Media Computation is not “done”

I heard from a colleague last week that Media Computation is “done.”  “There are no more research questions to answer.  No one will be able to publish on it anymore.”  I’m at a Media Computation workshop in Kansas City this week where I can assure you, nobody thinks all the questions about Media Computation are answered.

What we do know is that adoption of Media Computation (at multiple schools, with both genders and a variety of ethnic groups, including under-represented minorities) has improved retention in the first course compared to the more common approaches to CS1.  That was our explicit goal in designing Media Computation, to address the 30-50% WDF rate.  While that’s a pretty often-repeated result now, I still wonder what that means.  Is Media Computation “teacher proof”?  Could a really lousy teacher do a really lousy implementation that does not improve retention?  Well, of course!  So, what then does that finding mean?  It’s a true statement empirically, and it’s telling us something about what engages and motivates students.  I’m not sure what it tells us about computing education and its practice yet.

What are the other open questions?

• Does Media Computation lead to the same learning? I don’t know.  Nor does anyone else have evidence of their CS1 approach leading to the “same learning.”  We have no way to measure “same learning” across languages and approaches. We are behind other domain-specific education research fields.
• Does Media Computation lead to more interest in computing as a major or minor? The evidence that I’ve seen suggests “no,” and further, there’s not much that we can do with any new approach at the undergraduate level to influence our enrollment numbers.  Sarita Yardi and Amy Bruckman’s ICER 2007 paper suggests to me that decisions about whether computing is a promising career are made by students in their pre-teens.  That meshes with what we’re seeing in our Girl Scout and high school studies.
• Does Media Computation lead to more interest in going on to more computer science classes? I don’t know.  We did have enough interest in our CS1 to build a CS2.  Bryn Mawr is finding that their IPRE approach in CS1 is leading to their largest CS2’s ever, which is using a context of robots and media.  I’m not sure how one would go about answering this question in a way that generalizes across schools — it’s an interesting question.
• What’s the real impact of Media Computation or any contextualized computing approach past the first semester? That’s a hard, interesting, and open question.  Mike Hewner answered this question in one way in his ICER 2008 paper where he studied Georgia Tech seniors and asked them (indirectly) about the impact that their contextualized first course had on the way that they used computing over the rest of their academic career.  Bottomline: Not much.  If you use computing in your other classes, than that first course was useful and spurred on your interest.  But if your major doesn’t use much computing, then that first course may have been enjoyable, but it was one course out of 40 that you took in your undergraduate years — why should that have made much difference?  On the other hand, Lana Yarosh’s paper suggests context is still useful in CS2, and we had a paper in JERIC last year showing the benefit of context in a computer organization class.  Context may still be useful, but maybe different contexts.

What is a contextualized computing education approach, anyway?  Is it just problem-based learning applied to computing? Project-based learning?  Is it “teaching with a theme” as Bill Gates says has been so successful with the high schools funded by the Gates Foundation?  What kind of contexts/themes lead to improved engagement, and which don’t?  Do contexts have to change with generations of kids?  Is that why our generation did fine without contexts (unless computing the next Fibonacci number is a “context”) but we’re seeing an impact of context on this generation?

No, I don’t think MediaComp is “done” yet.  It’s actually a bit worrying that teachers or researchers would think that it is.  That’s all the evidence you need?  You’ll accept something as being “known” with what we have so-far?  As computing education researchers, we should have a higher bar.  It’s one thing to say “It’s no longer interesting” or “It’s pretty clear what direction the results are pointing now.”  It’s another to say that “We know all that we need to know.”