Archive for June, 2014

Male- and female-dominated fields | Gas station without pumps

Interesting post on how STEM isn’t all male-dominant, but Engineering and CS are SO male dominant, it shifts the average.

Computer science is a particularly strange case, as it has seen more fluctuation both in raw numbers of students data not shown here and gender balance than any other field. Other fields have seen large shifts in gender balance, but they have generally been gradual and nearly monotonic—not reversing course in the early 1980s.  It seems to me that the biggest drops in the ratio of women in CS came at times when the overall number of students in CS was dropping like after the dot-com bubble burst in the 2000.  When CS grew, the number of women grew faster than the number of men.  When CS shrunk, the number of women shrunk faster than the men.  Perhaps if CS education had had a steady growth, rather than the boom-and-bust cycles that have plagued it since the late 1970s, it would not have had such a mysterious rise and fall in proportion of women in the field. The boom-and-bust cycles are not driven by the real need for CS degrees, but by media hype about relatively small shortages or excesses of personnel.  I believe that the demand for CS degrees has been stabler than the supply unlike most other fields, where the supply has been steady even as demand has fluctuated.

via Male- and female-dominated fields | Gas station without pumps.

June 28, 2014 at 9:40 am 3 comments

“Disruptive Innovation” in Universities is not as important as Value

The below-linked article by Jill Lepore is remarkable for its careful dissection of Christensen’s theory of “disruptive innovation.” (Thanks to Shriram Krishnamurthi for the link.)  As Lepore points out, Christensen’s theories were referenced often by those promoting MOOCs.  I know I was told many times (vehemently, ferociously) that my emphasis on learning, retention, diversity was old-fashioned, and that disrupting the university was important for its own sake, for the sake of innovation.  As Lepore says in the quote below, there may be good arguments for MOOCs, but Christensen’s argument from a historical perspective just doesn’t work.  (Ian Bogost shared this other critical analysis of Christensen’s theory.)

I just finished reading Michael Lewis’s The Big Short, and I see similarities between how Lepore describes reactions to Christensen’s theory of “disruptive innovation” and how Lewis describes the market around synthetic subprime mortgage bond-backed financial instruments.  There’s a lot of groupthink going on (and the Wikipedia description is worth reading), with the party line saying, “This is all so great!  This is a great way to get rich!  We can’t imagine being wrong!”  What Lewis points out (most often through the words of Dr. Michael Burry) is that markets work when there is a logic to them and real value underneath.  Building financial instruments on top of loans that would never be repaid is ludicrous — it’s literally value-less.  Lepore is saying something similar — innovation for its own sake is not necessarily valuable or a path to success, and companies that don’t disruptively innovate can still be valuable and successful.

I don’t know enough to critique either Lewis or Lepore, but I do see how the lesson of value over groupthink applies to higher-education.  Moving education onto MOOCs just to be disruptive isn’t valuable.  We can choose what value proposition for education we want to promote.  If we’re choosing that we want to value reaching students who don’t normally get access higher education, that’s a reasonable goal — but if we’re not reaching that goal via MOOCs (as all the evidence suggests), then MOOCs offer no value.  If we’re choosing that we want students to learn more, or to improve retention, or to get networking opportunities with fellow students (future leaders), or to provide remedial help to students without good preparation, those are all good value propositions, but MOOCs help with none of them.

Both Lewis and Lepore are telling us that Universities will only succeed if they are providing value. MOOCs can only disrupt them if they can provide that value better.  No matter what the groupthink says, we should promote those models for higher-education that we can argue (logically and with evidence) support our value proposition.

In “The Innovative University,” written with Henry J. Eyring, who used to work at the Monitor Group, a consulting firm co-founded by Michael Porter, Christensen subjected Harvard, a college founded by seventeenth-century theocrats, to his case-study analysis. “Studying the university’s history,” Christensen and Eyring wrote, “will allow us to move beyond the forlorn language of crisis to hopeful and practical strategies for success.” … That doesn’t mean good arguments can’t be made for online education. But there’s nothing factually persuasive in this account of its historical urgency and even inevitability, which relies on a method well outside anything resembling plausible historical analysis.

via Jill Lepore: What the Theory of “Disruptive Innovation” Gets Wrong : The New Yorker.

June 26, 2014 at 7:44 am 6 comments

We need computing in schools, in whatever category will work

At the NCWIT Summit this year, I heard an interesting concern.  If CS counts as a mathematics or science course towards high school graduation requirements, will that make CS even less diverse?  Should we keep CS as a business topic (elective) where the women and under-represented minorities are?

I took up that question for my Blog@CACM post for this month: Why Counting CS as Science or Math is Not Considered Harmful. I argue that our goal is universal computational literacy, with everyone using computing in every class and everyone taking CS.  I don’t really care how it gets a foothold in schools.  It was fun to write about Alan Kay, Adele Goldberg, and Andy diSessa, pointing out that they were talking about these ideas long time before computational thinking.

 

June 24, 2014 at 8:48 am 8 comments

Is Coding the New Literacy? What does learning to code buy you?

The article posted below is a carefully-considered (not a “Rah! Rah! Let’s Code!”) and intriguing consideration of the role of coding in modern notion of literacy.  I particularly liked the idea below.  Is Annettee Vee right?  Does knowing about coding inform your ability to think about things to code?  I suspect that’s true, but it’s an empirical question.  It’s much nearer transfer, and is not as much of a stretch as looking for evidence of general problem-solving skills from programming (which is very rare) or applying a computational framework for understanding the world (i.e., computational thinking).

The happy truth is, if you get the fundamentals about how computers think, and how humans can talk to them in a language the machines understand, you can imagine a project that a computer could do, and discuss it in a way that will make sense to an actual programmer. Because as programmers will tell you, the building part is often not the hardest part: It’s figuring out what to build. “Unless you can think about the ways computers can solve problems, you can’t even know how to ask the questions that need to be answered,” says Annette Vee, a University of Pittsburgh professor who studies the spread of computer science literacy.

via Is Coding the New Literacy? | Mother Jones.

June 22, 2014 at 9:32 am 11 comments

Let’s do the math: Does it make sense to fill a pipeline of CS workers from 3rd grade?

According to the article linked below, there is a large effort to fill STEM worker jobs in Northern Virginia by getting kids interested in STEM (including computing) from 3rd grade on.  The evidence for this need is that there will be 50K new jobs in the region between 2013 and 2018.

The third graders are 8 years old.  If they can be effective STEM workers right out of high school, there’s another 10 years to wait before they can enter the workforce — 2024.  If they need undergrad, 2028.  If they need advanced degrees, early 2030’s.  Is it even possible to predict workforce needs out over a decade?

Now, let’s consider the cost of keeping that pipeline going, just in terms of CS.  Even in Northern Virginia, only about 12% of high schools offer CS today.  So, we need a fourfold increase in CS teachers — but that’s just high school.  The article says that we want these kids supported in CS from 3rd grade on.  Most middle schools have no CS teachers.  Few elementary schools do.  We’re going to have to hire and train a LOT of teachers to fulfill that promise.

Making a jobs argument for teaching 3rd graders CS doesn’t make sense.

The demand is only projected to grow greater. The Washington area is poised to add 50,000 net new STEM jobs between 2013 and 2018, according to projections by Stephen S. Fuller, the director of the Center for Regional Analysis at George Mason University. And Fuller said that STEM jobs are crucial in that they typically pay about twice as much as the average job in the Washington area and they generate significantly more economic value.

It is against this backdrop that SySTEMic Solutions is working to build a pipeline of STEM workers for the state of Virginia, starting with elementary school children and working to keep them consistently interested in the subject matter until they finish school and enter the workforce.

via To create a pipeline of STEM workers in Virginia, program starts with littlest learners – The Washington Post.

June 19, 2014 at 8:29 am 12 comments

Teaching programming could be made easier

Gas station without pump’s post on Garth’s complaint “Teaching programming is not getting easier” intrigued me.  Garth does a good job of pulling together a lot of the themes of what makes teaching CS hard today.  I think that we can improve the situation.  I’m particularly interested in learning how to scaffold the development of programming knowledge, and we have to find ways to create professional communities of CS teachers.  There are techniques to share (worked examples, peer instruction, pair programming, Parson’s problems, audio tours), and we’re clearly not doing a good job of it yet.

In programming there are 4 homework problems over the period of a week, none of which are “easy”, and all require some problem solving and thinking.  There is somewhat of an incremental progression to the problems but that step from written problem to code is always a big one.  It is somewhat similar to solving word problems in math, every student’s favorite task.  For programming there are no colleagues available that have as much or more experience to pull teaching ideas from, if there are any other programming teachers at all.  There are no pedagogical resources anywhere online for teaching strategies.  After watching a number (3) of programming teachers teach it seems the teaching strategy is pretty consistent; show and tell and hope.

via Teaching programming is not getting easier. | Garth’s CS Education Blog.

June 17, 2014 at 8:55 am 12 comments

Guest Post from Shriram Krishnamurthi: Growing respect for Research around Computational Learning and Thinking

Shriram and I had an email correspondence around the blog posts aboutrenaming the field and gaining respect for the study of how people learn and think about computation. He suggested a path forward that was about re-connecting to the fields that the CSEd community broke away from. I invited him to prepare a guest post that conveyed these ideas. Thanks to him for this!

Let me suggest you are probably trying to achieve two very different things here.

1. Create an actual community. There is real value to having all the interesting people from one area in one room. (This is why, despite the trouble it is to get there and back, I almost never say no to a Dagstuhl invitation.)

2. Have your students publish in venues such that, when they go out onto the job market, research universities such as yours (Georgia Tech) and mine (Brown) will notice and respect them, interview them, and make them tenure-track offers so they can have students of their own.

Unfortunately, I believe that right now these are fundamentally conflicting goals. SIGCSE, ITiCSE, and ICER address the former but not really the latter.

One, unrealistic, option is for 1 and 2 to merge. For this to happen, these venues need to become a whole lot better. I hear great things about the structure of ICER, but some of the papers are great while others are at best so-so. Changing the other two is harder than turning around an aircraft carrier. It may be possible to make ICER a stronger conference, but one small conference cannot really a whole area make. Plus, you still need to convince people to pay attention to it.

The only other option I see is to do both. Attend whatever conferences you need to to form a community. But get your students to publish at really good venues outside the area. That way, they can write a gung-ho application: “Look, I’m perfectly capable of holding my own in the open competition of conferences you respect”. People like Amy Ko—who published her work in conferences like ICSE—or my colleague Jeff Huang—an HCI person with strong publications in information retrieval—are examplars whose technical chops can’t be questioned.

In other words, this is a long response that could be abbreviated to “Yes, you should grow CSEd by sending it to more respected venues”, but I’m also showing you some of my thinking (because a good teacher grades the work, not just the answer!). A student who publishes a few papers in some conference already recognized as respectable technical CS is going to stand a far better chance. Once a dozen of those populate good departments and start producing students of their own, you’ve pretty much gotten over any prejudice and can then reset your standards. (Though I would still say it’s unhealthy to drop ties to these other areas and retreat into a CSEd shell.)

Which conferences, of course, depend on the student. For students doing HCI work, it might be SIGCHI; for those doing software engineering, it might be ICSE; for machine learning, ICML; for information retrieval, SIGIR; and so on. One good bit of advice to a young CSEd PhD student might be, “Find another area of CS in which you can demonstrate enough depth to publish papers in its good conferences and be able to hold your own in conversations with an expert in that field”.

Here are three other things to consider.

1. Being able to hold one’s own in another field creates natural allies in a department. A non-CSEd faculty member who realizes there will not be hires in their own area is likely to become an advocate for a CSEd candidate who has at least some presence in their area.

2. I feel the CSEd community has let itself be put into the “liberal arts ghetto” or, at the research university level, “instructor ghetto”. The leaders of “research” are tenured professors, but the leaders of “education” are Instructors, Professors of Practice, and so forth. This is a self-perpetuating cycle. For instance, who is the CSEd applicant going to get letters from? Getting a letter from an Instructor naturally makes the tenured faculty think, “Hmm, why should we take this person seriously?”

3. Finally, candidates need to be able to demonstrate a growth path. When I look at a candidate we’ve decided to interview, I’m only so interested in what they did before: their past achievements got them their interview, so now I’m interested in what lies ahead. I care to see what kind of agenda they have mapped out—is it interesting, is it hard, could someone else do it, etc.—and what skills they bring to the table (can they do it, and can they do it better than others).

I imagine this step is hard for some CSEd candidates. If you got a PhD studying some population, it may or may not be interesting to keep studying that population or to study the next such population or whatever. At the very least, then, if you intervened, showed an N% improvement, and have good plans to get to much more, and then show a path to bigger and more interesting problems, now you’ve got my interest. Put differently, think in terms of active interventions that demonstrate impact. Now you become comparable to students who are building or verifying software, deriving inferences from datasets, and so on. I don’t know whether CSEd students are getting advice in terms of presenting themselves this way.

June 12, 2014 at 8:36 am 5 comments

A flawed case against teaching: Scaffolding, direct instruction, and learner-centered classrooms

Premise 1: Teaching is a human endeavor that does not and cannot improve over time.

Premise 2: Human beings are fantastic learners.

Premise 3: Humans don’t learn well in the teaching-focused classroom.

Conclusion: We won’t meet the needs for more and better higher education until professors become designers of learning experiences and not teachers.

at Change | The Case Against Teaching

——

Interesting argument linked above, but wrong.

 

June 10, 2014 at 9:57 am 5 comments

Hands up who likes PHP? The role of popular programming languages in Computing Education

I was at the NSF CS10K Evaluators meeting earlier this summer, and we got to talk about important research questions. Someone suggested the issue of learning progressions. How do students move from Scratch or Alice or Blockly to Java or C++? One of the evaluators, whose background is entirely in education and evaluation, asked, “Professional programmers don’t use Scratch and Alice?” We explained what professional programmers really do. “Then why are we teaching Scratch and Alice, especially if we don’t know how the transfer works?!?”

The tension between what languages are “useful” (read: “we use them today in industry”) and what languages are helpful for learning has always existed in CS Ed. I’ve recommended the blog below to several people this summer, including reading  the comments from the developers who push back — “Yeah, stop with Alice and teach real languages!”  I agree with the post’s author, but I see that, even in the CS10K project, the notion that we should teach what’s vocationally useful is strong.

At the NSF CS10K Evaluators meeting, I got to wondering about a different question. Most of our evaluators come from science and math education projects, where you teach the way the world is.  If you have trouble teaching students that F=ma, you better just find a new way to teach it. I told the evaluators that I hope their results inform the design of future programming languages. Computer science is a science of the artificial, I explained. If you find that mutable variables are hard to understand, we can provide programming languages without them. If the syntax of curly braces on blocks is too subtle for novices to parse (as I predict from past research findings), we can fix that, too. I got confused looks. The idea that the content and the medium could be changed is not something familiar to this audience. We have to figure out how to close that loop from the evaluators to the designers, because it’s too important an opportunity to base our language design for novices on empirical results.

It is a school’s job to churn out students who will be able to walk into a job in industry on day one and work in whatever language/paradigm is flavour du jour.
WRONG! We’re here to teach children the core concepts of Computer Science. Working on that basis to produce someone with employable skills is your job. Do you expect Chemistry students to walk out of school ready to begin work in a lab? Should we stop using Scratch as a teaching language because nobody programs with it in industry? Of course not, so please stop recommending that we should be teaching using Scala/JSON/whatever is currently flavour of the month.

via Hands up who likes PHP? | Code? Boom..

June 8, 2014 at 7:30 am 20 comments

Engaging Women with Context in Hard Science: A Visit to SpaceX

After the NCWIT Summit, we had two days of meetings with ECEP State Partners and our Advisory Board, hosted by Debra Richardson at the University of California at Irvine. Then, Barbara and I got a chance to visit with Alan Kay for a few hours on Friday. As always, we came away with pages of notes and a long list of things to read and think about. All of these meetings were productive and interesting, but the next stage on our California adventure has had me thinking about how we teach hard science and hard computer science.

A former student at Georgia Tech and one of the first MediaComp Teaching Assistants, Jim Gruen, now works at SpaceX. He invited Barb and I to come up for a tour. We rented a car and drove to Hawthorne.

Barb-at-SpaceX

Barb at SpaceX

What an amazing place! The front third of the building are where the 40 programmers (“Everything is software,” Jim told us) sit with other engineers and developers. The back 2/3’s of the building is the factory floor where rockets are assembled. As you walk onto the floor, there is mission control to your right, and above your head is the actual Dragon capsule that first docked with the International Space Station. It is an inspiring sight as you walk onto the factory floor.

We saw rockets being built! Jim showed us where engines are being assembled into racks, where carbon composites are molded into parts, where detailed metal parts are made with 3-D (metal!) printers, and where the parts of the fuel tanks are welded together then painted. We saw the shop where they’re making prototype space suits. We saw via live video stream (on a giant TV on the wall of the developers’ floor) the amazing Dragon Taxi that was just recently unveiled. We saw lots of people (mostly men, unfortunately) working to build a future where humans are space-faring.

I was deeply impressed. SpaceX has a corporate goal to put human beings on Mars. What a noble goal! (Perhaps we could compare that to a corporate goal of, say, getting more people around the world to drink fizzy, flavored sugar-water?)

Jim does kernel-level hacking. He works on the boot sequence for the flight computer, networking, and device drivers. He showed us his current project. He is integrating in the module responsible for firing the rocket that will pull the astronauts off of the rocket in case there is an explosion during take-off.

I left the SpaceX feeling like I just had a glimpse of the future. The discussions when I tell people about our visit have had me thinking about how we prepare students for that future.

SpaceX is exciting and motivating to everyone I’ve talked to. Admittedly, I tend to hang out with people interested in science and engineering. Our daughters were jealous that we got to visit SpaceX. The other night, my 16 year old daughter had a girlfriend over for dinner, and the friend had questions for me about SpaceX.  I was shocked — my teenage daughter is telling her female friends stories about her parents’ adventures?!?  All the undergraduate and graduate students that I have told about SpaceX were impressed and had questions about our visit, both male and female students.

I do believe in the literature that suggests that women are socialized to be motivated to help people, and that efforts like service learning can motivate women to study CS. That’s part of the motivation for efforts like HFOSS. Many people are asking the question why women aren’t pursuing the “hard sciences.”

Maybe we’re using the wrong context in the hard sciences. Many people (not just women) don’t get too excited about physics, chemistry, and engineering. Everyone I’ve talked to is very excited about SpaceX. Working at SpaceX requires lots of “hard science.” The stuff that Jim is doing is low-level and geeky — rebuilding the Linux kernel stuff.  My kids are still fascinated about it. Maybe women and other students would be more excited about science if the connection was made to end goals like SpaceX and to helping get humans onto other planets.

Context matters for science education, as well as for computing education. As my colleagues Betsy DiSalvo and Amy Bruckman (2011) wrote:

Computer science is not that difficult but wanting to learn it is.

Maybe that goes for “hard science,” too.  SpaceX is a great reason to want to learn a lot of “hard science.”


 

Postscript: I told my daughters about this blog post.  One daughter said, “We’ve both been to Space Camp (in Huntsville).  Space Camp would be great except for that one annoying guy who always thinks he knows everything and wants to tell everyone all about it.” The other daughter agreed.  Context is important, but we have to get the social stuff right, too.

 

June 5, 2014 at 8:05 am 2 comments

NCWIT Summit 2014: Changing Computing Education in US States

The 2014 National Center for Women & IT (NCWIT) summit was fantastic. I was at the first NCWIT national meeting ten years ago, and I have been at several since. They are always thought-provoking and enlightening. I may have enjoyed this one more because I got a chance to present as well as be in the audience.

(Thanks to Robert Walker for the picture and for allowing me to post it here.)

I offered a workshop on how to change state education public policy to improve and broaden access to computing education. The slides from the workshop are available here in PDF and here in PPTX. The workshop was offered twice: Tuesday afternoon (SRO packed room of about 40!) and Wednesday morning (maybe 25). I had a half-dozen hallway conversations from people who wanted to talk about their state in particular. Overall, there was a significant interest.

All the workshop presenters advertised their workshops as a Flash talk. A Flash talk is intense: exactly 20 slides, presented for exactly 15 seconds each. No control over either. Jeff Forbes hosted the Flash talks. They were all recorded by Turner Broadcasting, and you can see them all here. (I’m the first one.) My slides are available here in PPT format.

What can you possibly say in exactly five minutes? I worked harder on that five minute talk than on most of the keynotes I have ever presented. I’ve been thinking about this since last December when I wrote the initial blog post on this idea. In the end, the structure of what I was saying was good, and I ended up using it for the workshop, too.

To change a state, start here

I proposed a four step process to start changing a state:

  1. Find a leader(s): Computing education reform doesn’t just happen. Someone (or a small group of someones) has to take the initiative.
  2. Figure out where you are and where you’re going: The hardest part is seeing the big picture (of how schools, higher education, businesses, and state politics have to work together) and figuring out how to make change within a state. Two years into ECEP, and I am still surprised at the state differences. Here’s one I just learned. Hawaii makes all education decisions at the district level (like California and Massachusetts), but all of Hawaii is one school district. All those islands, one school board.
  3. Gather your allies: Find all the high school teachers, university faculty, business leaders, and state Department of Education leaders who want to work together. We find that efforts that speak with multiple voices from different sectors to promote computing education tend to get more influence in state government.
  4. Get initial funding: There are big ticket items for computing education, like professional learning opportunities for all your high school teachers. But there are smaller ticket items that need to happen early on in the process. One of these is a landscape report: Where are you now. There are several of these available at the CSTA website. Another is a summit, a face-to-face meeting of all your allies, along with the people that you’d like to influence (the ones who will come), to develop a set of shared goals and a shared strategy for getting there.

Plenaries: 80-hour work weeks are a human issue, not a women’s issue

NCWIT summits always have a mix of alliance meetings (Academic Alliance, K-12 Alliance, Workforce Development, Social Science Advisory Board) and plenaries, besides workshops. All the plenaries were recorded and are available here. A few of the plenaries were just so amazing that I want to highlight them.

Michael Kimmel is a social scientist working in masculine studies. His talk on engaging men to support women in technology was the my favorite talk of the summit. He was hilarious, yet grounded in real data. He explained what Larry Summers got wrong in his comments when he said that “many women with young children are unwilling or unable to put in the 80-hour work-weeks needed to succeed in those fields.” Kimmel pointed out that that framing implies men inviting women into a world where men’s values rule. If men and women had equal status in science, would we require 80-hour work weeks? Do we want anyone to work that hard at science and the consequent neglect of other priorities? Survey results show that men value time with their families more, but feel pressured by other men to be the “unencumbered worker” who will put in those hours and value work above all else. “Why do we call these concerns women’s issues when they’re really family issues or even human issues?”

Dr. Chelsea Clinton spoke and was amazing. She was articulate, confident, and well-prepared to speak to issues of gender diversity and technology. She just completed her doctorate at Oxford, so this was her first talk where she was introduced as Doctor Chelsea Clinton.

I didn’t really know who Donna Brazile was before she spoke. I didn’t know that she ran Al Gore’s presidential campaign, or that she’s a CNN commentator and columnist, or that she’s done cameos on shows like “House of Cards.” I’ve looked her up since she gave such a terrific speech at the NCWIT Summit. She was funny, irreverent, and compelling.

All in all, it was a great summit.  I learned a lot and made a lot of useful contacts.  We now are talking with people in several other states about ECEP working with them to improve and broaden participation in computing education.

June 3, 2014 at 8:01 am 3 comments


Enter your email address to follow this blog and receive notifications of new posts by email.

Join 9,004 other followers

Feeds

Recent Posts

Blog Stats

  • 1,875,389 hits
June 2014
M T W T F S S
 1
2345678
9101112131415
16171819202122
23242526272829
30  

CS Teaching Tips