• Stuart Reges from UW who talked about many interesting ideas related to computer science including meta, recursion and more!
• Mike Dussault from Valve who talked about creating video games
• Jim George who talked about using software as art
• Kwaku Sefa-Dedeh who talked about the business side of Microsoft
• Robert Morton who talked about his work at Tableau software and becoming a computer scientist

When I was in high school, I always appreciated the opportunity to talk to adults doing things I found interesting.  Strong engineering and computing mentors played a big role in steering me in the direction I followed so I hope to bring a bit of the same to my students.

Today, my classes were very lucky to get a visit from Ben Slivka, starter of Internet Explorer among other cool things.  I took some notes as students asked questions and have done my best to recreate some of what was discussed.  It was really fun to get his insights on all kinds of things technology.

Which of the companies you worked in was the most fun?
Mr. Slivka told us that he had the most fun at Microsoft.  Starting Internet Explorer was a creative and innovative endeavor involving great people.  It was a lot of work, too — he told us that 80-100 hour weeks were not uncommon for him!  Mr. Slivka first saw a web browser in 1994 (Mosaic) and knew that it was an exciting development.  In fact, in 1995, he wrote an internal memo on how important the web would become titled “The Web is the Next Platform.”  At the time, there were only a few thousand websites as opposed to today’s tens of millions.

Mr. Slivka worked with Internet Explorer through its third release and grew the team from 7 to 69 engineers.  He shared with us that during his time at Microsoft, a person in the USA was more likely to become a Microsoft millionaire than an NBA player!

Why did you leave Microsoft?
Young Microsoft took lots of risks to become successful but as it has grown, it has become more concerned with protecting its primary products (Windows and Office) rather than innovating.  Around 1999, Mr. Slivka wanted to pursue Internet-related innovations but that was not the direction the company was taking.  The book Breaking Windows covers the time when he was leaving Microsoft and the prologue is online.

Is it scary to talk to company founders like Bill Gates (Microsoft) or Jeff Bezos (Amazon)?
No!  According to Mr. Slivka, companies are a lot less hierarchical now than they were maybe 50 years ago so it’s natural for CEOs to have relatively frequent contact with their employees.  When he was at Microsoft, it was not unusual for him to trade e-mails and have face-to-face meetings with Bill Gates.

What is one of the most exciting ideas in computer science?
Mr. Slivka told us about computational complexity, the study of the difficulty of programming tasks.

Was it difficult to see OS/2 fail after 5 and a half years of work?
Only doing things that will succeed is boring, says Mr. Slivka!  There is a lot more to learn from mistakes than from successes.  It was difficult to see such a big time and energy investment be lost but going through the process of creating the product was valuable.  OS/2 was a joint venture between Microsoft and IBM and their goals were different.

What was the hardest project you were involved in?
The human factor in projects is often the most difficult.  In 1998, Mr. Slivka was asked to take part in designing a new interface for Windows.  He and two others were in charge of the project and there was conflict among the leadership which made it difficult.

What do you think of the iPad?
It’s somewhere between a phone and a laptop and it’s hard to know where it fits in.  It still requires a PC since when turned on it wants to be synced to iTunes.  The device is too heavy but it does have a gorgeous screen.  The brushed aluminum is beautiful but very slippery.  Mr. Slivka sees it mostly as an expensive toy.  He reminded us that computing technology is like grocery store produce in that it has a limited shelf life.  This first version of the iPad is not likely to be popular for long.  The lack of multitasking and virtual memory are real limitations.

Can you comment on the Apple vs. Adobe war?
Apple is playing defense right now by trying to protect their control over all aspects of their products.  The Flash battle is not about security or stability, it’s about market control and — ultimately — dollars.

Which web browser do you use?
IE7 was too slow and Mr. Slivka switched to Firefox.  He does not use Bing.

What do you think about cloud computing?
Offline computing still has a role since there is no pervasive connectivity yet.  If cloud computing means data is never lost, actions can be infinitely undone, groups can collaborate well, no need to worry about installations of software then it’s a great idea but in practice, there is no great implementation yet.  Google Docs doesn’t work well but it’s definitely possible to create a fully-functioning word editor in the cloud some day.

What are the main privacy issues on the Internet?
Mr. Slivka shared his policy: he doesn’t put anything up online that he wouldn’t be ok with being on the New York Times front page.  People should be thoughtful about what they share and market forces will work to punish companies that don’t respect privacy well enough.  In his opinion, the government is getting involved because it’s currently on people’s mind and will help politicians win elections.

What will Google look like in the next few years?
Google is now suffering from the same problem as Microsoft: Microsoft has revenue from Windows and Office and wants to protect those while Google has Search and AdWords and wants to protect those revenue streams.  Google’s challenge will be innovating beyond search and ads while making sure they can maintain their dominance as products like Bing get significant investment.  Their current strategy is to be everywhere (Android, Chrome, etc) and make Google the preferred platform so they can protect their search and ad dominance.

In Creative Computing, we recently spent time working with indefinite loops.  I think most introductory programming instructors would be shocked and appalled at how long we’ve spent primarily focusing on one
measly construct.  Indeed, while loops are a half-hour lecture in most college-level intro to programming courses.  But here’s the deal – while loops are hard.  What does it take to use a while loop properly? I’ve tried to think of all the little things necessary to know how to interpret and create code using indefinite loops but I’m sure I’ve forgotten bits and pieces! I poked around a little for formal articles with these sorts of breakdowns for various programming constructs but wasn’t very successful. Pointers?

Understanding while loops requires…

• syntactic knowledge
  • start the statement with while, have some condition in parentheses, end the line with a colon then indent things that need to be repeated
  • valid boolean operators (assignment = vs. equality ==)
  • creating complex boolean expressions with and and or (for example, my students often write things like value == 2 or 3 which won’t work as expected in Python)
  • how to group statements into a block
• understanding of scope rules
  • if I use a variable in my test, it has to have been initialized
  • if I create a variable in my loop, it won’t be available later
• understanding of flow of control
  • if I make a method call in my loop body, that method is run then Python keeps executing statements after the call
  • if my condition stops being true somewhere in the loop body, that doesn’t make me magically jump out
  • the test is executed every time around the loop
• converting between stopping conditions and continuing conditions
  • DeMorgan’s Law is hard

I have a lot of sympathy for students who take more time to synthesize all of this and I think it’s too bad that we don’t have more best practices on breaking concepts down into digestible pieces.  At the same time, I think CS courses are exciting for high-achieving students BECAUSE we haven’t figured out how to break things down into bite-sized chunks, yet!  Certainly, when I was starting my perpetual quest to learn to program, I found something deeply satisfying about looking at several examples of a construct to establish a model of how it works.  For students who are not used to considering an idea from different angles in an attempt to really understand it, it’s a deeply frustrating process.

I feel like this points to a deep need for differentiated instruction to  keep my top end students engaged without overwhelming my bottom end.  I’ve been trying to be more careful about giving students sample code that address sub-concepts one at a time and having different milestones so students at various levels can be successful.  Again, not really finding best practices but that’s probably because computing education is primarily done at the college level where it’s not much of a concern for instructors (or I don’t know where to look?).  Raymond Lister and John Leaney’s First Year Programming: Let All the Flowers Bloom does present some nice work supporting the idea of shifting my goals for weaker students to reading and interpreting code rather than producing entirely novel programs.

Of course, I don’t pretend to know what the right solution is.  One thing I think is underscored by the overwhelming list of concepts needed to understand the humble while loop is the importance of being very deliberate about the order topics are introduced in.  Sometimes I look at introductory programming course syllabi and I feel like concepts are just being thrown haphazardly into a pile instead of aiming to construct knowledge.  Strong students will probably be fine but what about normal people?!

In my exams, I try hard to uncover what students’ current mental models are and have an opportunity to review them as necessary.  Although I know it’s unpopular among many, I have them write code on paper as well as solve mechanical code reading problems (Stuart is my hero and I steal all my ideas from him).  Reading their solutions is so eye-opening for me, especially since I can correlate with what I’ve seen them do at the computer.

I recently had my Creative Computing students take a Python quiz.  I asked them a fairly simple conditional problem to get them to define a function that takes parameters and check their conditional syntax.  Something interesting came out.  Here’s the problem:

Write a function choose_todo that takes two parameters: a temperature and a mood.  It should print what to do according to the following rules:

Ok, not particularly demanding or intellectually stimulating but the average and good students did this:

def choose_todo(temp, mood):
    if(temperature >= 60 and mood == "happy"):
        print "Go hiking"
    if(temperature >= 60 and mood == "sad"):
        print "Go fishing"
    if(temperature < 60 and mood == "happy"):
        print "Go hiking"
    if(temperature < 60 and mood == "sad"):
        print "Stay home"

And from EVERY exceptional student, we have:

def choose_todo(temp, mood):
    if(mood == "happy"):
        print "Go hiking"
    else:
        if(temp >= 60):
            print "Go fishing"
        else:
            print "Stay home"

I had the two happy cases be the same to see if they would recognize it, but I didn’t expect it to be such a black and white thing.  I pretty much could give this one problem and assign grades for the year.

The strong students somehow turned the problem around in their brain a bit more before starting to write than the others did.  Of course, the first solution isn’t wrong, it’s just… less satisfying?

This is not by any stretch of the imagination a skill that I explicitly taught.  I showed examples of concise code and discussed the advantages of making mutually exclusive options obviously so by favoring elif/else constructs over sequential ifs… but it was parenthetical at best.  Why do some people just ‘get it?’

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.