problem-solving skills" we all talk about and hope to develop in our courses. Haixu Tang, from the Informatics program at Indiana contrasted the mentality of what he called information technology and scientific computing:

  • technique-driven versus problem-driven
    
  • general models versus specific, even novel, models
    
  • robust, scalable, and modular software versus accurate, efficient programs

  
  These distinctions reflect a cultural divide that makes integrating CS into science disciplines tough. In Tang's experience, domain knowledge is not the primary hurdle, but he has found it easier to teach computer scientists biology than to teach biologists computer science.

  
  
  
• Workshop 3: Computational Thinking in Physics -- bringing computation to the undergrad physics curriculum
  

  ...Further, many students do not think that computational physics is "real" physics. To them, physics == equations.
  
  This is a cultural expectation across the sciences, a product of the few centuries of practice. Nor is it limited to students; people out in the world think of science as equations. Perhaps they pick this notion up in their high-school courses, or even in their college courses. I think that faculty in and out of the sciences share this misperception as well. The one exception is probably biology, which may account for part of its popularity as a major -- no math! no equations! I couldn't help but think of Bernard Chazelle's efforts to popularize the notion that the algorithm is the idiom of modern science.

  
  
  
• Workshop 4: Computer Scientists on CS Education Issues -- bringing science awareness to computer science departments
  

  Next, Tom Cortina talked about Teaching Key Principles of Computer Science Without Programming. In many ways, Cortina was swimming against the tide of this workshop, as he argued that non-majors could (should?) learn CS minus the programming. There certainly is a lot of cool stuff that students can learn using canned tools, talking about history, and doing some light math and logic. Cortina's course in particular covers a lot of neat material about algorithms. But still I think students miss out on something useful -- even central to computing -- when they bypass programming altogether. However, if the choice is between this course and a majors-style course that leaves non-majors confused, frustrated, or hating CS, well, then, I'll take this!

  
  
  
• Workshop 5: Curriculum Development -- some miscellaneous projects in the trenches
  

  Bruce Sherwood reported a physics student comment of his own: "I don't like computers." Sherwood responded, "That's okay. You're a physicist. I don't like them either." But physics students and professors need to realize that saying they don't like computers is like saying, "I don't like voltmeters." If you can't work with a voltmeter or a computer, you are in the wrong business. That's just the way the world is.
  
  My favorite line of Landau's is one that applies as well to computer science as to physics:
  
  We need a curriculum for doers, not monks.

  
  
  
• Workshop 6: The Next Generation of Scientists in the Workforce -- computational thinking as competitive advantage
  

  How does computational thinking help the company do more better and faster? By...

  • ... letting scientists spend more time doing what they love.
    
  • ... eliminating low-value-add transactional activities in the business process.
    
  • ... boosting the speed and scalability of their systems.

  
  Notice that these advantages range from the scientific to business process to the technical. It's not only about techies sitting in front of monitors.

  
  

Ancillary entries:

• This and That -- the inevitable miscellaneous thoughts
  

  The buzzword of this year's workshop: infiltration. Frontal curricular assaults often fail, so people here are looking for ways to sneak new ideas into courses and programs. An incremental approach creates problems of its own, but agile software proponents understand its value.

  
  
  
• No One Programs Any More -- a timely conversation the week before the workshop
  

  In the time since I joined the faculty here, many departments have dropped the computer programming requirement from their majors. Part of the reason is probably that the intro programming courses were not meeting their students' needs, and our department needs to take responsibility for that. But a big part of the reason is that many faculty across campus believe as the Math faculty do, that their students don't need to learn computer programming anymore. Not too surprisingly, I disagree.

What scientists think of librarians

Ok, a slightly misleading post title mostly to get you scientists out there to read the post, but I think it gets to the core issue of a discussion happening over on FriendFeed about and article in The Scientist: Libraries 2.0: Secrets from science librarians that can save you hours of work.

Is any publicity good publicity? Is the article nasty or condescending to librarians? Do we really care what people think of us? Are we too thin-skinned?

Here's the offending paragraph:

Not the bifocal-sporting, cardigan-clad Dewey decimal experts of 25 years ago, science librarians in today's universities are a well-versed treasure trove of knowledge, even in life sciences. "People think they know how to search for things, when they really don't know how to use some search tools efficiently," says Osterbur.

With also a more postive spin:

Science librarians of today can scope out particular resources for you, give your lab a tutorial session on special database searching, or hunt down ancient and obscure citations. Here are better ways to get and manage information from popular databases, plus top tips from science librarians on how to make the most of your university and the Internet resources.

There are also some pull-sections highlighting what librarians can bring to the research table: Beyond Pubmed, Advanced Web of Science, RefWorks vs. EndNote and 10 Tips to Get the Most out of your Librarian.

So, what do you think?

Personally, I wouldn't mind getting the article into the hands of all the faculty and grad students at my institution.

(via Joe Kraus's FriendFeed)

Interview with Eugene Wallingford of Knowing and Doing

Welcome to the latest installment in my occasional series of interviews with people in the scitech world. This time around the subject is Eugene Wallingford, Head of the Computer Science Department at University of Northern Iowa and author of the blog Knowing and Doing. I've been following Knowing and Doing for most of the four years it's been running (Happy Blogiversary, Eugene!) and I've always been impressed by Eugene's insights into the world of computer science, especially from the educational viewpoint. Since it's been quite a while since I interviewed a CS faculty member, I thought it would be a perfect opportunity to see what Eugene thinks about some of the important issues in the field today. I think there's some food for thought in the interview for librarians supporting CS programs and students.

Thanks to Eugene for his thoughtful responses. Enjoy!


Q0. Hi, Eugene, please tell us about yourself, your career path and how you got to be the Head of the Computer Science Department at University of Northern Iowa.

Thanks, John, for asking me for an interview. I am honored to share a few thoughts with your readers.

From the time I was seven or eight, I wanted to be an architect. All of my career planning in school aimed that direction. Academically, I liked everything and so had a full load of math, science, literature, history, and social science.

I started college as an architecture major. While I liked it just fine, something was missing. Somehow, I was drawn toward computer science. I ended up double majoring in CS and accounting, but CS was my passion, especially artificial intelligence. I went on to grad school, specializing in knowledge-based systems. My dissertation focused on the interaction between memory and domain knowledge.

A little over three years ago, we were nearing the end of an interim department head's term. I'd never given much thought to being an administrator, but I saw many ways in which we could improve and thought for a moment that I might be the right person to help us get there. I am now ending my first 3-year term and have agreed to continue on for three more years. Looking back, I see some improvements but, frankly, had hoped to have accomplished more. This is a tough job. It lets me be a computer scientist in some ways but takes time away from doing all of the CS I love. I'm committed to helping us move forward for another term, and then we'll see.


Q1. Do you have a theory of blogging? What got you started blogging and what do you get out of it and what keeps you going? I'm sure all your faithful readers are hoping you can add comments to your blog at some point.

I don't think I have a theory of blogging. I first started because I had things I wanted to say. Every computer I had ever owned was littered with little essays, reviews, and conference notes that no one had ever seen. I'd been reading several blogs for several years and thought that starting a blog was a way to make some of my writing more permanent. If others found it worth reading, all the better.

My blog consists mostly of short pieces connected to my professional life as a computer scientist and faculty member. I make connections among things I read, write, see, and do. My one personal indulgence in writing is running, and I've written quite a bit about my experiences training for marathons. Some of my more interesting pieces in this category have made connections from training and running to software development.

Occasionally, I write something that is purely personal, or something that made me smile and laugh. I don't think anyone really wants to hear about what I eat for meals or who I am voting for in elections, so my blog has never veered in that direction. But readers get to know me as a professional person, and I do think that knowing something about the person on the fringes adds depth to how they read my other pieces.

Comments... Yes, I understand. When I first started blogging -- four years ago today (July 9)! -- I planned to add comments. The tool I use to blog is very simple and didn't make that easy. I've just never gotten around to it.

I read many blogs in which comments make a valuable contribution to the message. In others, they add little. There are many ways in which I would relish an ongoing conversation with readers. Adding comments is still on my wish list.


Q2. You blog a lot about teaching computer science. Do you have a teaching philosophy? How do you think teaching computer science differs from teaching other disciplines?

There was a thread recently on the SIGCSE mailing list about teaching philosophies. Many schools ask job applicants for a statement of teaching philosophy, and some folks think that's silly. How could new Ph.D.s have teaching philosophies when they have spent little or no time in a classroom?

I've been on the CS faculty for sixteen years now, and I can't say that I have a coherent, pat teaching philosophy even now. Were I to apply for a new job, I would have to do what those new Ph.D.s have to do: scour my mind for bits of truth that reflect how I teach and how I think about learning, and then mold them into an essay that captures something coherent about me on this day.

My blog exposes some of these bits of truth as I write about my experiences in the classroom. It will be a wonderful resource the next time I have to write a statement of philosophy.

Thinking back to all I've written in the last few years, I can see some themes. Learning is more important than teaching. Students learn when they do. Students learn when they want to do. What I can do as a teacher is to create an environment where students come into contact with cool and powerful ideas. I can organize ideas, skills, and tools so that students encounter them in a way that might spur their desire. Ask students to write programs and solve problems. Ask them to think about how and why. Ask them to go deep in an area so that they learn its richness and not its surface chemistry. Oh, and show as often as I can and in as many ways as I can how much I love computer science. Show what I learn.

That paragraph would get me started on a philosophy statement.

Computer science is an interesting mix of mathematics and programs. Most people don't realize that it is a creative discipline -- a discipline in which making things is paramount. In that sense, we can learn a lot from how writers and artists (and architects!) learn their craft.


Q3. Another of your favourite themes is how computing is infiltrating all the other sciences -- in other words we're getting to the point where it's computational everything. What got you interested in that trend and where do you see it going?

This is not as new as it might seem. Computer science has always been about applications: creating solutions to real problems in the world. The discipline goes through spurts in which it looks inward, but the focus always turns back out. When I was in college in the first half of the 1980s, there was a lot of talk about end-user programming, and even then that wasn't new. Alan Kay has been talking for forty years about computing as a new medium for expressing ideas, a medium for every person. Before that, pioneers such as Marvin Minsky said similar things.

What's happening now is a confluence of several developments. Computing power has continued to grow at a remarkable pace. Our ability to gather and store data has, too. We realize that there will probably never be enough "computer scientists" to solve all of these problems ourselves, and how could we anyway? Biologists know more biology than I ever will; likewise for economics and astronomy and geography and most other disciplines. We are reaching a point where the time is right to fulfill the vision of computing as medium for expressing and testing ideas, and that will require we help everyone use the medium effectively.


Q4. Enrollment has been an issue in the CS community for a while now. Are you happy with the current levels of enrollment? What do you think are some of the ways to get enough students of all kinds interested in CS and willing to consider it as a major? How can we improve the diversity of the students willing to give CS a shot?

We've started to see a small bounce in our enrollments, and I think this trend will continue for a while. I'm not sure that we will ever see the large growth we saw in the 1980s and 1990s, but that's okay -- as long as we recognize our need to broaden the base of people who can use computing in their own disciplines.

Figuring out how to get more students to major in CS or to learn how to use computing in their own disciplines is not easy. If I knew the answer, my school would have a lot more majors and students! There are a lot of things we can do: tell our story better; help more people to understand what computing is and what we do; introduce our ideas to more students earlier in school. One thing a lot of us have noticed over the years is that most people learn about CS as something "hard", a discipline that requires special wiring in the brain. While it's probably true that not everyone is suited to do academic research in CS, I think that everyone can learn to use computing as a medium for expressing ideas. If we can find good ways to introduce computing in that way across the population, the number of majors and the number of interested non-majors will take care of themselves.


Q5. Could you tell us a little about your research interests?

As I mentioned in my history earlier, I started in the area of artificial intelligence, a field in which computer scientists work with many others in an effort to make computers do ever more impressive tasks. Most of my work was in Knowledge-based systems, a sub-area that focused on how systems with deep knowledge of a class of problems can organize, access, and use the knowledge to solve those problems. In the mid-1990s, I began to move in the direction of intelligent tutoring systems, which are programs that help people to learn. This was probably a natural evolution for me, given my interest in how my students and I learn new areas of expertise.

In the late 1990s, I found myself drifting toward work in the area of software design and development, which led me more toward programming languages. Notions of design and language were central to my interest in AI, but I found the concreteness of supporting software developers attractive.

As a department head, I don't have much time for research. When I do have time, I work on how to provide support to programmers as they write, modify, and manipulate code. Of particular interest is how to support refactoring (changes to programs that preserve their intended behavior but modify their structure) in dynamic languages, which do not provide all of the cues we need to ensure that a modification preserves behavior.


Q6. Being a librarian, you know I have to ask what journals, conferences, etc., you find most helpful. I'm also curious about any search engines you might use, be they commercial ones like INSPEC, Web of Science, Scopus or "free" ones like CiteSeer, Google, or Google Scholar? Or anything I haven't even mentioned.

Google. That's the answer for so many things! It's my primary tool for search to find new articles. It links me to more focused technical tools like CiteSeer and the ACM Digital Library, as needed. But so many articles are now available directly on the web from their authors that the journals themselves become more like convenient packaging devices than essential units themselves. It's akin to the change in the music industry from the album to the single. Singles fell out of favor for a while, but the advent of iTunes and other music services have really changed how most people come into contact with their music today.

I don't read many journals cover to cover anymore. I do subscribe to the Communications of the ACM and am looking forward to its new format. I also follow the bulletins of several ACM special interest groups (programming languages, AI, and education).


Q7. Again, being a librarian, I'm also curious about any CS-related books you've read that you've found useful or inspiring, either recently or in your formative years.

A few years back, before I had a blog, I created a webpage for sharing books with colleagues and students:

http://www.cs.uni.edu/~wallingf/miscellaneous/recommended-reading.html


I haven't added to that list lately, but it lists most of the CS books I'd recommend yet today, including Abelson and Sussman's The Structure and Interpretation of Computer Programs, Peter Norvig's Paradigms of Artificial Intelligence Programming, and the Gang of Four's Design Patterns. It also lists books that are not technically about CS but which might change how someone thinks about computing and software, such as Stewart Brand's How Buildings Learn -- a marvelous book!

One glaring omission from this page are the works of Christopher Alexander, the inspiration for the idea of software patterns. Most everyone recommends The Timeless Way of Buiding and A Pattern Language, and I concur. But I also strongly recommend The Oregon Experiment, which describes Alexander's experience implementing his ideas on a college campus. This is a thin little volume that I found rewarding.

Most of my CS-specific reading lately has been on Ruby.


Q8. I find it interesting that computer science students still seem to be relatively high users of print books and I was wondering about your take on that phenomenon. Is it still the same or is it changing?

Philip Greenspun has described CS as pre-paradigmatic in Thomas Kuhn's sense, which means that books play an important role in how new ideas are shared and disseminated. Computing has always been rich in print books, from timeless works down to skills books with a shelf life limited by the rapid change in technology. I know many publishers are thinking about ways the market might shift into electronic versions, and more and more books are available on-line now, sometimes in their first run.

A lot of my students are reading books on-line more now than in print. A recent favorite is Why's (Poignant) Guide to Ruby, available at http://poignantguide.net/ruby/. To my knowledge, this book is available only on the web and not in print. I'm curious to see how this trend develops. My guess is that individual authors will create most of the ideas that change how we read their works, which will cascade down to how we publish.

This comes back in to some ways to blogs, which seems like a good way to close the circle on this interview. One thing I love about my blog in comparison to the essays and comments I used to write in regular text files is the ability to link directly to other works. When I drop a short piece onto my blog, it often takes its place within a web of related writings and software pages. The connections among these works adds value to what I write by giving my readers a way to find and explore related work. That is so much more convenient than a list of references at the end, even if it is also a whole lot messier.

Thanks again for asking me to contribute to your interview series.

What's an education for, anyways

A good question. It seems to me that the purpose of an education is not to confirm the student's pre-existing habits and prejudices, but to help them to explore new ways of doing things. In higher education, part of that is going to be to expand their horizons from the stuff they learned in high school, to learn how to use new tools for self-expression (ie. for someone who has never created a web page, that would be a good thing to learn), to learn how to use old tools for self-expression (ie. for someone who has never written a literature review paper, that would be a good thing to learn) and even to learn how the scholarly landscape operates in the discipline they are studying.

Let's see what some other people have had to say on this recently.

First up, sociologist Eszter Hargittai, in an interview at Wired Campus talks about how web savvy students really are as opposed to how savvy everyone assumes they are. Or hopes that they are.

Q. What are the challenges for colleges that hope to better educate students about Web use?

A. How do you fit this into the curriculum? Is it supposed to be an academic department, or through libraries? How can you legitimately stand in front of a classroom when the students have an assumption that they know more about technology than you? At the beginning of my classes, I tell my students, “I know you don’t think I know as much as you because I’m older. I assure you, I know way more than you guys about this.” And they sort of smile, but by the end of the class they realize I’m right.

That's really one of the great challenges of libraries going forward: convincing students that we have something to offer to them, that we know something that they don't, that old fogies can be web savvy.

As far as learning to be a scholar, Wayne Bivens-Tatum points out that the way the humanities are studied really hasn't changed. Our obsession with being "innovative" in the way we deliver collections and services to humanities scholars is, beyond a certain point, kind of delusional:

The humanities are about reading and thinking through language and texts. We can’t assume that they inhabit a “visual culture” and there’s an end on it. There’s almost no visual culture in the humanities outside of art or film criticism. Humanistic scholars read, write, discuss, argue. They don’t make collages or Youtube videos, at least not as a central part of their scholarship. They might record a lecture, but that’s usually much more boring than reading an essay. I don’t know why we sometimes assume that the newest generation is somehow too slow or shallow to be able to adapt themselves to this scholarly tradition. They play video games, and they read books. They make videos, and they write essays. The liberal arts, the studies proper to free and rational human beings, are alive and well. That they aren’t the stuff of reality TV or celebrity websites means nothing, because they have always been the domain of the relative few who seek to question or reflect upon the world around them. Higher education in America gives us the opportunity to expand the benefits of the humanities, not assume that such study is irrelevant to the desires of today’s youth while we desperately flail around trying to seem relevant.

Now, I don't think what Wayne is saying applies to the sciences in quite the same way. After all, the escience computational revolution is radically changing the way that scientific data, information and knowledge themselves are being generated. And the way science is being communicated. But on the other hand, it really does help to know where you've been to be able to figure out where you're going. In that sense, new scientists can truly benefit from diving into all those old books and journals mouldering on the shelves and understanding how science was generated and communicated in the past.

The next bit is from an actually rather distasteful little article whose main point seems to be, "I'm a visual arts scholar, so the art I like is intrinsically better than the art you like." As someone who appreciates both Black Sabbath and Miles Davis, I find it rather condescending. But, if you change the the phrases around the word "taste" for "intellectual habits" or "searching skills" or "confidence with technology" I think there's something valid:

Freshmen arrive on campus with their own taste in everything from music to clothes, food, and electronic equipment. Consciously or not, they also have developed certain tastes in art. Taste being what it is, and young people being what they are, freshmen usually arrive with either no taste or very bad taste — not just in art, but in everything — but in either case, they’re very comfortable with their tastes. They don’t expect or want to change them. The paradox is that it just so happens that their taste, which they consider to be something that’s very particular and individual, is, in most important respects, exactly the same as that of most other college freshmen.

So, what's an education for? It seems to me that it's about changing the way you see things, not confirming or pandering to easy habits or ideas.

National Engineering Week!

It's National Engineering Week next week, with the Ontario page here.

As usual, there's a nice supplement in the Globe and Mail, although the 2008 edition isn't up yet. As usual, lots of good articles including ones on Environmental challenges, Alternative Energy, Engineering in the Life Sciences, Auto Innovation, Robot Games, a couple of Engineering Careers and Engineering in Space.

Now that York's Engineering Program has been accredited, we actually figure quite prominently in the supplement. There's a nice ad and Prof. Spiros Pagiatakis gets quoted in the article on Environmental Challenges.

Not only that, but there's a a good chunk of an article devoted to Space Engineering projects at York. Projects by Profs. James Whiteway and Ben Quine are featured -- and a rather fuzzy picture of Ben with his thermal vacuum chamber.

Labreporter.com: Films to take you to the heart of science

Thanks to Tara Shears, a particle physicist at the University of Liverpool for alerting me to a great project she and science communicator Alom Shaha are spearheading.

It's Labreporter:

Every day, thousands of people around the world get up and go to work in a science lab somewhere. Some make major discoveries leading to huge technological advances while others quietly add to humanity’s knowledge of the world and how it works. Labreporter.com provides a unique glimpse into laboratories from around the world, revealing the people who work in them, what they do, how they do it and, most importantly, why they do it.

What up so far are six videos on particle physics, in particular about the LHC. All are hosted in YouTube and can be viewed here on the Labreporter site.

I've watched a couple of the videos so far and can say that they're great. The videos, brief descriptions and related links are here:

• Big Bang V2.0
  
• Sizing things up
  
• The Mystery of the Missing Mass
  
• Hunting for Higgs
  
• The matter with Anti-matter
  
• B is for Beauty

Knowing and Doing on putting the Science in Computer Science

Knowing and Doing by Eugene Wallingford is one of my favourite CS faculty blogs. His commentary is always interesting and relevant; a bonus for us librarian types is that he often gives keen insight into the minds of working CS faculty, how they think, the problems they face and mostly, what they're thinking about.

Way back in November (yes, I know, I'm still recovering from all the posting about science books) he published a series of conference reports on the SECANT 2007 Workshop. The workshop topic was Science Education in Computational Thinking, in other words, how computational methods have infiltrated the practice of science at all levels. An important topic and one that I find very interesting and relevant.

Eugene was kind enough to publish a table of contents post of all the workshop-related posts, which I am sort of reproducing below. I've taken his TOC post and to each entry I've added a brief quote from the relevant post. Nevertheless, please visit a couple of Eugene's post and check out the details. As well, what he's done here is really a model for blog-based conference reporting, one of, if not the best, examples I've seen. I am certainly going to try and model my own conference blogging after what Eugene has done here.

Primary entries:

• Workshop Intro: Teaching Science and Computing (on building a community)
  

  SECANT's goals are to build a community that is asking and answering questions such as these:

  • What should science majors know about computing?
    
  • How can computer science be used to teach science?
    
  • Can we integrate computer science effectively into other majors?
    
  • What will the implications of answers to these questions be for how we teach computer science and engineering themselves?

  
  
  
• Workshop 1: Creating a Dialogue Between Science and CS (How can we help scientists and CS folks work together?)
  

  The second speaker was Noah Diffenbaugh, a professor in earth and atmospheric sciences at Purdue. He views himself as a modeler dependent on computing. In the last year or so, he has collected 55 terabytes of data as a part of his work. All of his experiments are numerical simulations. He cannot control the conditions of the system he studies, so he models the system and runs experiments on the model. He has no alternative.
  
  Diffenbaugh claims that anyone who wants a career in his discipline must be able to do computing -- as a consumer of tools, builder of models. He goes farther, calling himself a black sheep in his discipline for thinking that learning computing is critical to the intellectual development of scientists and non-scientists alike.

  
  
  
• Workshop 2: Exception Gnomes, Garbage Collection Fairies, and Problems (on a hodgepodge of sessions around the intersection of science ed and computing)
  

  This list tied well into the round-table discussion that followed, on what computational concepts science students should learn. I didn't get a coherent picture from this discussion, but one part stood out to me. Bruce Sherwood said that many scientists view analytical solution as privileged over simulation, because it is exact. He then pointed out that in some domains the situation is being turned on its head: a faithful discrete simulation is a more real depiction of the world than the closed-form analytical solution -- which is, in fact, only an approximation created at a time when our tools were more limited. The best quote of this session came from John Zelle: Continuity is a hack!

  
  
  
• Workshop 3: The Next Generation (what scientists are doing out in the world and how computer scientists are helping them)
  

  From these two talks, it seems clear that domain scientists and computer scientists of the future will need to know more about the other discipline than may have been needed in the past. Computing is redefining the questions that domain scientists must ask and redefining the tasks performed by the CS folks. The domain scientists need to know enough about computer science, especially databases and visualization, to know what is possible. Computer scientists need to study algorithms, parallelism, and HCI. They also need to take more seriously the soft skills of communication and teamwork that we have encouraging for many years now.

  
  
  
• Workshop 4: Programming Scientists (should scientists learn to program? And, if so, how?)
  

  And, yes, I do think that science students should learn how to program, for two reasons. One is that science in the 21st century is science of computation. That was one of the themes of this workshop. The other is that -- deep in my heart -- I think that all students should learn to program. I've written about this before, in terms of Alan Kay's contributions, and I'll write about it again soon. In short, I have at least two reasons for believing this:

  • Computation is a new medium of communication, and one with which we should empower everyone, not just a select few.
    
  • Computer programming is a singular intellectual achievement, and all educated people should know that, and why.

  
  
  
• Workshop 5: Wrap-Up (on how to cause change and disseminate results)
  

  On how to cause change. At one point the discussion turned philosophical, as folks considered more generally how one can create change in a larger community. Should the group try to convince other faculty of the value of these ideas first, and then involve them in the change? Should the group create great materials and courses first and then use them to convince other faculty? In my experience, these don't work all that well. You can attract a few people who are already predisposed to the idea, or who are open to change because they do not have their own ideas to drive into the future. But folks who are predisposed against the idea will remain so, and resist, and folks who are indifferent will be hard to move simply because of inertia. If it ain't broke, don't fix it.

  
  

Ancillary entries:

• A Program is an Idea (going farther on why scientists, and everyone else, should learn to program)

  A scientist can communicate an idea to others with a program, but they can also think better with a program. Graham captured this from the perspective of the software developer in the article I quoted earlier:
  
  Your code is your understanding of the problem you're exploring.
  
  Every programmer knows what this means. I can think all the Big Thoughts I like, but until I have working a program, I'm never quite certain that these thoughts make sense. Writing a program forces me to specify and clarify; it rejects fuzziness and incoherence. As my program grows and evolves, it reflects the growth and evolution of my idea. Graham says it more strongly: the program is the growth and evolution of my idea. Whether this is truth or merely literary device, thinking of the program as the idea is a useful mechanism for holding myself accountable to making my idea clear enough to execute.

  
  

Preparing students for jobs

With all the book list posting in December, the drafts of "real posts" have been piling up quite a bit. So, it's time to do a bit of catch up!

Preparing Students for Jobs by Michael Mitzenmacher at My Biased Coin starts a really interesting discuss about how a CS education works as a job strategy. He asks CS students to comment based on the following question:

Please tell me, in your experience, did your education prepare you for your life after in the real world. (For current students, you can comment on how you feel your education is preparing you.)

Twenty-five responses so far, mostly pretty revealing, coming down on both sides of the practical vs. theoretical. One example:

While in university I was constantly made to believe by professors and colleagues that to get the really good jobs you only need to be smart, and specific skills don't matter because you can learn them on the job. The atmosphere was that you don't want the job if they have the nerve to ask you about programming in the interview (because you are supposedly too good to be asked about programming skills).

This is BS. For the best jobs you are competing with people who are just as smart and know how to program. And, if you are not a very good computer scientist (in the practical sense), they might as well hire a physicist or a mathematician (who actually *know* math).

Your employer will give you time to learn what is specific to the company or the job, not to fill the gaps in your basic education.

Of course, that's an eternal struggle in any academic program, balancing teaching students to "think like a computer scientist" (or librarian or whatever) versus teaching them some of the practical skills that will help them get their first job. Thinking back to my own final semester at McGill, I recall taking two courses, one on Business Reference Sources, one on Personnel Management and combining those with a full course Practicum placement at the McGill Physical Sciences & Engineering Library and a reading course with Dr. Andrew Large on Digital Libraries. I still have the DL paper I wrote kicking around somewhere. I should brush it off and see if it still makes any sense. (Note: the McGill PSEL is now the Schulich Library of Science and Engineering)

Eludamos: Journal for Computer Game Culture

Via Open Access News, the first issue of a new OA journal on gaming culture.

Their goals are pretty ambitious:

In ELUDAMOS we want to challenge this misconception by celebrating the cultural and economic significance of digital game play in our technological world. We want to discuss digital games not only as recreational medium for digital natives but rather as a driving force which is shaping the future of our society. We see Wikipedia not only as a “free encyclopedia that anyone can edit”, we see it also as a Massively Multiplayer Online Game in which editors compete for the top positions in elaborate high score lists detailing page edit statistics. In this sense digital play is at the core of what French philosopher Pierre Levy called demodynamics, a post-democratic process in which our networked society is increasingly gaining control over the dynamics of its own intellectual progression. It is this evolving cultural significance of digital games and digital game play that we want to capture and explore in ELUDAMOS.

The TOC is a combination of articles, reviews and a conference report.

• Ordinary Gamers - The Vanishing Violence In War Games And Its Influence On Male Gamers by Hartmut Gieselmann
  
  
• Emotion and Story in "Shadow of the Colossus": A Meta-Review by Peter Purgathofer
  
  
• Black and White: Attending the Games Convention 2007 by Ralf Stockmann

Creating a science of games

Really cool looking section in the latest Communications of the ACM v50i7. Some highlights:

• Games for science and engineering education by Merrilea J. Mayo
  
• Games for training by Ralph E. Chatham
  
• How to build serious games by Henry Kelly, Kay Howell, Eitan Glinert, Loring Holding, Chris Swain, Adam Burrowbridge, Michelle Roper
  
• Using storytelling to motivate programming by Caitlin Kelleher, Randy Pausch

There's a lot of other very interesting stuff from this issue which I'll highlight in a later post.

Here & There

A couple of items from recent days:

• Via Discovering Biology in a Digital World, the 10th anniversary issue of Bioinform has interviews with a number of the leading lights in the bioinformatics field, including Russ Altman, Amos Bairoch, Rainer Fuchs, Steve Lincoln, Gene Myers and Lincoln Stein. Some of the questions that were asked all of them are: What are some of the biggest challenges the field still has to overcome? What do you think are some of the most exciting research areas in the field right now? What advice would you give to a student thinking about a career in bioinformatics?
  
  This little taste from the interview with Lincoln Stein:

  What advice would you give to a student thinking about a career in bioinformatics today?
  
  Learn as much biology as you can. Learn statistics. A lot of it comes down to statistics. And don't worry too much about learning a particular programming language because they're all transient anyway.

  
  
  
• Fortran is 50! I have a real soft spot in my heart for Fortran as it was the first programming language I ever learned, way back in 1981 or so. The most recent issue of Scientific Programming celebrates the language and it's past, present and, yes, future.
  
  
• The science blogosphere controversy du jour is about the role of science journalists: are they a necessary evil? Is it worth submitting to an interview if you're misquoted? Are they really science's best hope for greater recognition and understanding in society? Bora Zivkovic of A Blog Around the Clock has his usual great summary post, with some additional links at Aetiology, where it all started.
  
  Me, I'm a huge consumer of science journalism. In many ways, a lot of my understanding of science and scientists is mediated by them; as readers of this blog know, I consider disciplinary knowledge and understanding to be a core aspect of subject librarianship and I rely quite a bit on journalists to get me inside the head of scientists via newspaper and magazine articles, books and a/v documentaries. On the other hand, I also know that the journalism biz is fast and furious, with lots of people writing about things tht aren't their specialty. So, I expect there to be some inaccuracies, but I do know that I can rely of some journalists more than others. Peter Calamai of the Toronto Star is pretty good as are Natalie Angier and David Quammen and others. I always make sure to read the year's best science and nature series every year to make sure I get the best of the best in science journalism.

SciTalks

Via A Blog around the Clock, a link to SciTalk.com, a kind of portal page for science videos. There's lots of cool stuff here which I've only become to explore. This site aggregates links to videos on other sites rather than hosting the videos themselves, so you'll encounter items that will require various bits of software to be installed before you can view the videos. You might need Flash or RealPlayer or some such.

Check out their Welcome to SciTalks blog post.

Scitalks is important and needed. In the general trend toward democratizing education, we hope that it can become an important tool for educators, home schoolers and those who are wanting to educate themselves.

In another context, science’s credibility is at the heart of a conflict where the opponent is well funded and well organized. We’re a society trained to sound-bites. Our critical thinking skills are eroding. Scientific thought is by its very nature complex and challenging to communicate to the general public. Most universities aren’t up to the task and the scientists themselves are involved in a system where the public is at the bottom of the list of the masters they must satisfy if they want to remain in research. They must publish or perish, and peer review is where they publish.

Yet there is no one else who can better convey the necessity, drama and passion of their work than the scientists themselves.

*snip*

The task ahead of us is, in one sense, curatorial. We are collecting the pearls of our civilization. We encourage universities and scientists to give us their links and videos to catalog and care for. We have dreams for the site, but also know that your dreams and suggestions will likely shape it more than ours from now on. We want to hear from you. We would love your help.

The videos are at all levels, some highly technical and some of a more popular nature. Some of the subject areas covered include: astronomy, biochemistry, botany, engineering, environment, history of science, information technology, math, medicine, philosophy of science and space science.

Enjoy!

On Computer Science

A couple of recent interesting items that probably don't merit their own posts:

• Eugene Wallingford at Knowing and Doing on some favourite books and teaching as storytelling:
  

  For teachers, I think that the key to the effective story is context: placing the point to be learned into a web of ideas that the student understands. A good story helps the student see why the idea matters and why the student should change how she thinks or behaves. In effect, the teacher plays the role of a motivational speaker, but not the cheerleading, rah-rah sort. Students know when they are being manipulated. They appreciate authenticity even in their stories.

  
  He mentions a couple of Gerald M. Weinberg's books as among his favourites and many of his books are also among my favourites. And apparently, Weinberg blogs here on writing and here on consulting, which I didn't know about.
  
  
• Mike Hendrickson has started doing the State of the Computer Book Market quarterly surveys at O'Reilly Radar, taking over from Tim O'Reilly. His first effort is very detailed and very good, in four parts overview, technologies, publishers and programming languages. I'm not going to attempt to summarize the whole thing because if you're interested in the computer book market, you should probably read the whole thing, but I thought this little bit from the first part was worth quoting:
  

  n the first quarter of 2006, new interest in web development associated with Web 2.0 and strong performance of books on digital media applications like Photoshop helped to drive the market. In the first quarter of 2007, we hoped that the Microsoft Vista and Office 2007 releases would cause a similar sharp increase in our trend lines. That has not materialized, and in fact, you could say that Microsoft's new releases have not lived up to expectations yet, at least for book sales. I did say "yet" because there are signs that Vista is starting to pick up steam. But the fact is that without a significant bump from Vista and related Office products, the 2007 market has not performed at the 2006 level. I find it very interesting that the web and digital media had more of a market effect in 2006 than a huge, highly anticipated release of a new version of the world's most used consumer operating system and its office productivity suite has in 2007. It's one more sign of the waning of Microsoft's once fearsome market power.

  
  I particularly appreciated the major/mid-major/min-minor/minor/irrelevant breakdown of programming languages in part 4, as that kind of analysis is very helpful in collection development, especially for identifying the languages that are on the way down as well as the ones becoming more popular.
  
  
• From Journal on Educational Resources in Computing (JERIC) v7i2, A 2007 model curriculum for a liberal arts degree in computer science by Brad Richards looks very interesting. You can see an online version of it here (there are several versions of it; I'm not sure if they are all the final or various drafts). The document itself mentions the author as the Liberal Arts Computer Science Consortium.

Programming with Pictures

We all know that CS is a hard sell to students these days and that enrollments in most places for mainstream computer science programs are down. So, how to attract students to the field and keep them once they enroll? One strategy is to make the introductory programming experience a lot more pleasant, a lot less like banging your head against a very hard, very nitpicky brick wall. (For what it's worth, I'm one of those that took to programming like a duck to water. My first language was Fortran and I really didn't have too many problems learning to write programs.)

A great article in InsideHigherEd today, Programming with Pictures by Elizabeth Redden, talks about a new programming language/environment called Alice that lets students learn the basics of programming right away while working on cool-looking graphical programs.

About 10 percent of the nation’s colleges now use Alice, an open-source, graphical software program available free online that allows users to learn the very basics of programming — concepts like iteration, if statements and methods — while making 3-D animations. Alice’s growth within college computer science departments has been impressive: Most colleges only began incorporating Alice in their introductory CS0 or CS1 courses within the past 18 months, since the release of an accompanying textbook.

But the software, currently readable to users in plain old English (a major drawback for many faculty who of course teach programming in standard computer languages like Java and C++), is potentially poised to penetrate far more colleges in 2008, when Alice 3.0 comes out in Java — featuring, this time around, sophisticated graphics, made available free by Electronic Arts Inc., from “The Sims,” the best-selling PC video game of all time. (And significantly, Pausch adds, one of the few games more popular with girls than boys. Computer science, he notes drily, has the unfortunate distinction of being the only discipline in the sciences to actually face declining female enrollments percentage-wise in the last 25 years).

It's a well-done article, well worth reading the whole thing. Alice is not without its drawbacks -- it's not object oriented, for example -- and the article does a good job of giving the pros and cons.

Laurence Musgrove is cranky

And he does have a few good points, but not on everything.

InsideHigherEd a week or so ago published Musgrove's essay iCranky and it really hit a nerve for me. It touches on a lot of things that are changing about higher ed that are really important to keep track of, most especially how to deal with students that have a lot more options than they used to. And I mean options in terms of how to do research for assignments, how to waste time and tune out in class, how to procrastinate and plagiarize, how to get even with profs who annoy them. They also have options to collaborate and direct their own learning as never before. The trick is how to balance the good and evil of the multitude of possibilities that new technology offers us. Just because there are new possibilities doesn't mean that they're automatically either good or bad, what we should be aiming for is to find what works in different circumstances and for different student groups. We should be open to try new things but at the same time we should resist the temptation to brand something as a miraculous cure for all that ails us just because it's new. The other extreme is to put our heads in the sand and say that only old-school teaching methods are good and that nothing positive can come from new technolgies.

I'm going to exerpt the last few paragraphs of the essay and comment on them.

Another reason I’m cranky today is that I detest these facile characterizations of our students. At some point, I expect the next newest generation to be labeled “USBs” or “ScanDisks” or “Intels” or “iLearners.” These names and framing metaphors, of course, support all sorts of false notions of knowledge and learning and teaching and success and most frightening: humanity.

Kids today are just the same as always -- cool, lazy, hardworking, procrastinating, social, sullen, passive, overcontrolled, aggressive, bullying -- the whole gammut. Something I think we tend to forget is that not every kid is as plugged in or connected as the rest. There's a digital divide even within the net generation. Some aren't as interest or have the same aptitudes, some have had bad experiences with cyber bullying, or any other reason. I think we have to resist the temptation to assume all the kids in the current generation are the same.

And I’m cranky because this attempt to equate pedagogy with technology confuses ends with means. “Student engagement” has become the latest assessment buzzphrase, and thus, the newest once-and-for-all measure of and purpose for learning. In other words, any desire to understand the value of learning to individual students is replaced with the desire to promote the most efficient and engaging mode of learning by as many students as possible. And faculty better get in line to be online.

Hmmm. I'm torn on this one. On one hand, it is important to recognize that all students are different and have different learning styles and needs. On the other hand, there's really no reason why the technology can't serve those diverse needs just as well, if not better, than older methods. Especially if we find a way to let students mix old and new in a way that works best for them.

Techno-teaching and ilearning are also best because that’s what our students expect from us. They are the current experts on learning, they know how they best prefer to learn, and we should deliver unto them what they want in the way they want it. Thus I’m cranky because in between the government money pouring into institutional assessment and the tuition pouring in from 18 year old students, faculty members get shortchanged.

Letting students decide how we should teach them is like letting the inmates run the asylum. Very true. If most students could decide what and how they could learn, if would be "nothing" and on the beach to boot. On the other hand, we run asylums quite a bit differently now than we did in the 1800s. We don't even call them asylums any more. The university learning experience hasn't changed that much in the same time period. Maybe we should listen a bit more to what our students are telling us about ourselves and spend a bit less time proclaiming our authority. We should do what works, not because it's what students think we should do but because between us we should be able to find some solutions.

Finally, I’m cranky because I have to confront all of this professional development ruckus to claim my own professional authority, to say that I am smart enough to keep track of my own discipline and the latest pedagogical advancements without having to be lectured to two or three times a year about what college students need.

Most annoying part to me. Something as a librarian I sometimes encounter from students is the attitude, "Hey, I'm a millennial and you're an old fart librarian. There's nothing you can possibly teach me that's worth knowing." Or, "Hey, I'm a faculty member,and you're an old fart librarian. There's nothing you can possibly teach me or my students that's worth knowing." Ok, more than a little exageration for effect, but we've all seen that dismissive look on people's faces or the polite refusal of help. I think we all need to admit that we don't know everything, that other people can help us, that they have something to offer if only we'd just take a minute to listen. And I include myself in that category of needing to listen more.

What our students need is not more of what they come in the door with. They don’t need more of the same in the same way they got it before. They need to be confronted with people who talk about ideas that matter. They need to become people who can confront and talk to other people about ideas that matter. They need to sit in a room of people and learn about humanity.

This one I agree with totally. This is what education is about and we risk loosing this kind of interaction at the deadly peril of irrelevance. And students of all times and places have resisted getting their minds expanded. But shouldn't we expand the definition of door a bit? And doesn't he realize he accused himself of the same narrow-mindedness in the previous paragraph?

Also, not more Facebook, but more faces in books, extended periods of silent and sustained reading and writing, developing intellectual stamina and the ability to ask questions that don’t lead to easy answers or a quick and final Wikisearch.

Another good point. A lot of learning is more than just multitasking, more than just surface skimming, it's sustained, narrow focus on important texts and ideas until they begin to make sense. But again, I would submit that we should expand the definition of "book" until it might even include, well, FaceBook. You can learn through intense, narrow, focused conversation, interaction and collaboration too. I think students might be more receptive to reading books if they saw them as integrated with a much wider information landscape, the landscape they are more intimately familiar with.

The life of a CS grad student

Lance Fortnow at Computational Complexity brings together a bunch of posts where he's given some advice on thriving and surviving the grad student experience from choosing a school to apply to all the way to negotiating the first job offer. The emphasis is on CS, but most of what he says is relevant to other fields. As well, he gives lots of insights into what all those grad students skulking around campus are going through. Many of the posts also have lively conversations going on in the comments sections.

Here they are:

• Judging Applications
  
• Choosing a Graduate School
  
• Choosing an Advisor
  
• Finding Problems to Work On
  
• Attending Conferences
  
• Writing a Dissertation
  
• Looking for Academic Jobs
  
• The Academic Interview Trip
  
  
  • What to Wear
    
  • The Job Talk
    
  • Meeting with Faculty
  
  
• Negotiating Your Offer

Writing about science

Dave Munger of Cognitive Daily has a nice long post on how to write about scientific research for a general audience.

His points may seem obvious, but they certainly bear explicit mention. It can be a challenge to make science interesting to a mass audience in a culture that doesn't value science very highly compared to "entertainment" and I think he hits a lot of points on how to make science entertaining too.

1. Find interesting research -- this one's obvious, the subject needs to be compelling and relevant enough to catch people's attention.
   
2. Show why it's interesting first
   
3. Let the research speak for itself
   
4. Don't include details that are only relevant to scientists
   
5. Don't use scientific jargon
   
6. Tell a story
   
7. Visuals need the same treatment as words
   
8. Keep it concise
   
9. Cite your sources
   
10. Don't overstate your case
    
11. Have fun

Munger's core idea seems to be to find an interesting, relevant piece of research, show why it's interesting, put the cool details and cool pictures in the story (leaving out the boring stuff). But mostly, tell a good, human story and definately let your enthusiasm for the story shine through. The only thing Munger doesn't mention that I would highlight the suggestion that a good science story will also be a story about good scientists. Their struggles to figure out how nature works, the successes and failures, can also make extremely compelling reading. I always find if I can relate to the struggle of doing a good job, I can get a lot more out of the content of the story.

Good stuff -- go read it. There's certainly a lot of ideas that are relevant to bloggery.

Update 2007.02.08: A bunch more relevant posts from the ScienceBlogs universe, this time on learning to write like a scientist:

• Adventures in Ethics and Science, here and here.
  
• Uncertain Principles here.

Basic concepts in science

The crowd (and it is a crowd these days, up to 57 blogs) over at ScienceBlogs has decide to prepare a bunch of posts explaining various basic concepts in science, with the various bloggers each pitching in for their own subject areas. A couple of non-ScienceBlog types have also pitched in a few.

John Wilkins at Evolving Thoughts is collecting links to the various posts here.

The list is just getting some good critical mass; I hope it's something they continue, and continue to add new subject areas. In particular, I want to point out some great posts at Good Math, Bad Math on basic statistics concepts: Normal Distribution; Mean, Mode & Median; Standard Deviation; Margin of Error and Correlation (and Causation, and Random Variables).

Science videos on the web

Coincidentally (or not?), both inkycircus and LabLit have articles discussing and pointing to a bunch of different sources of science-related video content on the web.

Personally, I love this kind of stuff and could watch it all day if I let myself. A few of the suggestions from the two articles, featuring both new shows/videos and oldies-but-goodies:

• Lab Reporter: "films to take you into the heart of science"
  
• Secret Life of Machines
  
• 2006 Year in Videos from New Scientist
  
• ResearchTV
  

Of course, searches on YouTube and Google Video also turn up a lot of interesting content. Enjoy!