NSF BPC and CPATH end

The NSF CISE (CS-stuff) Division is cancelling the CPATH (CISE Pathways to Reinvigorate Undergraduate Education) and BPC (Broadening Participation in Computing) programs. The April CPATH call for proposals has been cancelled. Right now, the May BPC call is still going forward. We’re told that CISE is creating a new program to fund work in computing education, from middle school level up. All currently funded proposals will be honored. This does raise questions about the efforts started that will require additional funding, like the creation of the new APCS exam, the CS 10K effort (to create 10K high school CS teachers in 10K schools by the time the new AP CS starts in 2015), and the renewals for the BPC Alliances, like Georgia Computes!

What if “CS1” is just a really bad idea?

At the AP CS Commission meeting this last weekend, we addressed the question, “How would we know if we’ve done our job right?  How would we know if  this is a good class?”  It’s an important question to ask about anything, but I realized from the discussion that it’s a particularly hard question to ask about a class or a class definition.

We talked about the five pilots of this class which are going to take place in Fall 2010. (Yes, the teachers have been picked, and no, I’m not allowed to say yet who they are — they’ll be announced at SIGCSE 2010, I understand.)  These are all excellent teachers.  What could go wrong?  I started listing the problems that could occur.  Sure, those things could go wrong — but what would you attribute a failure to?  What evidence would you need to convince you that the idea of the class is bad, e.g., that the learning objectives are too big and too broad and can’t be covered in a one-College-semester or one-High-School-year course?

In any given offering of the class, outcomes might suggest that something went wrong — a high withdrawal or failure rate, students do not perform well on a post-test, or the loss of more women and minorities than white or Asian males.  Would you say that that was just bad luck? Maybe it was students in the class?  Maybe they were under-prepared, or unmotivated, or had a bad mix of personalities so that they were always annoyed with each other or with the teacher?  Maybe it was a bad teacher?  Maybe the approach to teaching the learning objectives was bad — a lousy book, an inappropriate use of project-based or inquiry-based learning, boring lectures, or bad homework?  Maybe the room was at fault — uncomfortable, poor HVAC, faulty A/V? Maybe the school didn’t support  the class well, or the graders were bad, or there were rumors about the class going around the school creating a set of weird expectations?

But at what point would you decide, “You know, I don’t think that this class works?”  What would convince you?

Now, let’s consider Jens Bennedsen and Michael Caspersen’s paper surveying CS1 failure rates across North American and Europe.  These failure rates range between 30-50% in the US, and even higher (on average) in Europe.  If you have a class that hundreds of schools can’t teach without flunking out half the students, maybe the whole class is a bad idea?  Maybe the set of learning objectives for CS1 are just too big and it’s actually the rare case (a correct combination of teacher, book, approach, room, school, etc.) where the class actually results in learning gains for most if not all students.

I’m not making the argument here that CS1 is a really bad idea.  I am raising the question of “How would you know?”

Context matters, not just my context

I had a really interesting conversation yesterday with Ron Eglash of RIT at the BPC Community Meeting.  Ron does wonderful work exploring the computing and mathematics in cultural practices, like the transformational geometry in how cornrows are woven, or the complex graphics algorithms in Native American bead weavings.  He mentioned that one of the surprising things he’s discovered is that the context matters a lot, but it doesn’t have to be their context.  As he’s been taking his design tools to places like Ghana and to peoples like the Inuit in Alaska, he finds that students often find most interesting the tools not from their own context.  He says that he shows them all his tools, then let’s them pick what they want to explore further, and they rarely pick their own culture’s practices.

I think that meshes with what we’re learning about contextualized computing education.  Not all the students in our IPRE CS1 want to become roboticists, but the students recognize that robotics is part of CS, so the robotics context brings meaning to what they’re doing.  Lana Yarosh found that 60-70% of the students in the Media Computation data structures class found  that the media context made the class more interesting and more motivating — even though the majority of the students were Industrial and Systems Engineers who were probably not going to be doing much media manipulation in their careers.

All these stories remind me of Viktor Frankl’s Man’s Search for Meaning — not that I’m saying taking a computer science class is like surviving a concentration camp!  Piaget said that humans are sense-making: we try to make sense of situations. Frankl said that humans are meaning-making: we need to have a reason for doing.  Ron’s work and our contextualized computing education is about providing meaning, demonstrating the value of what’s being learned, and giving a reason for making the effort to make sense of the material.

Context matters.  I have to value the context, but it doesn’t have to be my context.