Computing is a Liberal Art

I teach two introductory computing classes at Bard: one using Python (using IPRE’s Calico and robots) and the other with Processing. Both programming environments could be better by borrowing ideas from the other. And by better, I mean a lower floor, making it easier for newcomers to programming; and a higher ceiling, making the tool useful after CS1. Rather than concentrating exclusively on one tool, I am continuing to attack the problem on both fronts.

This post is focused on making Processing better for introductory courses; Calico is next.

My first attempt is a simple tool called sp5repl, a small layer around Scala and Processing that allows you to write Processing sketches dynamically using an interactive read-eval-loop. The code entered into the Scala REPL is actually compiled, thus it runs at full speed; we get most of the flexibility of Jython and Clojure/Quil with the speed and error checking of Scala. A small example that generates the image below:

sp5repl>size(250, 250)
sp5repl>background(24)
sp5repl>smooth()
sp5repl>fill(196, 128, 64)
sp5repl>ellipse(width/2, height/2, 150, 150)
sp5repl>fill(64, 128, 196)
sp5repl>for (i <- width to 0 by -1) ellipse(random(i), i, i/20, i/20)

Continue reading sp5repl: A Read-Eval-Processing Loop with Scala

What I like most about Keith’s post is that it asks precisely the right questions about how to best use an emerging medium in public outreach and education. Too often we can become fixated on new technology and try to use it as much as possible because it’s new, or because it seems able to fit (albeit often awkwardly) into an existing paradigm. Instead we should be thinking about how these technologies work, how they are changing our social habits, and develop our uses of them appropriately.

Children’s media has been trying to provide “instruction with delight” since we’ve had media content designated specifically for children. The celebrated children’s publisher John Newbery (called the “Father of Children’s Literature”) promised just this combination in A Little Pretty Pocket Book in 1744. But every medium has different properties, so understanding what kinds of delight a medium can afford is crucial to being able to make it educationally effective.
Continue reading Making the Most of the Medium: A Response

If we were creating Sesame Street from scratch in 2012 would it use Scratch? A Scratch-based Facebook? A Pre-school-MOOC? If we wanted to create a large publicly-funded 21st century education equalizer — what would that look like?

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At Bard we like to experiment, particularly with education. Bard runs various public high school early colleges throughout the country and is involved in higher education throughout the world. Later this week, Bard’s Center for Curatorial Studies (the program that gets the CS acronym on campus, computer science is shortened to CMSC) is hosting a conference on experimental education. Maria Sachiko Cecire, who will write a follow-up to this post, will speak at this conference about Bard’s new Experimental Humanities concentration she directs, and if distilled to a single quote:

“…provides students with the historical context, theoretical background, and analytical and technical skills needed to engage productively with new forms of humanistic inquiry in our digital age”

The concentration emphasizes the need to think critically in many modes at once, e.g. text, film, and digital media. As my first blog post indicates, my participation stems from an interest in promoting digital literacy and reforming our “read-only” digital culture, as Larry Lessig might put it. Ultimately, we hope literacy in experimental media can push the boundary in terms of thinking and education.

Continue reading Doubling Down on Experimental Public Education

Brett Victor recently posted an intriguing essay entitled Learnable Programming. I’ve been a fan of many of his essays (e.g., [1] and [2]). Victor is quite a pioneer of what we might refer to as design-based computing pedagogy as opposed to a programming or assessment driven pedagogy. And this essay surely lives up to his previous work; I think I could write fifty blog posts reacting to this single essay. T-49 …

Pedagogical Processing

I use Processing in my introductory computing class at Bard. This semester is my third iteration of the class. I chose Processing for a variety of reasons, some of which overlap:

• Processing allows artists and designers to write real code with relatively little pain.
• Processing balances developing powerful programmed artifacts with a relatively simple programming interface.
• Processing has a welcoming, productive open-source community.
• A ton of libraries and examples help students write relevant, meaningful sketches (e.g. with video, images, sounds, etc.)

Continue reading Learnable Processing Programming: Part One

Why aren’t computer scientists the best teachers?

(Or, why our students aren’t robots.)

“Science is knowledge which we understand so well that we can teach it to a computer; and if we don’t fully understand something, it is an art to deal with it. Since the notion of an algorithm or a computer program provides us with an extremely useful test for the depth of our knowledge about any given subject, the process of going from an art to a science means that we learn how to automate something.”
—Computer Programming as an Art, Donald Knuth, CACM, December 1974.

Why aren’t computer scientists better teachers? Or rather, why aren’t computer scientists the best teachers? We are very good — pros, in fact — at explaining things in absolute detail to things that know absolutely nothing. If we can explain quicksort to a RISC machine, we should surely be able to teach binary-search to teenagers, right?

But of course we don’t teach our computers. And we don’t program our students. Or do we?

Continue reading On Computational Teaching