August 14, 2017 1:42 PM

Papert 1: Mathophobia, Affect, Physicality, and Love

I have finally started reading Mindstorms. I hope to write short reflections as I complete every few pages or anytime I come across something I feel compelled to write about in the moment. This is the first entry in the imagined series.

In the introduction, Papert says:

We shall see again and again that the consequences of mathophobia go far beyond obstructing the learning of mathematics and science. The interact with other endemic "cultural toxins", for example, with popular theories of aptitudes, to contaminate peoples' images of themselves as learners. Difficulty with school math is often the first step of an invasive intellectual process that leads us all to define ourselves as bundles of aptitudes and ineptitudes, as being "mathematical" or "not mathematical", "artistic" or "not artistic", "musical" or "not musical", "profound" or "superficial", "intelligent" or "dumb". Thus deficiency becomes identity, and learning is transformed from the early child's free exploration of the world to a chore beset by insecurities and self-imposed restrictions.

This invasive intellectual process has often deeply affected potential computer science students long before they reach the university. I would love to see Papert's dream made real early enough that young people can imagine being a computer scientist earlier. It's hard to throw of the shackles after they take hold.


The thing that sticks out as I read the first few pages of Mindstorms is its focus on the power of affect in learning. I don't recall conscious attention to my affect having much of a role in my education; it seems I was in a continual state of "cool, I get to learn something". I didn't realize at the time just what good fortune it was to have that as a default orientation.

I'm also struck by Papert's focus on the role of physicality in learning, how we often learn best when the knowledge has a concrete manifestation in our world. I'll have to think about this more... Looking back now, abstraction always seemed natural to me.

Papert's talk of love -- falling in love with the thing we learn about, but also with the thing we use to learn it -- doesn't surprise me. I know these feelings well, even from the earliest experiences I had in kindergarten.

An outside connection that I will revisit: Frank Oppenheimer's exploratorium, an aspiration I learned about from Alan Kay. What would a computational exploratorium look like?

Posted by Eugene Wallingford | Permalink | Categories: Computing, Teaching and Learning

August 11, 2017 9:08 AM

Don't Say "Straightforward" So Often, Obviously

This bullet point from @jessitron's Hyperproductive Development really connected with me:

As the host symbiont who lives and breathes the system: strike the words "just", "easy", "obvious", "simple", and "straightforward" from your vocabulary. These words are contextual, and no other human shares your context.

My first experience coming to grips with my use of these words was not in software development, but in the classroom. "Obvious" has never been a big part of my vocabulary, but I started to notice a few years ago how often I said "just", "easy", and "simple" in class and wrote them in my lecture notes. Since then, I have worked hard to cut back sharply on my uses of these minimizers in both spoken and written interactions with my students. I am not always successful, of course, but I am more aware now and frequently catch myself before speaking, or in the act of writing.

I find that I still use "straightforward" quite often these days. Often, I use it to express contrast explicitly, something to the effect, "This won't necessarily be easy, but at least it's straightforward." By this I mean that some problem or task may require hard work, but at least the steps they need to perform should be clear. I wonder now, though, whether students always take it this way, even when expressed explicitly. Maybe they hear me minimizing the task head, not putting the challenge they face into context.

Used habitually, even with good intentions, a word like "straightforward" can become a crutch, a substitute minimizer. It lets me to be lazy when I try to summarize a process or to encourage students when things get difficult. I'm going to try this fall to be more sensitive to my use of "straightforward" and see if I can't find a better way in most situations.

As for the blog post that prompted this reflection, Hyperproductive Development summarizes as effectively as anything I've read the truth behind the idea that some programmers are so much more effective than others: "it isn't the developers, so much as the situation". It's a good piece, well worth a quick read.

Posted by Eugene Wallingford | Permalink | Categories: Software Development, Teaching and Learning

July 28, 2017 2:02 PM

The Need for Apprenticeship in Software Engineering Education

In his conversation with Tyler Cowen, Ben Sasse talks a bit about how students learn in our schools of public policy, business, and law:

We haven't figured out in most professional schools how to create apprenticeship models where you cycle through different aspects of what doing this kind of work will actually look like. There are ways that there are tighter feedback loops at a med school than there are going to be at a policy school. There are things that I don't think we've thought nearly enough about ways that professional school models should diverge from traditional, theoretical, academic disciplines or humanities, for example.

We see a similar continuum in what works best, and what is needed, for learning computer science and learning software engineering. Computer science education can benefit from the tighter feedback loops and such that apprenticeship provides, but it also has a substantial theoretical component that is suitable for classroom instruction. Learning to be a software engineer requires a shift to the other end of the continuum: we can learn important things, in the classroom, but much of the important the learning happens in the trenches, making things and getting feedback.

A few universities have made big moves in how they structure software engineering instruction, but most have taken only halting steps. They are often held back by a institutional loyalty to the traditional academic model, or out of sheer curricular habit.

The one place you see apprenticeship models in CS is, of course, graduate school. Students who enter research work in the lab under the mentorship of faculty advisors and more senior grad students. It took me a year or so in graduate school to figure out that I needed to begin to place more focus on my research ideas than on my classes. (I hadn't committed to a lab or an advisor yet.)

In lieu of a changed academic model, internships of the sort I mentioned recently can be really helpful for undergrad CS students looking to go into software development. Internships create a weird tension for faculty... Most students come back from the workplace with a new appreciation for the academic knowledge they learn in the classroom, which is good, but they also back to wonder why more of their schoolwork can't have the character of learning in the trenches. They know to want more!

Project-based courses are a way for us to bring the value of apprenticeship to the undergraduate classroom. I am looking forward to building compilers with ten hardy students this fall.

Posted by Eugene Wallingford | Permalink | Categories: Computing, Software Development, Teaching and Learning

July 27, 2017 1:36 PM

How can we help students overcome "naturalness bias"?

In Leadership as a Performing Art, Ed Batista discusses, among other things, a "naturalness bias" that humans have when evaluating one another. Naturalness is "a preference for abilities and talents that we perceive as innate over those that appear to derive from effort and experience". Even when people express a preference for hard work and experience, they tend to judge more positively people who seem to be operating on natural skill and talent. As Batista notes, this bias affects not only how we evaluate others but also how we evaluate ourselves.

As I read this article, I could not help but think about how students who are new to programming and to computer science often react to their own struggles in an introductory CS course. These thoughts reached a crescendo when I came to these words:

One commonly-held perspective is that our authentic self is something that exists fully formed within us, and we discover its nature through experiences that feel more (or less) natural to us. We equate authenticity with comfort, and so if something makes us feel uncomfortable or self-conscious, then it is de facto inauthentic, which means we need not persist at it (or are relieved of our responsibility to try). But an alternative view is that our authentic self is something that we create over time, and we play an active role in its development through experiences that may feel uncomfortable or unnatural, particularly at first. As INSEAD professor of organizational behavior Herminia Ibarra wrote in The Authenticity Paradox in 2015,

Because going against our natural inclinations can make us feel like impostors, we tend to latch on to authenticity as an excuse for sticking with what's comfortable... By viewing ourselves as works-in-progress and evolving our professional identities through trial and error, we can develop a personal style that feels right to us and suits our organizations' changing needs. That takes courage, because learning, by definition, starts with unnatural and often superficial behaviors that can make us feel calculating instead of genuine and spontaneous. But the only way to avoid being pigeonholed and ultimately become better leaders is to do the things that a rigidly authentic sense of self would keep us from doing.

So many CS students and even computing professionals report suffering from impostor syndrome, sometimes precisely because they compare their internal struggles to learn with what appears to be the natural ability of their colleagues. But, as Ibarra says, learning, by definition, starts with the unnatural. To be uncomfortable is, in one sense, to be in a position to learn.

How might we teachers of computer science help our students overcome the naturalness bias they unwittingly apply when evaluating their own work and progress? We need strategies to help students see that CS is something we do, not something we are. You can feel uncomfortable and still be authentic.

This distinction is at the foundation of Batista's advice to leaders and, I think, at the foundation of good advice to students. When students can distinguish between their behavior and their identity, they are able to manage more effectively the expectations they have of their own work.

I hope to put what I learned in this article to good use both for my students and myself. It might help me be more honest -- and generous -- to myself when evaluating my performance as a teacher and an administrator, and more deliberate in how I try to get better.

Posted by Eugene Wallingford | Permalink | Categories: General, Managing and Leading, Teaching and Learning

July 21, 2017 3:47 PM

Some Thoughts from a Corporate Visit: Agility and Curriculum

Last Thursday, I spent a day visiting a major IT employer in our state. Their summer interns, at least three of whom are students in my department, were presenting projects they had developed during a three-day codejam. The company invited educators from local universities to come in for the presentations, preceded by a tour of the corporate campus, a meeting with devs who had gone through the internship program in recent years, and a conversation about how the schools and company might collaborate more effectively. Here are a few of my impressions from the visit.

I saw and heard the word "agile" everywhere. The biggest effects of the agility company-wide seemed to be in setting priorities and in providing transparency. The vocabulary consisted mostly of terms from Scrum and kanban. I started to wonder how much the programming practices of XP or other agile methodologies had affected software development practices there. Eventually I heard about the importance of pair programming and unit testing and was happy to know that the developers hadn't been forgotten in the move to agile methods.

Several ideas came to mind during the visit of things we might incorporate into our programs or emphasize more. We do a pretty good job right now, I think. We currently introduce students to agile development extensively in our software engineering course, and we have a dedicated course on software verification and validation. I have even taught a dedicated course on agile software development several times before, most recently in 2014 and 2010. Things we might do better include:

  • having students work on virtual teams. Our students rarely, if ever, work on virtual teams in class, yet this is standard operating procedure even within individual companies these days.

  • having students connect their applications programs to front and back ends. Our students often solve interesting problems with programs, but they don't always have to connect their solution to front ends that engage real users or to back ends that ultimately provide source data. There is a lot to learn in having to address these details.

  • encouraging students to be more comfortable with failure on projects. Schools tends to produce graduates who are risk-averse, because failure on a project in the context of a semester-long course might mean failure in the course. But the simple fact is that some projects fail. Graduates need to be able to learn from failure and create successes out of it. They also need to be willing to take risks; projects with risk are also where big wins come from, not to mention new knowledge.

Over the course of the day, I heard about many of the attributes this company likes to see in candidates for internships and full-time positions, among them:

  • comfort speaking in public
  • ability to handle, accept, and learn from failure
  • curiosity
  • initiative
  • a willingness to work in a wide variety of roles: development, testing, management, etc.
Curiosity was easily the most-mentioned desirable attribute. On the matter of working in a wide variety of roles, even the people with "developer" in their job title reported spending only 30% of their time writing code. One sharp programmer said, "If you're spending 50% of your time writing code, you're doing something wrong."

The codejam presentations themselves were quite impressive. Teams of three to six college students can do some amazing things in three days when they are engaged and when they have the right tools available to them. One theme of the codejam was "platform as a service", and students used a slew of platforms, tools, and libraries to build their apps. Ones that stood out because they were new to me included IBM BlueMix (a l´ AWS and Azure), Twilio ("a cloud platform for building SMS, voice and messaging apps"), and Flask ("a micro web framework written in Python"). I also saw a lot of node.js and lots and lots of NoSQL. There was perhaps a bias toward NoSQL in the tools that the interns wanted to learn, but I wonder if students are losing appreciation for relational DBs and their value.

Each team gave itself a name. This was probably my favorite:

   int erns;
I am a programmer.

All in tools, the interns used too many different tools for me to take note of. That was an important reminder from the day for me. There are so many technologies to learn and know how to use effectively. Our courses can't possibly include them all. We need to help students learn how to approach a new library or framework and become effective users as quickly as possible. And we need to have them using source control all the time, as ingrained habit.

One last note, if only because it made me smile. Our conversation with some of the company's developers was really interesting. At the end of the session, one of the devs handed out his business card, in case we ever wanted to ask him questions after leaving. I looked down at the card and saw...

Alan Kay's business card, redacted

... Alan Kay. Who knew that Alan was moonlighting as an application developer for a major financial services company in the Midwest? I'm not sure whether sharing a name with a titan of computer science is a blessing or a curse, but for the first time in a long while I enjoyed tucking a business card into my pocket.

Posted by Eugene Wallingford | Permalink | Categories: Software Development, Teaching and Learning

July 17, 2017 2:35 PM

Getting Started With Unit Testing

Someone wrote on the Software Carpentry mailing list:

I'm using Python's unittest framework and everything is already set up. The specific problem I need help with is what tests to write...

That is, indeed, a problem. I have the tool. What now?

Rather than snark off-line, like me, Titus Brown wrote a helpful answer with generic advice for how to get started writing tests for code that is already written, aimed at scientists relatively new to software development. It boils down to four suggestions:

  • Write "smoke" tests that determine whether the program works as intended.
  • Write a series of basic tests for edge cases.
  • As you add new code to the program, write tests for it at the same time.
  • "Whenever you discover a bug, write a test against that bug before fixing it."

Brown says that the smoke tests "should be as dumb and robust as possible". They deliver a lot of value for the little effort. I would add that they also get you in the rhythm of writing tests without a huge amount of thought necessary. That rhythm is most helpful as you start to tackle the tougher cases.

Brown calls his last bullet "stupidity driven testing", which is a self-deprecating way to describe a locality phenomenon that many of us have observed in our programs: code in which we've found errors is often likely to contain other errors. Adding tests to this part of the program helps the test suite to evolve to protect a potentially weak part of the codebase.

He also recommends a simple practice for the third bullet that I have found helpful for both bullets three and four: When you write these tests, try to cover some of the existing, working functionality, too. Whenever I add a new test to the growing test base, I try to add one or two more tests not called for by the new code or the bug I'm fixing. I realize that this may distract a bit from the task at hand, but it's a low-cost way to grow the test suite without setting aside dedicated time. I try to keep these add-on tests reasonably close to the part of the program I'm adding or fixing. This allows me to benefit from the thinking I'm already doing about that part of the program.

At some point, it's good to take a look at code coverage to see if there are parts of the code that con't yet have tests written for them. Those parts of the program can be the focus of dedicated test-writing sessions as time permits.

Brown also gives a piece of advice that seasoned developers should already know: make the tests part of continuous integration. They should run every time we update the application. This keeps us honest and our code clean.

All in all, this is pretty good advice. That's not surprising. I usually learn something from Brown's writing.

Posted by Eugene Wallingford | Permalink | Categories: Software Development

July 11, 2017 3:17 PM

Blogging as "Loud Thinking"

This morning, I tweeted a quote from Sherry Turkle's Remembering Seymour Papert that struck a chord with a few people: "Seymour Papert saw that the computer would make it easier for thinking itself to become an object of thought." Here is another passage that struck a chord with me:

At the time of the juggling lesson, Seymour was deep in his experiments into what he called 'loud thinking'. It was what he was asking my grandfather to do. What are you trying? What are you feeling? What does it remind you of? If you want to think about thinking and the real process of learning, try to catch yourself in the act of learning. Say what comes to mind. And don't censor yourself. If this sounds like free association in psychoanalysis, it is. (When I met Seymour, he was in analysis with Greta Bibring.) And if it sounds like it could you get you into personal, uncharted, maybe scary terrain, it could. But anxiety and ambivalence are part of learning as well. If not voiced, they block learning.

It occurred to me that I blog as a form of "loud thinking". I don't write many formal essays or finished pieces for my blog these days. Mostly I share thoughts as they happen and think out loud about them in writing. Usually, it's just me trying to make sense of ideas that cross my path and see where they fit in with the other things I'm learning. I find that helpful, and readers sometimes help me by sharing their own thoughts and ideas.

When I first read the phrase "loud thinking", it felt awkward, but it's already growing on me. Maybe I'll try to get my compiler students to do some loud thinking this fall.

By the way, Turkle's entire piece is touching and insightful. I really liked the way she evoked Papert's belief that we "love the objects we think with" and "think with the objects we love". (And not just because I'm an old Smalltalk programmer!) I'll let you read the rest of the piece yourself to appreciate both the notion and Turkle's storytelling.

Now, for a closing confession: I have never read Mindstorms. I've read so much about Papert and his ideas over the years, but the book has never made it to the top of my stack. I pledge to correct this egregious personal shortcoming and read it as soon as I finish the novel on my nightstand. Maybe I'll think out loud about it here soon.

Posted by Eugene Wallingford | Permalink | Categories: Computing, Teaching and Learning

July 09, 2017 9:04 AM

What It's Like To Be A Scholar

I just finished reading Tyler Cowen's recent interview with historian Jill Lepore. When Cowen asks Lepore about E.B. White's classic Stuart Little, Lepore launches into a story that illustrates quite nicely what it's like to be a scholar.

First, she notes that she was writing a review of a history of children's literature and kept coming across throwaway lines of the sort "Stuart Little, published in 1945, was of course banned." This triggered the scholar's impulse:

And there's no footnote, no explanation, no nothing.
At the time, one of my kids was six, and he was reading Stuart Little, we were reading at night together, and I was like, "Wait, the story about the mouse who drives the little car and rides a sailboat across the pond in Central Park, that was a banned book? What do I not know about 1945 or this book? What am I missing?"

These last two sentences embody the scholar's orientation. "What don't I know about these two things I think I know well?"

And I was shocked. I really was shocked. And I was staggered that these histories of children's literature couldn't even identify the story. I got really interested in that question, and I did what I do when I get a little too curious about something, is I become obsessive about finding out everything that could possibly be found out.

Next comes obsession. Lepore then tells a short version of the story that became her investigative article for The New Yorker, which she wrote because sometimes I "just fall into a hole in the ground, and I can't get out until I have gotten to the very, very bottom of it."

Finally, three transcript pages later, Lepore says:

It was one of the most fun research benders I've ever been on.

It ends in fun.

You may be a scholar if you have this pattern. To me, one of the biggest downsides of becoming department head is having less time to fall down some unexpected hole and follow its questions until I reach the bottom. I miss that freedom.

Posted by Eugene Wallingford | Permalink | Categories: Patterns, Personal, Teaching and Learning

June 30, 2017 1:35 PM

Be Honest About Programming; The Stakes Are High

It's become commonplace of late to promote programming as fun! and something everyone will want to learn, if only they had a chance. Now, I love to program, but I've also been teaching long enough to know that not everyone takes naturally to programming. Sometimes, they warm up to it later in their careers, and sometimes, they never do.

This Quartz article takes the conventional wisdom to task as misleading:

Insisting on the glamour and fun of coding is the wrong way to acquaint kids with computer science. It insults their intelligence and plants the pernicious notion in their heads that you don't need discipline in order to progress. As anyone with even minimal exposure to making software knows, behind a minute of typing lies an hour of study.

But the author does think that people should understand code and what it means to program, but not because they necessarily will program very much themselves:

In just a few years, understanding programming will be an indispensable part of active citizenship.

This is why it's important for people to learn about programming, and why it's so important not to sell it in a way that ambushes students when they encounter it for the first time. Software development is both technically and ethically challenging. All citizens will be better equipped to participate in the world if they understand these challenges at some level. Selling the challenges short makes it harder to attract people who might be interested in the ethical challenges and harder to retain people turned off by technical challenges they weren't expecting.

Posted by Eugene Wallingford | Permalink | Categories: Computing

June 29, 2017 4:03 PM

A New Demo Compiler for My Course

a simple FizzBuzz program

Over the last couple of weeks, I have spent a few minutes most afternoons writing a little code. It's been the best part of my work day. The project was a little compiler.

One of the first things we do in my compiler course is to study a small compiler for a couple of the days. This is a nice way to introduce the stages of a compiler and to raise some of the questions that we'll be answering over the course of the semester. It also gives students a chance to see the insides of a working compiler before they write their own. I hope that this demystifies the process a little: "Hey, a compiler really is just a program. Maybe I can write one myself."

For the last decade or so, I have used a compiler called acdc for this demo, based on Chapter 2 of Crafting A Compiler by Fischer, Cytron, and LeBlanc. ac is a small arithmetic language with two types of numbers, sequences of assignment statements, and print statements. dc is a stack-based desk calculator that comes as part of many Unix installations. I whipped up a acdc compiler in Java about a decade ago and have used it ever since. Both languages have enough features to be useful as a demo but not enough to overwhelm. My hacked-up compiler is also open to improvements as we learn techniques throughout the course, giving us a chance to use them in the small before students applied them to their own project.

I've been growing dissatisfied with this demo for a while now. My Java program feels heavy, with too many small pieces to be simple enough for a quick read. It requires two full class sessions to really understand it well, and I've been hoping to shorten the intro to my course. ac is good, but it doesn't have any flow control other than sequencing, which means that it does not give us a way to look at assembly language generation with jumps and backpatching. On top of all that, I was bored with acdc; ten years is a long time to spend with one program.

This spring I stumbled on a possible replacement in The Fastest FizzBuzz in the West. It defines a simple source language for writing FizzBuzz programs declaratively. For example:

produces the output of a much larger program in other languages. Imagine being able to pull this language during your next interview for a software dev position!

This language is really simple, which means that a compiler for it can be written in relatively few lines of code. However, it also requires generating code with a loop and if-statements, which requires thinking about branching patterns in assembly language.

The "Fastest FizzBuzz" article uses a Python parser generator to create its compiler. For my course, I want something that my students can read with only their knowledge coming into the course, and I want the program to be transparent enough so that they can see directly how each stage works and how it interacts with other parts of the compiler.

I was also itching to write a program, so I did.

I wrote my compiler in Python. It performs a simple scan of the source program, taking as much advantage of the small set of simple tokens as possible. The parser works by recursive descent, which also takes advantage of the language's simple structure. The type checker makes sure the numbers all make sense and that the words are unique. Finally, to make things even simpler, the code generator produces an executable Python 3.4 program.

I'm quite hopeful about this compiler's use as a class demo. It is simple enough to read in one sitting, even by students who enter the course with weaker programming skills. Even so, the language can also be used to demonstrate the more sophisticated techniques we learn throughout the course. Consider:

  • Adding comments to the source language overwhelms the ad hoc approach I use in the scanner, motivating the use of a state machine.
  • While the parser is easily handled by recursive descent, the language is quite amenable to a simple table-driven approach, too. The table-driven parser will be simple enough that students can get the hang of the technique with few unnecessary details.
  • The type checker demonstrates walking an abstract syntax tree without worrying about too many type rules. We can focus our attention on type systems when dealing with the more interesting source language of their project.
  • The code generator has to deal with flow of control, which enables us to learn assembly language generation on a smaller scale without fully implementing code to handle function calls.
So this compiler can be a demo in the first week of the course and also serve as a running example throughout.

We'll see how well this plays in class in a couple of months. In any case, I had great fun ending my days the last two weeks by firing up emacs or IDLE and writing code. As a bonus, I used this exercise to improve my git skills, taking them beyond the small set of commands I have used on my academic projects in the past. (git rebase -i is almost my friend now.) I also wrote more pyunit tests than I have written in a long, long time, which reminded me of some of the challenges students face when trying to test their code. That should serve me well in the fall, too.

I do like writing code.

Posted by Eugene Wallingford | Permalink | Categories: Software Development, Teaching and Learning