Spaf on “Soup to Nuts”

Gene Spafford, of security fame, kicked things off with a keynote covering interesting puzzles to get students thinking out of the box as well as ideas on how to inspire students by showing them what can be done with computer science.  Examples included training soldiers with Segway-based robots and discovering security holes that make power plants vulnerable to cyber attacks.  Overall, it was an interesting, engaging talk.  There was a lot I recognized from Ed Lazowska‘s talks and materials I already use which I found comforting in some way.

Code as a Metaphor for Computational Thinking

I then went to Owen Astrachan‘s Code as a Metaphor for Computational Thinking session.  As he opened, he said he’d let us decide whether the talk was actually about computational thinking because he wasn’t sure.  Interesting to hear him say that — I have a hard time with the “computational thinking” label because I haven’t seen a satisfying explanation of what it is.  The talk was centered on three examples that involved reasoning about existing computational artifacts, writing some related code and then analyzing that code.  At one point, he said something to the effect of “if you don’t write code in class, students won’t know how to do it.”  I appreciated that and do believe that there’s something very powerful about seeing a (relative) expert go through the process of writing a program, making mistakes, verifying it, using tools like IDEs appropriately, etc.  I’m very suspicious of instructors who talk about code without demonstrating how to write anything.

The first example he discussed involved online gambling.  He started by mentioning that it’s a good place to talk about the legal code as it relates to computing.  It’s also a good opportunity to show some interesting code for labeling hands — he showed us a flawed example of an “isPair” function that returned true even when the hand should really be considered a triple or better.  We talked through different ways of resolving this issue and lots of good design ideas came out.  My only concern would be that poker tends to be a high-income, white, nerdy male sport… using this example would require careful thought on how to present it without alienating anyone.  I don’t really know poker and my first reaction was “yawn” though I warmed up to it once we got to the code.  There really are interesting things that come up, here.  One audience member suggested that the problem could be fixed by always calling the hand-testing functions in order of highest-scoring to lowest-scoring.  True, but Michael Kölling of Greenfoot fame rightly pointed out that functions should work regardless of the context in which they’re called.  This is a good type of conversation to have with and between students.  Students can then implement all the hand-scoring functions and compare their runs to expected probabilities, using those to evaluate whether their implementations are correct.  That’s an idea I really like.

Owen’s second example involved Tin Eye, a search engine that lets you upload a picture and find instances of it regardless of size, compression, format, etc.  It’s interesting to speculate on how it works and to try to discover the limits of its tolerance.  For example, Owen suggests that we ask students to use steganography functions to hide an unrelated image into a target image then see whether Tin Eye still recognizes the target.  What if more of the target image were replaced?  What if part of the image were cropped?  One could do something similar with Shazam, a tool for recognizing songs.  I like the “let’s figure this out” feel of this example.

Finally, he discussed an example from the “code of life” — finding repeated DNA substrings.  This is an interesting algorithmic problem that can be discussed free from code and eventually be written as an exercise.  The discovery for me was that Duke has a small set of problems with test sequences available here.  I don’t know what computational thinking is, but what Owen discussed were definitely examples of it.

Pre-AP Recruiting

The next session I attended, “How does your geek garden grow?  Identifying and cultivating the geeks of tomorrow (AP CS Feeder Course)” left a sour taste in my mouth.  The speaker argued that we need to be better at communicating with math teachers and counselors to tell them that we are in fact looking for the bored, disinterested students at the social fringe who never do their homework.  The reason for this is that they may make great ‘geeks,’ which is the type of person the tech industry wants to hire.  Maybe my thinking is clouded by the luxury of having lots of motivated, social students who want to take my courses but I really do want to target the leaders, the social butterflies, the high-achievers as much as possible.  Of course, I want my courses to be inclusive of all, but I feel that targeting unmotivated students at the social fringes is a pretty desperate move and not one I think will do a lot for the image or success of K-12 Computer Science.  The speaker’s suggestion for getting those unmotivated students is to tell them that they’ll make  video games, that there will be no homework and that they’ll pass if they play along.

This makes me uncomfortable but the speaker did report that this tactic has resulted in students finding something that they’re good at and continuing on to be successful in her AP class.  That, I think, is a real victory and something to be celebrated so I’m a little torn.  It’s possible that faced with low enrollment and a lack of strong students I would do the same thing.

A common theme in the talk was “let students do what they want to do so you don’t lose them.”  The course she described seemed like everything but the kitchen sink and heavy on the tools — Visual Basic, Java, Scratch, Alice, Gamemaker… my head was spinning just thinking about it!  Where I tend to opt for structured play and predictability, she really opens things up for students to experiment.  It’s a matter of philosophy and I wish I could go see how things play out in her classroom.

One thing I really appreciated from this talk was getting some good reminders about where teenagers are in their development while they’re taking our courses.  They’re identity-building and striving to find areas they’re successful in so we can have a very powerful effect by providing them with experiences that reinforce their sense of self.

Emmanuel Schanzer’s talk on Functional Videogame Programming was the day’s discovery and I’m glad Michelle Hutton encouraged me to see it.  Emmanuel’s project, Bootstrap, is a full curriculum for using Scheme to bolster algebra learning.  I think I’m going to ruminate on this one and write about it later.

Digitizing The World

The last session I attended was by two teachers from CSTA’s board of directors — current president Michelle Hutton and past president Robb Cutler.  They presented extensions on a cool CS Unplugged activity on image representation.  Michelle’s middle school girls “digitized” color images using graph paper and a color key.  They discussed different algorithms for choosing the color to put in one square and changing the grid size allowed them to discuss tradeoffs between storage space and fidelity.  I like it.  Then, they extended the exercise further by using points to digitally represent 3D objects.  Robb wrote a tool to interpret simple formatted text files and display the objects or scenes so they can be interacted with.  Michelle had her students represent Lego shapes and their classroom.  In a blog post about the exercise, she recounted one student’s inability to believe in her own success — spacial orientation exercises are generally more difficult for we ladies.

I liked their idea of giving “programming-like experiences.”  I’ll have to see whether there’s a way I can adapt the activity or something like it for my high schoolers.  I was also very impressed that Robb was modifying the tool and the text file’s syntax as the girls requested features.  Their requests ranged from function-like syntax (reusable blocks) to naming the tool after them.  Participating in this “client” way must definitely have given the girls a sense of the power of programming and I’d like to see whether I can replicate that experience somehow.

Megan Smith of Google.org

Our closing keynote was by Megan Smith, in charge of Google.org.  She discussed .org initiatives including Flu Trends, RechargeIT, Clean Energy 2030, and PowerMeter and tied those nicely to generating excitement in our students about computer science.  She’s an excellent speaker and closed the day well.  Valerie Barr, an inspirational instructor who has revamped the CS1 courses at Union College, mentioned that Google is hurting computer science by calling its employees “engineers.”  The same point was made to Marissa Mayer when she gave the keynote talk at SIGCSE in 2008.  Megan had a good response but I now read that she’s not a computer scientist at all but a mechanical engineer!  The problem may be partly on the computer science side… we still haven’t defined our field very well.  Engineering brings to mind creativity, construction, collaboration and even I’m not sure what CS should make me think of.

Overall, a positive, inspirational day leaving me with lots of food for thought and wishing I could have spent more time with so many people I admire and enjoy speaking with.

Saturday 6/28 was the Computer Science and Information Technology Symposium — pretty much the one big professional development event for high school CS instructors.  I’m so glad I was able to go and hope to make it annually!  The sessions gave me some great ideas and I had the opportunity to make very useful connections.

The keynote was given by Stuck in the Shallow End authors Jane Margolis (who also authored the excellent Unlocking the Clubhouse: Women in Computing) and Joanna Goode.  I was not a huge fan of the book: the problem seemed too obvious to me and the offered solutions too weak.  That being said, the keynote was excellent and brought in some more data and a little information about the Exploring Computer Science course they have been working to develop in LA area schools.  Of course, everyone wanted to see the curriculum outline and materials but it looks like they’re not sharing the details yet.  Joanna made it sound like they were going to release things in the fall — too late for those of us starting a new course then but still, I’m excited to see what they’ve come up with.

Dave Burkhart’s session on differentiated instruction provided a number of good ideas.  He managed to balance educational theory and computer science well and although he’s a middle school teacher, his insights were quite relevant to high school.  I’d also never seen the hilarious clip he showed on herding cats.  Indeed, when we’re given classes with students of wildly different levels and interests, chaos ensues.  According to Dave, differentiated instruction is having a vision of success for each of your students.  I love that way to think about it.  He provided some good tools for making sure that all students had a path to success available to them.  I found it interesting that he uses a multiple intelligence test to better cater to his students’ learning styles.  Not a bad idea.

The “Computational Thinking – A Problem Solving Tool for Every Classroom” session wasn’t quite as relevant to me.  I liked breaking down thinking computationally when approaching a problem as asking a series of questions including:

• “how difficult is this problem?”
• “how can it be solved?”
• “how can technology be applied to the problem?”

Computational thinking was also not-defined as “not thinking like a computer, it’s not programming, it’s not computer science, it doesn’t require a computer.”  Less sure about these.  Computational thinking may be broader than these, but they’re all great examples of applications, I feel.  This session was very similar to the previous day’s TeraGrid workshop where a lot of emphasis was placed on using simulations.  Interesting.

I really enjoyed the “Building Effective Leadership at the Grass Roots” panel.  Lots of very interesting people doing interesting things across the country.  I asked about making the CSTA curriculum resources into an easier to use tool and more of an online community.  Sounds like that is in the works.

I met a bunch of really inspiring people I hope to stay in contact with.  Highly recommended for anyone involved in K-12 computer science.

The day started with a quick mention of some videos modeling scientific phenomena from CMIST. We then got a long presentation from Shodor founder Bob Panoff on using their computational modeling tools for teaching math and science topics. Shodor (allegedly named for “Short Dork”) is a really neat non-profit based in North Carolina that provides all kinds of great free tools as well as workshops and internships in technology for high school students. For example, teachers could use their function grapher to get students to explore the effect of constants on trigonometric functions by having them graph 1 * cos(x + 0) + 0 and use the sliders to change the values of the constants. The rabbits and wolves simulation is a great tool for showing population dynamics complete with updating graphs of each species count and parameters to modify the type of world.

These kinds of materials are great “hooks” for math and science teachers to use in support of discovery learning (more on that in a future post). They can also be used to get students to think about building and using abstract models to represent real-world situations, a key part of computer science. A teacher could, Bob suggested, use the histogram activity to make a point about the importance of knowing how to interpret models and the assumptions they make. For example, looking at NBA salary data, a coach might slice the data into three ranges and use the resulting graph to claim that nearly all players are paid the same. By slicing the data into smaller ranges, though, players might claim that salaries are not equitable. The Shodor system makes that kind of “zooming” in and out on data really simple.

Given that we were nearly all computer science teachers, I felt this was the wrong crowd. These are cool, but aren’t there 101 different (and most likely inferior, I’ll admit) simulations like that online? Besides, this seems like a use of technology as a tool rather than an example of building computational thinking abilities. But Bob started his presentation with an interesting statement — he rather casually said something like “in CS, we’re starting with modeling rather than programming because there’s very strong evidence that starting with programming creates barriers that wouldn’t otherwise exist.” No one really blinked and the tone of the day was set. I’m uncomfortable with that position but have to think about it more before I can craft a coherent response. I do believe that using tools like Vensim to describe models in a lightweight way is a good first step but I’m not sure that manipulating a ready-made simulation such as those Shodor provides really is actively building computational thinking abilities. In the best-case scenario, strong students will build some sense of what makes a good model or abstraction by playing with many existing ones. Not all students are strong students. I think that using scientific computation as a hook for algorithm design and computer science is unrealistic for most kids in our urban schools.

Another theme of the day was discovery and exploration as the best teaching/learning strategy — “let’s get out of the way of students’ learning.” Certainly, for self-learners with strong family support and excellent role-models, this is an excellent strategy but I don’t think it works for the majority. We saw an interesting presentation on a great collaboration between a community college, a liberal-arts college and a couple of universities. Charlie Peck and his collaborators had brought their LittleFe cluster — a home-grown machine made of off-the-self parts for under $3000. They run a Linux distribution called Bootable Cluster CD on it and use it to teach parallel computing. This is where they lost me a little bit: from the presentation, they made it sound like their strategy was letting students loose on the machines and having them build cool stuff. Note that this could be a misrepresentation as I haven’t done much exploration to see whether they have more structured content available. Still, I think that for most people, this seems like a wonderful idea! Indeed, when I mentioned the need for structured instructional materials it kind of fell on deaf ears.

All this sounds pretty negative, but I really enjoyed the day. It was a good opportunity to meet some interesting people and to continue to figure out my own ideas on education and where computer science fits in. I’m definitely a minority in a lot of my stances (structured instruction over discovery-based learning, structured assignments rather than open-ended projects, deliberately ordered and linear curriculum pacing, early emphasis on basics, etc) so I have to be particularly careful in what I do to either be open to change when things don’t work or to have data to point to when challenged.

SIGCSE caught me in an interesting place somewhere between extreme career-angst and profound passion for ongoing CS projects. Unsurprisingly, a number of the sessions I chose to attend had to do with computer science’s negative image and ways to overcome them. One of my favorites was titled Rediscovering the Passion, Beauty, Joy and Awe: Making Computing Fun Again. Everyone has a different theory on why computer science is losing its appeal: programming is considered boring, programming is fun but students find the rest boring, it’s too hard, the field is too competitive, there’s a perception of a lack of jobs, it’s considered antisocial…

One of the talk’s speakers, executive director of the CSTA, noted that the enrollment crisis that’s been plaguing us for a few years may in fact prove to be positive because it is forcing us to come together and reengineer the field’s identity. Really, there’s an element of truth in all of the perceptions listed above.

I tend to feel that I was born in entirely the wrong decade to be a computer scientist, and I doubt I’m the only one. I wanted to be around forty years ago when Engelbart was founding the Augmentation Research Center at Stanford or thirty years ago when Metcalfe was creating Ethernet at PARC or twenty years ago when the original Macintosh was emerging. It’s books like What the Doormouse Said and long nights of hacking device drivers in Linux that got me hooked. And these days, all anyone seems to want is Facebook. Which is not to say that there are no active subfields — surely cloud computing, multi-core devices and computerized medical systems are not devoid of interest but I grew up about two and a half miles from the HP garage and it heavily influenced my concept of the future as a computer scientist. Where are the small grassroots innovations?

The whole conference placed a lot of emphasis on introducing algorithmic thinking and computer science-y things in K-12, which really resonates with me (I am, after all, coordinating the UW CS4HS workshop this summer). My early experiences with computers from programming with Logo in 6th grade, taking apart computers with my dad even before then and doing FIRST in high school all left me with very strong impressions. Regardless of the fields students will ultimately go to, any CS skills they pick up will serve them well, so it definitely makes sense to incorporate at all levels. Additionally, as Eric Roberts pointed out in his portion of the talk, the field loses most students before they even get to college, implying that the quality of courses offered at that level may not explain dwindling enrollment at all. In his words, “curriculum is our hammer and the enrollment crisis is our nail.” He was even able to show Stanford course evaluation data demonstrating that the intro CS series are among the more popular classes on campus, but that students’ enjoyment of the course has nothing to do with whether they’ll stick with the field — students choose majors based on what they want to do, not on what they want to study.

In some ways, I feel a little bit cheated because my FIRST experience, for example, was much closer to the HP garage than anything I’ve done since. All of this talk of introducing CS with gimmicks including Alice, robots and video games is all nice and good, but is it really representative of what students will end up doing? Probably not, and if they are hooked by those things, I don’t think it means that they will stay interested. If, with all my love of technology and my successes in the area, I still end up having an existential crisis related to my options to the future, of course others are suffering from the same. I think I’m an example of someone who chose the major because it’s exactly what I wanted to study but who isn’t sure what to do with it after that. Sure, I could keep studying it, and that’d probably be fun, but studying something just for the sake of fun is only fulfilling for so long for me.

Industry has become ridiculously unattractive to a whole slew of us. Sure, Google attracts many people with its promise of on-campus pool and dry cleaning service but to some of us those “perks” are repulsive. Of course it’s convenient, but it’s too invasive for me. A lot of jobs involve little creativity. The social impact is minimal. It just doesn’t fit into my value system. And it was really great to hear speakers denouncing this reality and suggesting that it’s industry’s responsibility to make work more appealing.

Beyond that talk, the conference was fantastic. It was so much fun to meet all the big names I’ve heard so often — Berkeley’s Dan Garcia and Mike Clancy Stanford’s Julie Zelenski and Nick Parlante, Duke’s Owen Astrachan and so many others…

Man, I just want to teach.