NRC Non-Statement on What is Computational Thinking

I read the new National Research Council report on what is Computational Thinking on the way out here to Berkeley (for the ACM Education Council meeting).  It was fascinating but a little disappointing.  As Marcia Linn explains in Preface to the report, the goal wasn’t to create and present a consensus view of what is computational thinking.  Instead, the report simply presents the discussion, the lack of consensus, with lots of argument and dialogue.  I found the discussion really interesting with some wonderful speakers presented.  I didn’t come away with any answers, though.

I was particularly pleased to read a revisiting of the NRC Fluency with IT report (sometimes called the “FITness Report”), led by Larry Snyder.  There are lots of people creating “information technology fluency” classes, but they often get it wrong.  As this report describes, the FITness report does call for programming — maybe in a domain specific language, maybe even in Excel, but definitely in a precise and testable way.

Some of my favorite parts of the report:

• The discussion of the 2004 NRC report on what is computer science, which quotes Gerald Sussman saying “Computer science is not a science, and its ultimate significance has little to do with computers.  The computer revolution is a revolution in the way we think and in the way we express what we think.”
• Alan Collins (who significantly influenced my dissertation work) whom I haven’t heard much from recently, was there and emphasized the importance of “representational competence, which he described as the effective application of computational means of representation of knowledge.”
• The discussion of modeling is really interesting.  Uri Wilensky and Yasmin Kafai spoke of the importance of having students learn to critique models and question assumptions of models.
• The report quotes Donald Knuth and Fred Brooks (in previously published work) and includes Alan Kay and Roy Pea who were at the event.

The report does get to what I see as one of the key questions of computational thinking.  Asking “What is Computational Thinking?” doesn’t make much sense by itself.  It’s more interesting to ask it in terms of outcomes, “What does computing education for everyone mean and what does such education offer?”  The report does speak to the key question, “Who is ‘everyone‘?”  Thinking about K-12 students as ‘everyone’ leads to one kind of focus on computational thinking, thinking about science and engineering majors leads to another, and thinking about college vs. non-college attending citizens leads to different emphases in computational thinking. The report doesn’t answer the question of who ‘everyone‘ is.  A key contribution of this report is to highlight that question and point out some of the different answers and the implications of each answer.

Adjuncts and Retention Rates

Adjunct faculty are particularly important in computing, where we want students to understand something about computing practice and in particular, gain from the experience of those who have developed expertise through years of effort.  However, we already have retention problems in computer science classes.  Studies like these are important for us — we need to figure out how to use adjuncts to enhance the educational opportunities that we offer students, but we need to do that in a way that avoids a rise in failure rates.

Freshmen who have many of their courses taught by adjuncts are less likely than other students to return as sophomores, according to a new study looking at six four-year colleges and universities in a state system. Further, the nature of the impact of adjunct instruction varies by institution type and the type of adjunct used, the study finds. And in some cases, students taking courses from full-time, non-tenure track instructors or from adjuncts well supported by their institutions do better than those taught by other kinds of adjuncts.

via News: Adjuncts and Retention Rates – Inside Higher Ed.