Archive for October, 2012
A nice piece (with interviews with Barbara Ericson, Jeff Gray, Dan Garcia, and Maureen Biggers) on getting more women into computing. I like that the story reflects current thinking and research on best practices for drawing more women into computing. For example, we used to think that having more female professors was critical to provide role models. But Joanne Cohoon’s work showed us that male professors can motivate women to consider graduate work in computing as well as female professors.
Experts on the gender gap in computer science have increasingly come to believe that a multipronged strategy is needed to close it. The tactics would include the following:
- More-diverse programming activities, to seize the interest of middle-school girls, in the same way that role-playing video games are embraced by boys.
- A revamped introductory course, whether taken in college or as an Advanced Placement course in high school, to provide a broad overview of the real-world applications of computer science.
- Early exposure to research projects during the first year of college. (Ms. Lamm was paired with her mentor, Mr. Gray, during her first month at Alabama.)
- Opportunities for undergraduates to interact with women who have enjoyed successful careers in technology.
An interesting piece, which argues that proficiency with computing is an important part of a modern liberal arts education. The argument is a modern and updated version of the argument that Alan Perlis made back in 1961. The specific computing literacies being described go beyond computational thinking — it’s explicitly about being able to make with computing. Steve Jobs’ made a similar famous claim that computer science is a liberal art.
Students who graduate with a degree in liberal arts should understand the basic canon of our civilization as well as their place in the world, sure, but they also need to understand how to explore and communicate their ideas through visual communication, data manipulation, and even making a website or native mobile app. If they can’t, they’ll just understand the global context of their own unemployment.
The American Association for the Advancement of Science (AAAS — the organization that publishes Science) sponsors a Science and Technology Policy Fellows program that places scientists and engineers into positions in the US government. The idea is to get more people who know science and engineering involved in public policy. In general, few of these fellows come from computer science and engineering, which is a real shame since an increasing amount of science and technology policy involves issues around computing.
I got a chance to chat with Becky Bates who was a AAS Science and Technology Policy Fellow last year, placed in the National Science Foundation (NSF). She told me, “I really care about the issue of policy, and the issue of how scientists and engineers interact with government.” She wanted to get involved because she saw that better understanding of science could inform policy, and that policy impacts what we do as scientists and engineers.
The program requires either a PhD in science or engineering or an MS in an engineering discipline plus eight years of experience. Many Fellows are placed at NSF, but there are also Fellows at NOAA, NASA, NIH, the State Department, Department of Defense, US AID, and other executive branch agencies as well as in various offices in Congress. Congressional Fellows are sponsored by professional societies (IEEE sponsors fellows, but ACM does not). What AAAS provides is matching, training, orientation, and coordination between all parties.
Becky’s degrees are in engineering, but she has worked as a CS professor for the last 10 years at Minnesota State University Mankato. She did the fellowship as a “not-quite sabbatical year.” It’s a fully-funded year, including travel money. Many of the fellows treat it as a kind of post-doc. Post-doctoral study years are still uncommon in computer science and engineering, so the fellowship doesn’t have a lot of visibility in computing.
She saw the fellowship as professional development and networking opportunities for her, and the government agencies appreciate having experts in science and engineering available. Fellows inform policy and help to create policy for issues that they care about. The AAAS-provided professional development goes on throughout the year. “Once a month, we go downtown to the AAAS mothership, to get seminars on cooperation, on working with the press, having ‘crucial conversations,’ on negotiation.”
“The first two weeks were pretty intense orientation. 8am to 5:30 of training for two solid weeks. It’s like a professional masters in two weeks: History of government, how policy happens, how budgets get decided.” That last part was particularly useful to Becky. “We know that money is good, and how it helps us to do what we want to do, but how it gets allocated and distributed is mostly hidden from us. We’re vaguely aware that it happens, and we definitely don’t know what kinds of influences are deciding who gets what.” That’s particularly important for readers of this blog, because how the money is allocated is important for STEM education and for support of research in computer science and engineering.
It’s a long application process, but both easier and shorter than a Fullbright. Written applications are due on December 5, 2012 (applications are now open at http://fellowships.aaas.org). You have to write a couple essays and provide some letters of recommendation. “Most importantly,” says Becky, “think about your interests and how that can connect to areas of fellowships.” Becky applied to Health, Education, and Human Services program area. “I had been doing a lot of educational research, and care about Broadening Participation in Computing. I made a convincing case that I fit into education. I mostly supervise undergraduate researchers doing AI and speech, and I look for connections to community in order to inform student engagement.” Another program is Diplomacy, Security, and Development, which could be a good fit for a computing person interested in information security.
In February, you learn if you are a semi-finalist, and then you have a month to prepare a policy briefing memo on some topic related to your area. Then you have a 30 minute interview in early March, where you present your policy memo to a committee. If you make it through that round, you’re a finalist, which isn’t a guarantee of placement, but many agencies want Fellows. “There’s a fun week, where you go around to different agencies to find the office for you. It’s almost like a residency match — they have to want you, and you have to want them.”
Becky said that producing the policy memo was challenging. She wrote about Race to the Top Funding. “I connected it to my research on connections to community and self-efficacy, presented some brief statistics about the pipeline and what we know works for under-represented students. I also thought about things happening at different levels. If we’re thinking about this at a national level, you can’t just say, ‘I want more faculty doing this in their classrooms.’ You need to go beyond your own classroom. Moving to a national level, who are all the stakeholders? Companies, state and national agencies, industry, etc. Think about what solutions would have an impact. Some things are expensive. But if I could plan partnerships with agencies to highlight things that are already happening, it could have a broader impact.”
She said that it was a great experience that she recommends to others. She finds herself thinking about education as an engineering problem, viewing education challenges from an engineering perspective. “Now, I think about engineering and STEM education. Can we imagine engineers engineering the education system? Modifying it using engineering principles? What would it mean to engineer the whole education system, mapping all the inputs, outputs and transformations, the way that engineers work with the power grid, or a transportation system, or even a very large software project?”
She told me, “Your perspectives get changed. It won’t ever again be as small as it was. I didn’t know how big it could be. I’ll go back to Mankato, but now think about state and federal levels. And think about how things I do at my university make an impact at multiple levels.”
Great news that the UK is putting up cash incentives to draw in CS teachers! This move addresses the biggest concern that I have for the CS10K project — where are we going to get the teachers? What will motivate them to study CS? A cash reward would certainly help.
Isn’t it a little surprising that Facebook, Microsoft, and IBM are being asked to design the training for the new teachers? Why them? Because they have so much experience training teachers? Or teaching people about CS? They may do a wonderful job. It’s just not an obvious set of choices.
High-flying graduates are to be given a £20,000 golden handshake to train as computer science teachers.
Ministers have asked Facebook, Microsoft and IBM to help design the training for the new teachers.
Education Secretary Michael Gove said current information and communications technology (ICT) teacher training courses would be axed from next year.
The move “could not be more welcome or more necessary”, said Prof Steve Furber of the Royal Society.
This week’s Time magazine piece on MOOCs is very good. The author was fair and even-handed in identifying strengths and weaknesses both of the current models of higher-education and of MOOCs. I was surprised by the sidebar on the results of a survey by Time and the Carnegie Corporation.
They reported that 68% of the general population believe that “Much of the teaching on college campuses can be replaced by online classes.” (Only 22% of the senior college administrators surveyed agreed with that statement.). 52% of the general population agree that “Students will not learn as much in online courses as they will in traditional courses.” (45% of college leaders agreed.). So the majority believes that courses will go online, and students won’t learn as much. This sounds like evidence for the argument made a while back that quality isn’t really a critical variable in decision-making about higher education. Completion rates and cost are two of the most critical variables in the Time piece.
The article says the economic burden of higher education is so great now, something has to change.
I was optimistic after reading the Time coverage — MOOCs could lead to positive changes in all of higher education. If MOOC completion is going to be accredited, it will have to be tested. If face-to-face colleges are going to demonstrate that they have greater value, they will want to show that they lead to testable performance, at least as good as MOOCs. The demand for better tests might lead to education research to develop more and better assessment methods. Actually measuring learning in higher education classes could be a real step forward, in terms of providing motivation to improve learning against those assessments — for both MOOCs and for face-to-face classes.
IEEE Computer Society and Educational Activities Board has launched a new website to help students understand computing and what university and career options are out there. There are also teacher resources, with alignment to various curriculum standards. Liz Burd championed the creation of the site, and its her vision and energy that made the site possible. There’s a page of interviews with career professionals, to give students concrete examples of what computing professionals do, including a couple former Georgia Tech students.
IEEE TryComputing.org is a free online pre-university computing education web site. IEEE TryComputing.org offers resources to inform and engage pre-university students, their teachers, school counselors and parents about computing and associated careers. Visitors can learn how to prepare for undergraduate computing studies and search for accredited computing degree programs around the world. They can also explore how computing careers can make a difference and meet computing professionals, students, and heroes. IEEE TryComputing.org features a variety of lesson plans on computing topics as well as tools and opportunities to support and encourage students in computing.
IEEE TryComputing.org is brought to you by the IEEE Computer Society and IEEE Educational Activities Board with funding from the IEEE New Initiatives Committee.
Holy cow! Most CS faculty that I know haven’t seen raises since the Great Recession hit. A 2.5% increase in a single year for software engineers is a pretty dramatic rise in comparison. How can we possibly keep people teaching when their knowledge is worth so much more in the marketplace?
In line with Economics 101, that increased demand for software engineers means increasing salaries. The national average for a software engineer’s base salary is currently $92,648, according to Glassdoor, marking an increase of 2.5 percent compared to 2011. But depending on where you work — both in terms of your employer and your geographical location — you could be take home more than $100,000 per year. Then again, even if you work for one of the major tech companies, your base salary may fall below the national average.
Where are the plum jobs these days for software engineers? According to recent data from Glassdoor, Google currently offers the highest average salary among 15 major tech companies at $128,336 per year. Ranked second is Facebook, which pays its software engineers an average of $123,626 per year. (Glassdoor came up with these figures based on at least 20 salary reports per company from October 2011 through October of this year.)
Sounds like a response to “Rising about the Gathering Storm” but with a particular focus on STEM education, and even CS education.
The United States faces a growing economic challenge – a substantial and increasing shortage of individuals with the skills needed to fill the new jobs the private sector is creating. Throughout the nation and in a wide range of industries, there is an urgent demand for workers trained in the STEM fields — science, technology, engineering and mathematics — yet there are not enough people with the necessary skills to meet that demand. Our nation faces the paradox of a crisis in unemployment at the same time that many companies cannot fill the jobs they have to offer. In addition to the short-term consequences for businesses and individuals, we risk these jobs migrating from the U.S., creating even bigger challenges for our long-term competitiveness and economic growth.
As an employer, we see these challenges first hand and are committed to doing what we can to help. One way we can help is to shine a light on these challenges and offer ideas and solutions. That’s why today we published a detailed whitepaper documenting ideas for a National Talent Strategy that would help secure U.S. competitiveness and economic growth. I also had the opportunity to discuss these ideas in a speech at the Brookings Institution today.
A fascinating analysis of MOOCs that takes the long-term view: That distance education isn’t new, and has been very hard to get right. I always find useful these historical analogies, to educational “technologies” of the past. (Trivia side point: What was the most quickly adopted educational “technology”? Larry Cuban has claimed that it’s the chalkboard, which “democratized education” since everyone could see what the teacher was writing.)
The MOOC advocates’ belief in “big data” may win out, and it’s certainly different than the postal service model of a hundred years ago. I do agree with Burke’s point (quoted below). Human learning is hard, and researchers have been trying to use “big data” to address the problems for awhile. Using big data to inform education may be harder than the MOOC advocates believe.
A hundred years ago, higher education seemed on the verge of a technological revolution. The spread of a powerful new communication network—the modern postal system—had made it possible for universities to distribute their lessons beyond the bounds of their campuses. Anyone with a mailbox could enroll in a class. Frederick Jackson Turner, the famed University of Wisconsin historian, wrote that the “machinery” of distance learning would carry “irrigating streams of education into the arid regions” of the country. Sensing a historic opportunity to reach new students and garner new revenues, schools rushed to set up correspondence divisions. By the 1920s, postal courses had become a full-blown mania. Four times as many people were taking them as were enrolled in all the nation’s colleges and universities combined.
The promoters of MOOCs have a “fairly naïve perception of what the analysis of large data sets allows,” says Timothy Burke, a history professor at Swarthmore College. He contends that distance education has historically fallen short of expectations not for technical reasons but, rather, because of “deep philosophical problems” with the model. He grants that online education may provide efficient training in computer programming and other fields characterized by well-established procedures that can be codified in software. But he argues that the essence of a college education lies in the subtle interplay between students and teachers that cannot be simulated by machines, no matter how sophisticated the programming.
I guess what Agarwal says is true: Just because the first MOOCs have been “particularly challenging” with low completion rates does not mean that a MOOC could not work for “less well-prepared students.” But, it also gives us no reason to believe that they could succeed. Lots of people are hoping that MOOCs will succeed at lower-level classes, at increasing completion rates. Would you invest $5M (of taxpayer money) explicitly to improve completion rates over face-to-face classes, when MOOC’s currently have lower completion rates than face-to-face classes? NSF grants are for far less money, and demand much higher expectations of return (though one might argue that NSF should go after riskier investments). Or maybe the situation in higher education (especially U. Texas) is so dire, that MOOCs are considered a last-chance effort?
But for Anant Agarwal, the president of edX, poor retention in the early courses, which were built to be particularly challenging, does not mean a MOOC aimed at less well-prepared students is doomed to fail.
“That is one of the particular exciting things about the University of Texas coming on board,” said Agarwal in an interview on Monday in Boston, where he had just given the keynote talk at a meeting of the New England Board of Higher Education.
“It is the largest and most diverse system and has a large number of first-generation [students],” he said. “And they and we all see online learning as a way of increasing the success rate. And for that the [low-level, high-enrollment] courses are going to be key.”
And edX is not done with completion-oriented partnerships. Agarwal says edX has received funding from the Bill & Melinda Gates Foundation to develop MOOCs aimed at community college students.
“We’ll be announcing community college partners soon,” he said. “We’ve narrowed it down and have got the final agreements in place.”
I recommend reading the whole sordid story below, of mathematics faculty decrying mathematics education reform efforts because they believe that it’s not rigorous enough. The story is a familiar one to many who have tried to change education to be more engaging or improve retention. I’ve certainly heard similar claims made about Media Computation (e.g., “If students are now passing MediaComp when they used to fail CS, then he must be lowering standards! How else could he be getting students to stay?”).
A thread I found particularly intriguing in this story is the assumption by the critics that peer-review and publication are meaningless. The only source for critique of the math ed reform in question is this one, never-published essay available on a Stanford FTP site. One of the essay’s authors insists that it was peer-reviewed, just never published, because he never found time to make the corrections that he was required to make by the human research board. In other words, it was peer-reviewed, found wanting, and he chose not to revise-and-resubmit. In response to the quote below: Yes, if they couldn’t get it published, that fact does undermine its worth.
This is a rejection of academic standards — by academics!
Ze’ev Wurman, a supporter of Milgram and Bishop, and one who has posted the link to their article elsewhere, said he wasn’t bothered by its never having been published. “She is basically using the fact that it was not published to undermine its worth rather than argue the specific charges leveled there by serious academics,” he said.
When the report “Researching Online Education” (quoted and linked below) was released, a couple people contacted me. “Tell them what’s really going on in collaborative learning! Tell them what we really know from research!” I looked at their report and concluded that the work I’ve done and am most familiar with doesn’t really have much to do with what they’re exploring. I don’t know much about business models in on-line collaborative learning. I do think that some of the work that I did 10-20 years ago in computer-supported collaborative learning (CSCL) is relevant for today’s MOOCs and other on-line learning experiments.
The work led us to a few hypotheses: (1) We’re skeptical a business model that charges for content will work at scale and in the long run. (2) We expect education platforms that offer vertical content and/or specific education experiences will be more successful than horizontal platforms, though we think credentials and careers offer two opportunities for horizontal aggregation. (3) Without credentialing or careers, online education seems aspirational and removed from the day-to-day of many people.
I got started working in CSCL as soon as I got to Georgia Tech in 1993. Janet Kolodner took me under her wing and got me started on several projects developing collaborative learning activities on-line with engineers and architects around campus. Note that this was two years before Mosaic, so we had to build our clients ourselves. We built a system called CaMILE (Collaborative and Multimedia Interactive Learning Environment) mostly in HyperCard, but then moved it to the Web as soon as graphical browsers became available.
Relevant finding #1: With CaMILE, we created a form of collaboration we called “anchored collaboration.” Rather than a wholly separate forum, we could link to a particular thread in a discussion, so that we could (for example) link a homework assignment to a thread for discussion of that assignment. Jennifer Turns and I did an analysis which showed that anchoring collaboration led to longer, on-topic discussions than having a separate forum. It seems to me when I look around at on-line learning forums today, they’re mostly stand-alone — not integrated, not anchored.
Later, we developed the CoWeb or Swiki (which I talked a bit about in a previous post). We had several reasons for moving to Wiki’s. We had noticed with CaMILE that the anchors that were most effective were written by teachers. Would they have been as effective if written by peer students? Wikis gave us the chance to explore that. (Unpublished finding: Nope. The posts by the teacher are always the most interesting, generating the most traffic.) We were also interested in moving away from a strictly threaded model, based on the work in CSILE and the Knowledge Forum on network-based representations that may lead to better student learning. Most of our earliest work with the CoWeb or Swiki was descriptive: Teachers and students were doing all kinds of wonderful things with it, and we simply tried to catalog them. Over those early years, the Swiki evolved rapidly, in response to the needs of teachers and students. Jochen Rick did a nice CSCW paper describing our design process and how the Swiki met the needs of different roles in an educational context.
Relevant finding #2: One of our coolest findings from back then was that collaborative learning could be better than classroom learning at lower cost. Jochen Rick ran this study, in two English classrooms: One doing close-reading on paper, and the another doing the identical activity in a Swiki. We tracked costs down to teacher and student time (e.g., using diary studies). The Swiki-based learning was better and at lower cost. Here’s a paper providing an example of a blended classroom that really did reduce costs and improve learning.
Relevant finding #3: We did CSCL research for a long time (from pre-Web into the early 2000′s), and we started to notice how and where collaboration worked and when it didn’t work. Jochen did another nice paper on the interaction between the culture in the classroom and collaboration. (His dissertation work explored the complicated issues of permissions, privacy, and transparency in personal webpages.) We had one really large project where we worked on cross-disciplinary collaboration between engineers, mathematicians, and computer scientists. It was a disaster. Students had no interest in collaborating, and even accepted failing grades rather than participate in the Swiki. (We called this “non-integrated engineering education.”) Our work completely changed — instead of creating collaborative learning situations, we switched to studying why they didn’t work. These are important results for the MOOCs: Collaboration doesn’t always happen, and making it work sometimes requires changing culture, which is hard to do in an international, multiple-thousands-of-students “classrooms.”
One of the final projects I did in CSCL was with Karen Carroll. We noticed that, in our English class study, there really wasn’t all that much use of the Swiki by each individual. I had done a “dirty secrets” paper years earlier that got a plenary spot in a CSCL conference, showing that use of online collaborative forums, viewed from an individual level, was far too small for learning to occur. Our existing theory on collaborative learning (e.g., Roschelle, 1992) says that learning arises from the dialog between the participants — 0.5 notes/week/student (a fairly regular rate across several studies) is not a dialog. We found a couple of similar papers in the literature that, like our English class study, showed significant learning, but without significant dialog. How is learning occurring? Karen did a really interesting interview study, where she explored all the ways that reading the on-line forum led to learning activities, even if there was no posting. I wanted to follow up on that, to see how common these activities were and if they did explain the learning we were seeing. But then Media Computation came along.
Nice piece with how-to lessons from Barb, based on her Grace Hopper talk.
From advocacy to action. In the previous session I attended at #ghc12, Are we there yet: education & innovation for women & girls?, I heard a clarion call for moving from advocacy to action. In this session, Barbara Ericson, newly minted A. Richard Newton Educator award winner, answers the question – how? First, I think it is interesting that she is a women who did not start out in education, but comes from industry. She also didn’t start out to pursue computing as a career, horses and therefore becoming a veterinarian was her passion. As with many women of my generation, she stumbled unto computer science in college and she also remembers that in the “early days” it was not such a male-dominated field. Somewhere along her journey, she became passionate about addressing the gender equity issues that arose. Barbara is a great role model for the rest of us that are also passionate about this issue and want to take action.
Nice piece from the NYTimes on how humans tutor and how computers might tutor. I liked the insights below (e.g., “challenge a correct answer if the tutor suspects guessing” might be an excellent approach to deal with possible cheating in MOOC’s), but also liked the interview with Ken Koedinger later in the article which suggests a more data-driven and less heuristic approach to making computer tutors even better than human tutors.
So Heffernan forged ahead, cataloging more than two dozen “moves” Lindquist made to help her students learn (“remind the student of steps they have already completed,” “encourage the student to generalize,” “challenge a correct answer if the tutor suspects guessing”). He incorporated many of these tactics into a computerized tutor — called “Ms. Lindquist” — which became the basis of his doctoral dissertation. When he was hired as an assistant professor at Worcester Polytechnic Institute in Massachusetts, Heffernan continued to work on the program, joined in his efforts by Lindquist, now his wife, who also works at W.P.I. Together they improved the tutor, which they renamed ASSISTments (it assists students while generating an assessment of their progress). Seventeen years after Heffernan first set up his video camera, the computerized tutor he designed has been used by more than 100,000 students, in schools all over the country. “I look at this as just a start,” he told me. But, he added confidently, “we are closing the gap with human tutors.”
I predict that we’re going to see more of this: Universities using on-line services to teach computing classes. Discussions with my colleague, Beki Grinter, have given me a new perspective on thinking about the impact of MOOCs and other on-line services.
Here’s what I’m wondering: Who got fired? Was NYU teaching this class previously? What happened to the teacher who used to teach this course? How do the administrators at NYU know that it was unsuccessful? Why do they think that Codeacademy will work better?
How will they know “if all goes well” with the pilot program? I wonder if the answer isn’t already determined. Once you’ve gone from a paid-course to a free-service, how can you possibly NOT decide that “it went well”?
A department at New York University is beginning to use a free online service to help teach computer-programming courses.
The department of media, culture, and communication in NYU’s Steinhardt School of Culture, Education, and Human Development recently announced a partnership with Codeacademy, a free site that started last year and has quickly gained a following in the computer-science field, to provide a 10-week programming course this semester.
Fifty undergraduates will participate in the pilot program, which includes a weekly class and monthly lectures from technology-industry leaders. If all goes well, the course may be incorporated into the department’s curriculum.