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Seymour Papert might have predicted this. It doesn’t matter if they’re great or not. It is very hard for educational technology to disrupt school. School fights back, and schoolifies subjects and technologies. I said before: Education is technology’s Afghanistan. Lots of technologies have come in and tried to change everything, and the technologies come out limping.
Massive open online courses will not fundamentally reshape higher education, nor will they disappear altogether. Those are the conclusions of separate reports released this week by Teachers College at Columbia University and Bellwether Education Partners, a nonprofit advisory group.
Neither report contains any blockbuster news for those who have followed the decline of the MOOC hype over the last year or so. But they support the theory that the tools and techniques Stanford University professors used in 2011 to enroll 160,000 students in a free, online computer-science course will be subsumed by broader, incremental efforts to improve higher education with technology.
MOOCs are like free gyms, says Mr. Kelly. They might enable some people—mostly people who are already healthy and able to work out without much guidance—to exercise more. But they won’t do much for people who need intensive physical therapy or the care of a doctor.
The below-linked article is highly recommended. It’s an insightful consideration of the different definitions of “University” we have in the US, and how the goals of helping students become educated for middle class jobs and of being a research university are not the same thing.
This article gave me new insight into the challenges of discipline-based education research, like computing education research. We really are doing research, as one would expect in a research university, e.g., trying to understand what it means for a human to understand computation and how to improve that understanding. But what we study is a kind of activity that occurs at that other kind of university. That puts us in a weird place, between the two definitions of the role of a university. It gives me new insight into the challenges I faced when I was the director of undergraduate studies in the College of Computing and when I was implementing Media Computation. Education research isn’t just thrown over the wall into implementation. The same challenges of technology adoption and, necessarily, technology adaption have to occur.
At the “TIME Summit on Higher Education” that the Carnegie Corporation of New York and Time magazine co-sponsored in September 2013 along with the Bill & Melinda Gates Foundation and the William and Flora Hewlett Foundation, the disconnect between the views of the research university from inside and outside was vividly on display. A procession of distinguished leaders of higher education mainly emphasized the need to protect—in particular, to finance adequately—the university’s research mission. A procession of equally distinguished outsiders, including the U.S. secretary of education, mainly emphasized the need to make higher education more cost-effective for its students and their families, which almost inevitably entails twisting the dial away from research and toward the emphasis on skills instruction that characterizes the mass higher-education model. Time’s own cover story that followed from the conference hardly mentioned research it was mainly about how much economically useful material students are learning, even though the research university was explicitly the main focus of the conference.
Research Outcome: Professors work long hours, spend much of day in meetings, and tuition increases aren’t because faculty are getting raises
To all academics this is totally obvious. But I’m guessing that the general public may not know this. The general public may think that tuition rises are paying for rising faculty salaries, when the dramatic rise in salaries is with coaches and administrators. (Here at Georgia Tech, the faculty have not had raises across the board since January 2008.) As mentioned earlier this month, research funding has decreased dramatically, and the time costs for seeking funding have grown. There’s a blog (meta?) post that is collecting links to all the “Goodbye, Academia” blog posts – faculty who are giving up on academia, and explaining why. All of this context may help explain declining number of American students going into graduate school.
Professors work long days, on weekends, on and off campus, and largely alone. Responsible for a growing number of administrative tasks, they also do research more on their own time than during the traditional work week. The biggest chunk of their time is spent teaching.
Those are the preliminary findings of an ongoing study at Boise State University – a public doctoral institution — of faculty workload allocation, which stamps out old notions of professors engaged primarily in their own research and esoteric discussions with fellow scholars.
Special Issue of ACM Transactions on Computing Education: International K12 CS with “Georgia Computes!”
The special issue of ACM Transactions on Computing Education on primary and secondary schools’ computing has just come out (see table of contents). There are articles on the UK’s Computing at School effort, Tim Bell’s effort in New Zealand, and efforts in Israel, Germany, Italy, Russia, and several others.
This is a particularly big deal for Barb and me, because in this issue, we publish the capstone journal paper on “Georgia Computes!” and describe what resulted from our six years worth of effort. We present both the positives (e.g., big increase in Hispanic participation in CS, teacher professional development touching 37% of all high schools in the state, great summer camp programs spread across the state) and the negatives (e.g., little impact on African American participation, little uptake by University faculty).
Georgia Computes! (GaComputes) was a six-year (2006–2012) project to improve computing education across the state of Georgia in the United States, funded by the National Science Foundation. The goal of GaComputes was to broaden participation in computing and especially to engage more members of underrepresented groups which includes women, African Americans, and Hispanics. GaComputes’ interventions were multi-faceted and broad: summer camps and after-school/weekend programs for 4th–12th grade students, professional development for secondary teachers, and professional development for post-secondary instructors faculty. All of the efforts were carefully evaluated by an external team (led by the third and fourth authors), which provides us with an unusually detailed view into a computing education intervention across a region (about 59K square miles, about 9.9 million residents). Our dataset includes evaluations from over 2,000 students who attended after-school or weekend workshops, over 500 secondary school teachers who attended professional development, 120 post-secondary teachers who attended professional development, and over 2,000 students who attended a summer day (non-residential) camp. GaComputes evaluations provide insight into details of interventions and into influences on student motivation and learning. In this article, we describe the results of these evaluations and describe how GaComputes broadened participation in computing in Georgia through both direct interventions and indirect support of other projects.
Barb will probably do her demographic analysis in the Fall. Gas Station Without Pumps analysis on raw scores is out now and is quite interesting.
The Computer Science A exam saw an increase of 33% in test takers, with about a 61% pass rate 3, 4, or 5. The exams scores were heavily bimodal, with peaks at scores of 4 and at 1. I wonder whether the new AP CS courses that Google funded contributed more to the 4s or to the 1s. I also wonder whether the scores clustered by schools, with some schools doing a decent job of teaching Java syntax most of what the AP CS exam covers, so far as I can tell and some doing a terrible job, or whether the bimodal distribution is happening within classes also. I suspect clustering by school is more prevalent. The bimodal distribution of scores was there in 2011, 2012, and 2013 also, so is not a new phenomenon. Calculus BC sees a similar bimodal distribution in past years—the 2014 distribution is not available yet.
Great interview with Sebastian Thrun. I particularly found fascinating his candid response to this important question.
That doesn’t sound like democratizing education, if only the affluent can afford the version that works.
I would be careful to say this is not democratizing it. Any alternative path is actually much more expensive. We managed to lower the cost by a factor of ten. Going to the extreme and saying it has to be absolutely free might be a bit premature. I care about making education work. Everything else being equal, I would love to do this at the lowest possible price point. Where we’ve converged is right. You don’t need a college degree anymore. I would be careful with the conclusion that this is the end of democratization. We still have the free model for students. It just doesn’t work as well — it’s just a fact.
Alfred Thompson raises an important question here. I agree with him — we haven’t reached consensus. We also will never have a national CS curriculum in the United States, because we have a distributed education model. It’s a state decision. I do fear that there may be a de facto standard now.
But the bigger concern is at a higher level of abstraction: How should we make curricular decisions in CS (or anywhere else)? I hope that we make our decisions based on empirical evidence. I don’t see that we have the empirical evidence that any of the below classes ought to be the dominant model.
Oh boy are things up in the air in the HS CS curriculum these days. While we have some great advice from the CSTA (CSTA K-12 Computer Science Standards) the implementation of those standards are still left up to individual schools/districts/states. Still it is easy to come to the conclusion from watching social media and some conferences that there is a consensus on a high school Computer Science curriculum. Today I got the following from a friend.
Is it an incorrect read or has a national consensus for CS in HS’s been achieved with a sequence of :
–ECS (Exploring Computer Science) Curriculum
–CS Principles/BJC Curriculum (Beauty and Joy of Computing)
–AP CS (JAVA [for now])
The website https://www.madewithcode.com/ is really nice, with high-quality videos. I like the direction. It’s not clear to me how all the different Google initiatives in CS education integrate. Does MadeWithCode, CS First, their new CS teaching repository, and the CS Fellows program all fit together in a strategic direction?
Made with Code’s mission is anchored by a website where girls can use basic coding technique to make bracelets and other items; Google also will dole out grants to host girl-coding parties at Girl Scouts and Boys and Girls Clubs around the country, as well as fund a range of marketing and other awareness campaigns.The idea is to de-couple coding with dry tech chores, and instead show how the skill is vital to everything from movie-making to helping cure malaria.
Roger Schank (one of the founders of both cognitive science and learning science) declares MOOCs dead (including Georgia Tech’s OMS degree, explicitly), while recommending a shift to Mentored Simulation Experiences. I find his description of MSE’s interesting — I think our ebook work is close to what he’s describing, since we focus on worked examples (as a kind of “mentoring”) and low cognitive-load practice (with lots of feedback).
So, while I am declaring online education dead, because every university is doing it and the market will soon be flooded with crap, I am not declaring the idea of a learning by doing mentored experience dead.
So, I propose a new name, Mentored Simulated Experiences.
The title is right, but the article (linked below) doesn’t really explain what “encouragement” means. We do have an answer to that from our “Georgia Computes!” work. We found that a sense of “belonging” was key to retention in the Computing major, especially for women and under-represented minorities.
More encouragement will be needed to attract girls into the IT profession, according to a BCS survey.
BCS, The Chartered Institute for IT, found that 79% of BCS members believed that the IT profession would benefit from having more women working in it.
Currently, women account for just 15-18% of IT professionals, a figure that has fallen significantly in recent years, said the BCS.
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.
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.
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 a long time before computational thinking.
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.
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.