Education is already Gamified: Dan Hickey on Badges

This is the most insightful and balanced piece that I’ve yet read about badges, including Nora Sabelli’s spot-on comments at the tail end. The insight from Henry Jenkins, that education is already gamified is important and one I hadn’t really considered. It is already about getting “score,” and beating some relatively arbitrary challenges/bosses in order to gain points. A possible benefit of badges is to expose the current flaws, and possibly create a better model. I’d love to see this in CS, to address the kind of “We covered that in a five line example, so you should be able to build this 75 line program!” assumption that the cartoon about CS textbooks was lampooning. We assume that students learn much more than what our assessments say that they’re learning. But Dan and Nora point out that it only gets better if we can measure what we really think is important, and it’s still not obvious that we can.

In particular, I agree with Henry’s argument that education is already “gamified”. So the answer to Mike’s question about what badges promise is really another question: Compared to what? Given the trivial amount of learning supported by many current formal and informal educational contexts, ANY attention to learning outcomes might be an improvement. Introducing digital badges is sure to change most learning ecosystems. On the upside, the incentive value of digital badges is likely to draw attention to dubious credentialing practices and lousy assessments. While stakeholders who have a vested interest in the existing ecosystem are likely to blame the badges, most will agree that such attention is needed and generally helpful.

Certainly some of the changes that follow from digital badges will be bad. In particular, I worry about the fetishistic obsession with test-driven educational reform expanding to badges. I believe the policy researchers who argue that overconfidence in test-driven reform undermined achievement in many schools that were already high-achieving before No Child Left Behind. I worry that the same thing may happen as well-meaning administrators and governing boards insist that high-functioning schools and programs incorporate digital badges.


Deepa Singh
Business Developer
Web Site:-http://www.gyapti.com
Blog:- http://gyapti.blogspot.com
Email Id:-deepa.singh@soarlogic.com

Why CS graduates don’t teach, but it’s not inherent to CS

I mentioned that a UK survey of CS graduates found that fewer of them went into teaching than did other kinds of graduates. The below blog piece tries to explain why that’s a case, and generally suggests that it’s not because of money. In other countries, CS graduates do teach, e.g., Israeli CS teachers get a CS degree, first. The problem is likely cultural to the region, not inherent to the discipline. It is a real concern that computer scientists are not getting involved much in creating more high school teachers — computer scientists are not going to be happy with the result if we don’t participate and influence the preparation of the teachers and the definition of the curriculum.

I found that the Computer Science graduates from my course fitted into one of two categories. They either chose CS because they thought it could make them a lot of money, or because they were a bit of a geek and they were into that kind of thing. The first group are lost already – you don’t earn anywhere near as much in teaching as you potentially could do in industry. The other group by their very nature are usually not particularly comfortable with social situations, and may find it their idea of hell to stand up in front of lots of people, let alone do it every day as a job. I’m not saying everyone shuffled around staring at the floor wearing 2 week old clothes and grunting for social interaction, but putting oneself on show in such a manner as teaching demands is not usually within a geek’s comfort zone – unless of course the room is filled with other geeks, which at school it definitely isn’t.

Deepa Singh

Business Developer

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Blog:- http://gyapti.blogspot.com

Email Id:-deepa.singh@soarlogic.com

Does learning occur differently with physical or digital print?

I’m skeptical about this claim: That your brain interprets text in books differently than text in digital form. One argument in support of the claim is an observation (not much data) that we have to re-read digital information more often than print information before we remember it, but doesn't offer a theory for why that should be true. I find this second claim a bit more plausible: That our memories rely on contextual information, and physical books provide us more cues to support recalling what we read. I wonder, though, if we might not be able to provide more contextual cues through the interface. I've started reading the “Our Choice” app on my iPad, and there are lots of cues in that book to provide a sense of “place” (what page you’re on, what pages are around you, what chapter you’re in).

But without stronger evidence that there is a difference, I’m going to keep reading on my iPad and Kindle (well, once I get a new Kindle — my Kindle’s screen died somewhere during my trip to Venice this last weekend). In other words, the human brain uses location to recall the words it reads, which helps reinforce the information. To trigger a memory, the brain might recall whether it read the information at the top, middle, or bottom of the page, remember a corresponding picture on the page, or even a page number — essentially creating a mental bookmark to cue recall of the information. “Anyone who has read an e-book can attest that the page provides fewer spatial landmarks than print,” Changing continues. “In a sense, the page is scrolled without incident, infinite and limitless, which can be dizzying. On the other hand, printed books give physical reference points, which can be particularly helpful in recalling how far along in the book we are, something that’s more challenging to assess on an e-book.”

Deepa Singh

Business Developer

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Blog:- http://gyapti.blogspot.com

Email Id:-deepa.singh@soarlogic.com

How do faculty learn about and use Peer Instruction?

How do teaching innovations spread among faculty? I am exploring this research question as a sociology doctoral student at Johns Hopkins University. I am working with several faculty, including Dr. Eric Maura  to examine the diffusion patterns of the teaching methods they pioneered as part of my dissertation project. Would you be willing to participate in my dissertation study by completing a short survey? http://www.zoomerang.com/Survey/WEB22FTWGYJJDQ I’m interested in your response even if you are not an instructor or don’t use Peer Instruction in your class. As a sociologist, I’m exploring how information about Peer Instruction spreads, not how instructors use it. “Don’t remember” and “Don’t Use” are valid responses on several questions.

The survey can be completed in as little as 7 minutes with only 2 open-response questions in addition to several multiple choice/rating questions. All participants will be entered into a raffle for one of eight $25 Amazon.com gift cards or a $100 gift card. No sensitive personal information will be asked beyond your role and colleges at which you have taught/worked. All data will be kept strictly confidential and will not be publicly shared. Any publications or presentations resulting from this research will only include aggregate summaries or anonymous quotes. To ensure timely analysis of the data, I am asking all participants to complete the survey by Friday, July 20th. I know your time is valuable—thank you for your help with this research. Please don’t hesitate to contact me with any questions.Sincerely.

Deepa Singh

Business Developer

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Blog:- http://gyapti.blogspot.com

Email Id:-deepa.singh@soarlogic.com

A Report on Worked Examples and Self-Explanations in Media Computation

I should give you a little report on how my worked examples/self-explanation intervention worked in my Media Computation class. I have nothing close to real data, and you shouldn't believe me if I offered any. This is a ratified class: 22 students, meeting four days a week for 90 minutes, plus office hours for 90 minutes twice each week (that most of the students have come to), and the teacher (who is the author of the textbook) attends breakfast and dinner with the students. I think it would be hard to get more student-teacher interaction than in this model.

That said, I would definitely do it again. I was quite surprised at how seriously the students took the task of explaining these programs! In retrospect, I shouldn’t have been surprised. In most classes, aren’t students asked to analyze and explain situations, even asked to make sense of some text? That’s exactly what I asked these students to do, and they really worked at it. I had students coming to office hours to ask about their assigned programs, so that they could write up their one paragraph of explanation. There were things that I had to teach them about this process, e.g., teaching them to try a program with different data sets, to make sure that the odd result they got wasn’t an anomaly. I gave them feedback (every single student, on every single program) about the quality of their explanations, and the explanations definitely got better over time.

The real benefit was that they were trying to understand some relatively complicated code before it was their own code that they were trying to understand (while also designing and debugging it, all before a deadline). With the worked examples tasks, they were just trying to understand. There clearly was a reduction in cognitive load. Variations on the below program had lots of students coming to see me — combining sounds at different rates was a challenging idea, but students did a good job of getting a grasp on it:def modifysound2(sound): retsound = makeEmptySound(2*getLength(sound)) newsound = makeSound(getMediaPath("bassoon-c4.wav")) trgi = 0 nsi = 0 for i in range(getLength(sound)): value = getSampleValueAt(sound,i) if nsi < getLength(newsound): nsvalue = getSampleValueAt(newsound,int(nsi)) else: nsvalue = 0 setSampleValueAt(retsound,trgi,value+nsvalue) trgi = trgi + 1 nsi = nsi + 0.5 return resound

Because there four labs (that just involved explaining programs) and two homework’s (that involved typing in, executing, and explaining programs), the first real programming assignment was the collage assignment. Everybody did it. Everybody turned in a working program. And some of these were huge. This one (by Savannah Andersen) was over 100 lines of code:

This one, by Julianne Burch, is over 200 lines of code. I’m posting shrunk versions here: Julianne’s is about 4000 pixels across, representing the travel portion of this study abroad program.

I suspect that the worked examples and self-explanations gave the students more confidence than they normally have when facing their first programs. It’s unusual in my experience for students to be willing to write 50-200 lines of working code for their first programming assignment.

 But some of these students were also getting it. A few of my students realized that they could make their collages more easily by using a copy() method to reduce the complication of composing pictures. I did prompt them to do that, and a few did — most just went with hard-coded FOR loops, because that was easier for them to understand. When I described how to do that, one student asked, “ Aren't you just naming some of those lines of code?” Yes! Nice way to start thinking about functions and abstract: it’s about naming chunks of code. One of my students,without prompting, also decided to create a copy() method for her sound collage. They’re starting to grapple with abstraction. Given that this is the third week of class, when none of them had any previous programming experience (all my students are liberal arts and management students), I think that they’re doing quite well at moving from notation into abstraction. They’re working on their first midterm exam now, a take-home exam (to save classroom time.) I think it’s significantly challenging for a first exam, but it doesn't have much coding. It has a lot of analysis of code, because that’s one of the key learning objectives. I want them to be able to look at a piece of code and predict its behavior, to trace (if necessary) what’s going on. For me, that’s a more important outcome from a first course than being able to write a lot of code.

Deepa Singh

Business Developer

Web Site:-http://www.gyapti.com

Blog:- http://gyapti.blogspot.com

Email Id:-deepa.singh@soarlogic.com

What would Constitute Evidence that Open Education is helping a Global Economy?

Another piece, this time in the NYTimes, makes the claim that open education will have vast impacts on the global economy, especially in the developing world. Set aside that it’s very hard for any education interventions or reform to have economic impacts, it’s clear that any education effort has to be broad and touch many people to have an economic impact. Daphne Koller makes a comment in the Chronicleabout Coursera “changing the lives of millions of people.” Does it? Will it? Do we have any evidence than any on-line site does? Notice that ALISON (an Irish system described in this piece) admits that the bulk of its learners are in the developed world. There are developing-world users of MIT OpenCourseware, but not a large percentage and those users are mostly just getting a piece of information, not doing long-term studying (as best we can tell from the usage statistics). The results on the new MITx course are just out, and they’re mostly serving US, India, and UK, with 7K students finishing.

What kind of usage would lead us to believe that an open education site is having an impact on the global economy? I completely believe that open education has the potential to have a huge impact. The question is: is it? What measure are we hoping to achieve that would indicate that we’re on the right track? If we didn’t achieve that standard, how do we need to change/improve the model so that it did?

I don’t need job stats or improvements in GDP to be convinced that open education is reaching that impact. Let’s consider the statistics given below. We have a worldwide shortage of 40 million college students, the article says, and it’s probably a much greater shortage in the developing world (e.g., if you count available job openings, you’re not going to count jobs that don’t yet exist but might if there was a dramatic improvement in education and entrepreneurship). How about if one of these sites had 1 million students (which still means it’ll take 40 years to address the shortage), in the developing world, each of which visit the site more than four times in a month, spends more than 3 hours on-line, and actually posts something (homework, feedback to peer students) at least once a week? That feels like a minimum to indicate real studying at a scale great enough to potentially have an impact. Can we find those kinds of statistics for any of the sites? Perhaps for allof the open education sites summed together? At 100K students per course, it’s conceivable that we could reach that goal — if the students stuck around.

If we’re not seeing that, is there something wrong with our models? Maybe there are other factors that we’re not yet identifying that prohibiting open education from having the broad reach that could result in an impact on the global economy. This is good news for everyone, but it is particularly good for the vast number of people around the world whose job prospects are constrained by their skill levels and who lack the resources to upgrade them through conventional training. It’s a problem that a company based in Ireland called ALISON — Advanced Learning Interactive Systems Online — is helping to address with a creative model.

ALISON provides free online interactive education to help people acquire basic workplace skills. It’s not a megasite. It has a million registered learners, the bulk of whom live in the United States, the United Kingdom, India, Malaysia, the Philippines, Nigeria and the Middle East, where ALISON has 200,000 students. It is adding 50,000 learners each month, but the kinds of services it offers are likely to proliferate in the coming years. To understand why, we only have to think back to last week, when the big news was the release of the June jobs report, which found that the unemployment rate had stalled disappointingly at 8.2 percent. As always, the story behind that number is more noteworthy than the political spin it gets. According to the Department of Labor, the unemployment rate for people in “management, business and financial operations” is nowhere near 8.2 percent; it’s only 3.8 percent. For workers in “installation, maintenance and repair,” it’s 5.3 percent. It’s workers in certain occupations — like “transportation and material moving” (10.3 percent unemployment) and “construction and extraction” (13 percent) — who are experiencing the most severe economic pain.

That’s because the skills of many workers are increasingly out of sync with the demands of the job market, and the gap is likely to grow, particularly given that only a minority of companies provide formal training to employees. This isn’t just an American problem, however. There are 200 million unemployed people around the world, 75 million of whom are youths, and many lack rudimentary workplace skills — the ability to use a computer, make a budget, communicate in an office environment. According to a study published last month by the McKinsey Global Institute, by 2020, the world will have a surplus of up to 95 million low-skill workers and a shortage of up to 40 million college graduates.

Deepa Singh
Business Developer
Web Site:-http://www.gyapti.com
Blog:- http://gyapti.blogspot.com
Email Id:-deepa.singh@soarlogic.com

Why the Internet Isn’t Going to End College As We Know It

What an interesting argument in this piece from the Atlantic. As we mentioned previously, Internet technologies cut into older markets if they impact the revenue stream. So far, MOOCs are not impacting the revenue stream. This article goes further to point out that even the for-profits aren’t generating the quality to be much of an impact on traditional universities. Maybe quality doesn’t matter all that much in higher education (as discussed previously), but it does matter if the sense of quality (or lack thereof) impacts success in the job marketplace. If the for-profit’s can’t compete with the non-profits in terms of getting jobs, and they can’t touch the non-profits revenue streams, then there really isn’t much threat from for-profits or MOOCs.

New innovations don’t disrupt old industries by merely competing with them. They do it by cutting into their source of revenue. The music industry ignored the Internet, tried to sue it out of existence, and then let Apple effectively monopolize digital music sales, which gave Steve Jobs the power to set prices at 99 cents a song. Journalism saw its ad dollars whittled away by the profusion of online media outlets and Craigslist. As George Washington University’s David Karpf has noted, if the Internet is to conquer higher education, it needs to hit colleges in the pocket book. And so far, there’s no sign of that happening.

The simple truth is that nobody has figured out how to build a cheap, high-quality online university. Not even close. So far, the biggest investments in Internet education have come from the for-profit sector, and their results have been, to put it lightly, lacking. For-profit graduates have worse job prospects and earn less than their peers who attend nonprofit schools. A new study released this week suggests that many for-profit diplomas are literally worthless in the marketplace. This even holds true when you control for student characteristics like wealth. And so perhaps not surprisingly, their alums are responsible a disproportionate fraction of student loan defaults.

Deepa Singh

Business Developer

Web Site:-http://www.gyapti.com

Blog:- http://gyapti.blogspot.com

Email Id:-deepa.singh@soarlogic.com

Yum, Tasty Seed Corn: Where will we find the teachers?

The Snowbird Report and the NSF-ED report both make the point that the working environment may not be able to sustain quality: Lab and computing facilities are not being upgraded or expanded to meet the demand; salaries and graduate student stipends are unattractive; faculties have not grown; heavy time commitments to large classes and counseling destroy the intellectual atmosphere and deprive graduate students of proper supervision…On the other hand, there is in Congress sentiment that ‘all the universities must do is raise faculty salaries,’ and the problem will go away.”

No, that’s not from a follow-up to the below article. It’s a quote from Peter Denning’s 1981 Letter to the ACM, “Eating our Seed Corn.” Eric Roberts warned last year that we were going to end up in the same place as we were in the early 80′s (when Peter wrote the above words) and in the early 2000′s (during the dot-com boom). According to US News and World Report, we’re getting there — the flow of students, in a time of cutbacks at Universities, is going to hinder our ability to meet demand, and the relentless draw of industry with its higher salaries is going to make it harder to find faculty.

At some institutions, the computer science program faces a shortage of qualified computer science faculty to meet student demand, notes Gwen Walton, a professor of computer science at Florida Southern College. Walton, who spent more than 20 years working in the industry, says schools cannot compete with the salaries many professionals command in the job market. “Computer science is one of the few fields where you can start with a very high-paying salary with only a [bachelor's degree],” Walton says. “You don’t go into [teaching computer science] for the pay.”

Deepa Singh

Business Developer

Web Site:-http://www.gyapti.com

Blog:- http://gyapti.blogspot.com

Email Id:-deepa.singh@soarlogic.com

Larry Cuban on “The technology mistake”: Confusing access to information with becoming educated

Historian Larry Cuban has a great perspective on the role of technology in learning. His book on “How Scholars Trumped Teachers” is one of my favorites on the history of higher education in the United States. Here is his take on what’snot working, and what is. This was essentially the point that Woodies Flowers was making at the ACM Education Council meeting — new online courses are great for training (getting access to information), and that may be what much of the first two years of undergraduate are about, but real education is more than that, and online courses are probably not enough. I found an interesting piece by Milton Fried man that talks similarly, about the citizenship role of education and the need for the government to support that.

What technology enthusiasts, however, forget, neglect, stumble over — pick a verb — are the multiple purposes of tax-supported schools in a democracy. They and many others futurists err — my choice of the verb — in equating access to information with becoming educated. Even worse, these very smart people ignore the crucial and historical purposes public schools have served in a democracy. Tax-supported public schools have been and are social, political, and moral institutions whose job is to help children and youth acquire multiple literalness  enter the labor market well prepared, vote, serve on juries, contribute to their communities, think for themselves, and live full and worthwhile lives.

Deepa Singh

Business Developer

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Blog:- http://gyapti.blogspot.com

Email Id:-deepa.singh@soarlogic.com

Pixel Spreadsheet in a Media Computation class: Exposing data abstraction with Excel

I mentioned awhile ago that some undergraduates built for me a new tool for converting from images to spreadsheets, and back again. It allows us to do image manipulations via spreadsheet tools like Excel. More importantly, it exposes the data abstractions in picture files (turning JPEGs into columns of x,y and RGB), and makes the lower level data malleable. I’m using this tool in the Media Computation course that I’m teaching this summer. Normally, CS1315 (the course I’m teaching) includes labs on Word, Excel, and Powerpoint, but there’s no sense of “lab” in these compressed courses. And I bet that most of my students know a lot about Office applications already. So I asked them at the start of class: What did they want to learn about Office applications? Several students said that they’d like to learn to use formulas in interesting ways in Excel.

I’ve come up with a homework assignment where students do Media Computation using unusual Excel formulas (e.g., using IF, AND, and COUNTIF). I lectured on Excel on Thursday in support of this assignment, and it was rough. Things that I had worked out in Windows Excel failed or worked differently when doing a live coding session in MacOS Excel (e.g., the FREQUENCY function worked differently, or not at all — hard to tell). Fortunately, we figured it out, but I got a new appreciation of how non-portable the edge of Excel functions can be.

My students are working on this assignment this week, and I’ll let you know how it goes. Based on the questions I’m getting already, it’s challenging for the students. Excel functions are hidden, invisible when you look at a spreadsheet until you click on the right cell. Much of how you do things in Excel, the process, is invisible from watching the screen, e.g., shift-clicking to select a range. So, they’re having a hard time discerning exactly how I did what I did in class.

Deepa Singh

Business Developer

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Email Id:-deepa.singh@soarlogic.com

Science Education Research: Misconceptions are suppressed, not supplanted

Very interesting report from Neil Brown. Here’s the question I’d like to know: So what are students intuitions about computing as they enter the classroom? Are they suppressed or supplanted through instruction? My guess is that it’s different for computing than for science. We live our lives for many years, 24 hours a day, in the real world before we enter school. That’s a lot of time to invent science hypotheses about the world. Not so much for computing. While we may increasing live our lives in a computing world, it’s a constructed, designed world — a world in which the computer science is explicitly hidden. I bet that students only make up theories about computing in times of break down, when they have to invent a theory to explain what went wrong. How often does that happen? What theories do they develop?

The paper title here says it all: Scientific knowledge suppresses but does not supplant earlier intuitions. A consistent theme across the research described in this post is that when you are explaining science to pupils, you are not adding totally new knowledge, in the way that you might when explaining a lesser-known historical event. When you explain forces to someone, they will already have an idea about the way the world works (drop something, and it falls to the ground), so you are trying to adjust and correct their existing understanding (falling is actually due to gravity), not start from scratch. The paper suggests that the old knowledge is generally not replaced, but merely suppressed, meaning people carry their original misconceptions with them forever-after.

Deepa Singh

Business Developer

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Email Id:-deepa.singh@soarlogic.com

Universities on the Defensive: What is it we do

Ian Bogosity piece (linked below) on Georgia Tech’s involvement in Courser is biting and to-the-point. ”The fundamental problem isn't one of cost containment, it’s one of funding—of understanding why the cost containment solution appeared in the first place. We collectively ‘decided’ not to fund education in America. ” Why is Georgia Tech doing Courser? Why are any of the other schools doing this? He argues that nobody knows, that everybody is doing this because they are trying to position themselves as a member of the elite, as being in the lead. It’s a defensive posture.

Are Universities under attack? DE-funding is a form of attack. Why do we have universities, then? What do Universities exist for? Why did we collectively decide not to fund education? Maybe decision makers don’t understand what we do. And the question at hand: do MOOCs replace what we do? I've been thinking about this, while living at one of the world’s oldest and most influential universities. Teaching is not all that they do at Oxford, though I do think that they are particularly good at real education and not just imparting knowledge. The issues of what Universities are for were raised at the C21U launch almost a year ago.Educating students is only part of what Universities do (and there is some question about whether MOOCs education or simply train). But when it comes to education, a research university can provide a unique learning experience.

I love teaching at Georgia Tech’s Study Abroad program at Oxford. The location is amazing, but that isn't the greatest value of the experience for me–and I hope not for the students. I love the opportunity to interact with students intensively (in class, at meals, on the street, and even in the pubs), to spend every day in the classroom, and to grade everything myself and get a sense for how everyone is doing. All of us GT faculty are here to teach. There’s a community of scholars. I meet weekly for dinner (and often over breakfast) and conversation with a group of similarly minded GT faculty who really care about teaching and students. For me, the experience informs my research. The intensive interaction with a small number of students is my opportunity to try out new ideas (like worked examples with self-explanations and pixels in a spreadsheet) and inform my intuition about whether or not they might work. It’s the first stage of design-based research: I’m trying to make something work, with small numbers, when I can really see what’s going on. This is more than teaching for me — it’s an intense, immersible, research-informing experience.

I believe that the students are getting something unique out of this, too. Excuse me for being immodest here: This is what I’m good at, and what I’m trained for. This is why I’m a professor. I’m a good teacher, but I also have decades of experience as an education researcher. My students know that I’m trying new ideas out with them. I tell them (in both of my courses) about what I’m trying and why I’m trying it and about my research agenda. Even those students who are “just” taking a first-year-level intro to computing course are hearing about the research context and how it informs what we’re doing. My colleagues who do not do education research also wrap their courses with their research context. Every course is infused with the passion of a scholar who talks about what they study and why they think it’s amazing and fascinating.

This is education that a University can offer, uniquely. My students are learning knowledge and skills and perspectives, in a rich and intense and personal experience. It doesn't always work so well, I admit. I can’t do the kinds of things I do here at Oxford in our enormous courses in Atlanta. And this kind of education isn't for everybody. Turgid told us that we need a variety of learning systems for a variety of needs. I definitely have students who are going through the paces and aren't interested in taking advantage of the whole experience. I’m damn sure that there is no MOOC that can replace what is going on in my classrooms this summer. Now, society can decide that what I’m offering isn't worthwhile, or is too expensive, or can be offered to too few students, or may even not as work as well as I hope. Maybe that’s the real danger of MOOCs — it offers something for free (to the students) that seems as good as what a good University education could be, or as good an education as members of our society need. Maybe what we in Universities ought to do is show people more often what it is that we do and explain why. We need to be able to show people why what we’re offering in a University is better than a MOOC and is valuable to the greater society.

Institutions like mine are afraid of the present and the future yet drunk on the dream of being “elite” and willing to do anything to be seen in the right crowd making the hip choices. The providential email also notes, “It also is significant that Georgia Tech is a founding member of this group.” Group membership is a key obsession of university administration, and it’s why they take systems like the US News rankings so seriously. Of course, all such structures are partly fictions we invent to structure our lives and society. The Ivy League isn't a natural law or a God-given lineage. In this respect, Coursera’s clearly got the upper hand among institutions that fancy themselves elite: once they get a critical mass on board, the rest don’t want to appear left behind. Given the recent drama at the University of Virginia, whose president was fired partly for failing to blindly adopt online learning only to be re-hired after a PR-nightmare only weeks before UVA announced their participation in Coursers anyway, you can see how Presidents and Provosts across the land might be ready to sign on for defensive reasons alone.

Deepa Singh

Business Developer

Web Site:-http://www.gyapti.com

Blog:- http://gyapti.blogspot.com

Email Id:-deepa.singh@soarlogic.com

Who funded the Internet? I care that you don’t know what it is!

I’m not really that upset or surprised over the argument that the government did (or did not) fund the Internet. I do realize that it really matters, but it’s a complex issue. The Internet was most successful because of a government and business partnership, which means that there’s always going to be a question of who did what. As a computing educator, I am more concerned that the article in the Wall Street Journal was so full of conceptual errors! Hyperlinks have nothing to do with the Internet. Ethernet is not the Internet. As my colleague Christine Alvarado said to me on Facebook, the WSJ piece is a symptom of a problem that even educated Americans do not understand the computing in our daily lives.

Cronkite then points out that TCP/IP, the fundamental communications protocol of the Internet, was invented by Vinson Cerf (though he fails to mention Cerf’s partner, Robert Khan . He points out that Tim Berbers Lee “gets credit for hyperlinks.” Lots of problems here. Cerf and Khan did develop TCP/IP–on a government contract! And Berbers Lee doesn't get credit for hyperlinks–that belongs to Doug Enlargeable of Stanford Research Institute, who showed them off in a legendary 1968 demo you can see here. Burners Lee invented the World Wide Web–and he did so at CERN, a European government consortium.

Cerf, by the way, wrote in 2009 that the ARPANet, on which he worked, “led, ultimately, to the Internet.” As for Ethernet, which Bob Metacafe and David Bogs invented at PARC (under Taylor’s watchful eye), that’s by no means a precursor of the Internet, as Cronkite contends. It was, and is, a protocol for interconnecting computers and linking them to outside networks–such as the Internet. And Metacafe drew his inspiration for the technology from ALOHANet, an ARPA-funded project at the University of Hawaii.

Deepa Singh

Business Developer

Web Site:-http://www.gyapti.com

Blog:- http://gyapti.blogspot.com

Email Id:-deepa.singh@soarlogic.com

Educational Kit from CMU Can Turn Artwork and Crafts Into Robots

In our summer camps, two of the most popular activities have been Scratch and Pict Crickets. Unfortunately, the company has been bought out by Lego and is being dismantled in favor of their We Do, which isn’t anywhere close to the same thing. I’m excited about Hummingbird — I hope that it captures some of the Pict Crickets excitement. While educational robotic kits traditionally have focused on the technology itself — the building of a robot — Hummingbird treats robotics as just one element that can be combined with craft materials and text to communicate thoughts, feelings or ideas.

“We want students to become inventors of technology rather than users of technology,” said Robotics Professor Illah Bourbaki  whose CREATE Lab developed Hummingbird for a project called Arts & Bots. “Hummingbird feeds a student’s natural curiosity about technology by enabling her to incorporate robotics into something she is making that is meaningful or useful.” The results often amount to kinetic sculptures that use sensors to detect changes in their environment and respond with movement and/or light displays. A cardboard dragon that turns its head and tries to bite anyone who comes close is one example. Students in West Virginia built a working replica of Star Wars’ R2D2.

Deepa Singh

Business Developer

Web Site:-http://www.gyapti.com

Blog:- http://gyapti.blogspot.com

Email Id:-deepa.singh@soarlogic.com

How does higher education funding relate to teaching quality?

We’re in the final week of the Computational Freakonomics course at Oxford, and students are looking for data. Several of my students are diving into the Guardian’s impressive open data journalism site. Helping them look around, I found this interesting article relating funding to teaching quality. The findings are all for UK institutions (comparable to US? Similar issues?). The “teaching scores” are not course-specific, but at the end of the three year undergraduate degree, what did the graduates think of the teaching at the institution? I wonder if the influences are the same as on other course surveys. The graph below was one of the most interesting: Higher funding was related to better teaching and student-to-staff ratios.

In the chart below, we seed how teaching scores relate to the expenditure per student and the student staff ratio and how expenditure per student and student staff ratio relate to each other:

Deepa Singh

Business Developer

Web Site:-http://www.gyapti.com

Blog:- http://gyapti.blogspot.com

Email Id:-deepa.singh@soarlogic.com

What makes for a course that works as a MOOC?

Nice analysis from “Gas station without pumps” on what’s offered via Coursers and why the course offerings are what they are. I particularly liked his wordplay on MOOC: Massively Over-hyped Online Course. He suggests offering a Coursers course soon, because it’s unlikely to be around for long. A lot of the courses that are offered are the “book learning” courses that require no lab facilities, no face-to-face discussions, and no close mentoring. They are the easiest courses to offer, but the ones least likely to save universities much by switching to an online format (those sorts of lecture classes are already relatively cheap per student).

One exception is computer science classes, since the specialized equipment needed for CS courses is now so cheap that just about anyone who can access on-line courses has the necessary equipment already, and much of the software needed for CS courses is available free (often open-source). If grading the courses is reduced to low-quality automatic checking of programs (a travesty that has already happened in some brick-and-mortar CS courses), then there is nothing stopping the scaling of fairly advanced courses to MOOCs.

Deepa Singh

Business Developer

Web Site:-http://www.gyapti.com

Blog:- http://gyapti.blogspot.com

Email Id:-deepa.singh@soarlogic.com

MOOCing an analogy between teachers and John Henry: But maybe it’s students?

I wrote my monthly Blog@CACM piece this last weekend, which was a synthesis of several pieces I wrote here: About the worked examples that I’m trying out in Oxford, the Pixel Spreadsheet, and contrasting the study abroad I’m teaching on and MOOCs. I mention that I’m doing an end-of-term survey about how all this worked, and I expect to say more about those results here in the next couple weeks. In the Blog@CACM piece, I mention an analogy I've been thinking about. (Please forgive the terrible pun in the title.) John Henry is an American folk hero who worked on the railroads “driving steel.” Along comes the steam-powered hammer, which threatened the job of steel-drivers like John Henry. John Henry raced the steam-powered hammer, and beat it — but suffered a heart attack and died immediately afterwards. In some versions of the story, John Henry’s wife or son picks up his hammer and keeps driving steel. But as we all know, the steam-powered hammer did drive the steel-drivers out of a job.

I wonder about the analogy to higher education. The Internet makes information cheaper and easier to access. Teachers play the role of John Henry in this analogy. Sure, they may do a better job than that steam-powered education, but cheap and plentiful is more important than quality, isn't it? Taking the analogy in a different direction, the teachers who are building the new Coursers courses at Universities with no additional pay or course/work release remind me of the John Henry who suffered exhaustion and “died with a hammer in his hand.” Colleagues who went to the Google Faculty Summit came back with stories of how MOOC’s were part of the conversation there. I heard that my adviser, Elliot Solo way, stood up to say: ”I’m at the University of Michigan where in addition to our university we have Central Michigan, Eastern Michigan, Western Michigan, etc. In five years, those schools will be gone.”

That’s when I realized another potential casualty in the battle over MOOCs, if Elliot is right. My niece went to Central Michigan to get a degree in Occupational Therapy. Today, she works with special needs children, with both physical and cognitive impairments. There are only a couple of OT programs in the state of Michigan, and none at U-M. Can you imagine teaching students how to provide therapy to patients with physical impairments via MOOCs?!? (Relates to “Gas Stations Without Pumps” on what works as a Coursers course.) How do we teach everything that we want and need to teach if only elite universities and MOOC’s exist for higher education? Is the role of John Henry in the higher education version of the analogy played by teachers (as in my original blog post), by degree programs that don’t fit these models, or by the students who seek to do something other than what the elites and MOOCs offer? It’s over-the-top melodramatic, I admit, but that’s what makes for good folklore. Folklore and similar stories play a useful purpose if they help us to see new perspectives. In the vision of the world where community colleges don’t survive, who gets wiped out (besides the Colleges themselves) like John Henry?

Deepa Singh

Business Developer

Web Site:-http://www.gyapti.com

Blog:- http://gyapti.blogspot.com

Email Id:-deepa.singh@soarlogic.com

A Professorship in Gender Studies in Computer Science

First time I’ve ever heard of a position like this! How cool! I found it a little weird to say, “and please do research in embedded systems, too,” but any attention is better than none. The Faculty of Engineering at the University of Freiburg, with its Departments of Computer Science and Microsystems Engineering, invites applications for a Junior Professorship (W1) for Gender Studies in Computer Science.

The prospective candidate will represent the area of “Gender Studies in Computer Science”, at the interface between the fields Computer Science and the humanities. Candidates should have earned a PhD in Computer Science or a related discipline and have extensive experience in the areas of gender studies as related to MINT subjects (Mathematics, Informatics, Science and Technology). Relevant research areas include e.g. gender aspects and didactics in Computer Science as well as Embedded Systems and Society. The ability and willingness to collaborate with members of the faculty in Computer Science and Gender Studies is essential. Teaching in Computer Science and in the Master’s Program Gender Studies is expected. Candidates should have an exceptional aptitude for academic research, as evidenced by excellence in the research leading to the award of their PhD. A Junior Professorship requires the establishment of an independent research and teaching program. This non-tenure-track position is limited to four years with a possible extension of an additional two years.

The University of Freiburg is an equal opportunity employer and is dedicated to

facilitating the dual demands of family and career. We explicitly encourage women to

apply for the post. Given equivalent qualifications, preference in hiring will be

extended to handicapped applicants. Applications, including a CV, publication list, and a description of research interests should be submitted before September 22, 2012 to the Dean of the Faculty of

Engineering, Albert-Ludwigs-University Freiburg, Georges-Koehler-Allee 101, 79110.

Deepa Singh

Business Developer

Web Site:-http://www.gyapti.com

Blog:- http://gyapti.blogspot.com

Email Id:-deepa.singh@soarlogic.com

Surveying Media Computation Students: Self-Efficacy, Worked Examples, Python, and Excel

I’m back from Oxford, after an intense six weeks of teaching “Computational Freakonomics” and “Media Computation.” Since I did new things in Media Computation this term, I put together a little survey to get students’ feedback on what I did — not for research publication, but to inform me as a teacher. It’s complicated to interpret their responses. Only 11 of my 22 students completed my survey, so the results may not be representative of the whole class. (The class was 10 males and 12 females. I didn’t ask about gender on the survey, so I don’t know gender of the respondents.) The first thing I was wondering was whether the worked examples was perceived by students as helping them learn. “I found it useful to type in Python programs and figure them out at the start of class.” 4 strongly agree, 6 agree, 1 neutral.

That seems generally positive — students thought that the worked examples were useful. How about helping with Python syntax? ”Getting the characters exactly right (the syntax of Python) was difficult.” 2 agree, 1 neutral, 8 disagree. That’s in the right direction.

In the written portion, several students commented that they liked being able to focus on “understanding” programs “rather than just executing them.” One student even suggested that I could have questions about the program after they studied them, or I could have them make a change to the program afterward, to demonstrate understanding. I loved this idea, and particularly loved that it was suggested by a student. It indicates seeing a value in understanding programming, even before doing programming, while seeing value in that, too. This worked examples approach really does lead to a different way of thinking about introductory computer science: Programs as something to study first, before designing and engineering them. When I asked students what their favorite part of the course was, and what their least favorite part of the course was, Excel showed up on both lists (though more often on the least favorite part). Here’s one of the questions that stymied me to interpret: “Python is harder to learn and use than Excel.” Could not be a more perfect bell curve — what does that mean?!?

“I wish I could have learned more Excel in this course.” An almost perfectly uniform distribution!

Their reaction to Excel is so interesting. On the written parts of the survey, they told me how important it was for them to learn Excel, that it was very important for their careers. But they did not really like doing something as inauthentic (my word, not their’s) as pixel manipulation in Excel. They wished they could have done something more useful, like computing “expenses.”

The responses above suggest to me a hypothesis: The students don’t really know how to think about Excel in relation to Python. It’s as if they’re two different things, not two forms of the same thing. I was hoping for more of the latter, by doing pixel manipulations in both Python and Excel. This may be someplace where prior understanding influences the future understanding. I suspect that the students classify these things as.

“Excel is for business. It’s not for computing. Doing pixel manipulations in Excel is just weird and painful.”

“Python is for computing. I have to go through it, but it doesn’t really have much to do with my future career.” On the statement, “Learning programming as we have in this course is not useful to me,” 3 were neutral, and 8 disagreed. I read that as, “It’s okay. Sorta.” Something that I always worry about: Are we helping students to develop their sense of self-efficacy in an introductory course, especially for non-majors?

“I am more confident using computers now, after taking this course.” Quite positive: 10 agree, 1 neutral.

“I think differently about computers and how they work since taking this class.” Could not get much more positive: 8 strongly agree, 6 agree!

And yet, “I am not the kind of person who is good with computers.” Mostly, students agree with that: 3 strongly agree, 4 agree, 1 neutral, 3 disagree. One average, my students still don’t see themselves as among the people who are “good” with computers.

There was lots for me to be happy about. Some students said that the lectures on algorithmic complexity and the storage hierarchy were among their favorites; that they would have liked to have learned more about the “big questions” of CS; and they they liked writing programs. On the statement, “I learned interesting and useful computer science in this course,” 3 students strongly agreed, and 8 agreed. They got that this was about computer science, and some of them even found that useful. Even in a class of only 22, even seeing them every day for hours, even with grading all their papers — I’m still surprised, intrigued, and confounded by how they think about all of this. That’s fine by me. As a teacher and a researcher, my job isn’t done yet.

Deepa Singh

Business Developer

Web Site:-http://www.gyapti.com

Blog:- http://gyapti.blogspot.com

Email Id:-deepa.singh@soarlogic.com

Report from the Open University on Innovating Pedagogy

Perhaps the most positive immediate impact of Georgia Tech’s joining Coursera has been the size, extent, and frequency of discussion that it has engendered about education, technology, and the role of the University. While I was on study abroad, it came up in conversation with faculty at least every couple of days. Several of the faculty mailing lists I’m on raise issues about MOOC’s daily.

One of the common themes in these discussions is the Open University UK. Here’s a university that has a proven track record in using technology for educating students at a distance. The Open U. has just released a report on innovating pedagogues which looks really worthwhile. (I’ve downloaded it for review on my way home Sunday, when I saw that it has a whole section on eBooks.) I recommend diving into this material through Sen Schmoller’s blog, linked below, because he links into the additional literature that should have been included in the report. I note that this is “Report #1″ in a series, so I hope to see more instances of such useful reports.

Mike Sharpies sent me a link to this pre-release version [PDF] of Innovating Pedagogy 2012, which he has written for the Open University with Patrick MC Andrew, Martin Weller, Rachel Ferguson, Elizabeth Fitzgerald  Tony Hirst, Yishay Mor, Mark Gaven, and Denise White lock. The report gives an accessible overview of ten new forms of teaching, learning and assessment, and it has been written for non-academics. It looks to have been inspired by the EDUCAUSE Horizon Reports, but with a focus on learning and teaching

.Deepa Singh

Business Developer

Web Site:-http://www.gyapti.com

Blog:- http://gyapti.blogspot.com

Email Id:-deepa.singh@soarlogic.com

National Academies Report Defines ’21st-Century Skills’

I looked up this report, expecting to see something about computation as a ’21st-century skill.’ The report is not what I expected, and probably more valuable than what I was looking for. Rather than focus on which content is most valuable (which leads us to issues like the current debate of whether we ought to teach algebra anymore), the panel emphasized “nonacademic skills,” e.g., the ability to manage your time so that you can graduate and intra-personal skills. I also appreciated how careful the panel was about transfer, mentioning that we do know how to teach for transfer within a domain, but not between domains.

Stanford University education professor Linda Darling-Hammond, who was not part of the report committee, said developing common definitions of 21st-century skills is critical to current education policy discussions, such as those going on around the Common Core State Standards. She was pleased with the report’s recommendation to focus more research and resources on nonacademic skills. “Those are the things that determine whether you make it through college, as much as your GPA or your skill level when you start college,” she said. “We have tended to de-emphasize those skills in an era in which we are focusing almost exclusively on testing, and a narrow area of testing.”

The skill that may be the trickiest to teach and test may be the one that underlies and connects skills in all three areas: a student’s ability to transfer and apply existing knowledge to a problem in a new context. “Transfer is the sort of Holy Grail in this whole thing,” Mr. Pellegrino said. “We’d like to believe we can create Renaissance men who are experts in a wide array of disciplines and can blithely transfer skills from one to the other, but it just doesn’t happen that way.”

Deepa Singh

Business Developer

Web Site:-http://www.gyapti.com

Blog:- http://gyapti.blogspot.com

Email Id:-deepa.singh@soarlogic.com

Khan Academy offers kind-of-scaffolded computer science learning: Doing away with the teacher

With a bold claim, “Khan Academy Launches the Future of Computer Science Education,” Tech Crunch described Khan’s new foray into computer science. They've had CS videos in the past, but now they have a powerful text editor in which students can edit JavaScript, or manipulate variables like in Bret Victor’s cool demo. The Tech Crunch article actually cites research (see below), a paper by Cindy Hmelo. Cindy’s paper is actually on problem-based learning, but it does describe scaffolding — as defined in a Hmelo & Guzdial paper from 1996! How about that!

What I see in the Khan Academy offering is one of the kinds of scaffolding that Cindy and I talked about. Scaffolding is an idea (first defined by Wood, Burner, and Ross) which does involve letting students explore, but under the guidance of a tutor. A teacher in scaffolding doesn't “point out novel ways of accomplishing the task.” Instead, the teacher models the process for the student, coaches the student while they’re doing it, and gets the student to explain what they’re doing. A key part of scaffolding is that it fades — the student gets different kinds of support at different times, and the support decreases as the student gets more expert. I built a form of adaptable scaffolding in my 1993 dissertation project, Emile, which supported students building physics simulations in Hyper Talk. Yes, students using Emile could click on variables and fill in their values without directly editing the code, but there was also process guidance (“First, identify your goals; next, find your components in the Library”) and prompts to get students to reflect on what they’re doing. And the scaffolding could be turned on or off, depending on student expertise.

I wouldn't really call what Khan Academy has “scaffolding,” at least, not the way that Cindy and I defined it, nor in a way that I find compatible with Wood, Burner, and Ross’s original definition. There’s not really a tutor or a teacher. There are videos as I learned from this blog post, and later found for myself. The intro video (currently available on the main Khan Academy page) says that students should just “intuit” how the code works. Really? There’s a lot more of this belief that students should just teach themselves what code does. The “scaffolding” in Khan Academy has no kind of process modeling or guidance, nothing to explain to students what they’re doing or why, nothing to encourage them to explain it to themselves.

It is a very cool text editor. But it’s a text editor. I don’t see it as a revolution in computer science education — not yet, anyway. Now, maybe it’s way of supporting “collaborative floundering” which has been suggested to be even more powerful than scaffolding as a learning activity. Maybe they’re right, and this will be the hook to get thousands of adolescents interested in programming. (I wonder if they tested with any adolescents before they released?) Khan has a good track record for attracting attention — I look forward to seeing where this goes. The heart of the design places a simplified, interactive text editor that sits adjacent to the code’s drawing output, which updates in real time as students explore how different variables and numbers change the size, shapes, and colors of their new creation. An optional video guides students through the lesson, step-by-step, and, most importantly, can be paused at any point so that they can tinker with the drawing as curiosity and confusion arise during the process.

This part is key: learning is contextual and idiosyncratic; students better absorb new material if they can learn at their own pace and see the result of different options in real time. The pedagogy fits squarely into what educators called “ scaffold ed problem-based learning” [PDF]; students solve real-life problems and are encouraged to explore, but are guided by a teacher along the way, who can point out novel ways of accomplishing the task. Scaffold ed learning acknowledges that real-life problems always have more than one path to a solution, that students learn best by doing, and that curiosity should drive exploration. This last point is perhaps the most important, since one of the primary barriers to boosting science-related college majors is a lack of interest.

Deepa Singh

Business Developer

Web Site:-http://www.gyapti.com

Blog:- http://gyapti.blogspot.com

Email Id:-deepa.singh@soarlogic.com

ICER2012 Preview: Adapting the Disciplinary Commons for High School CS Teachers

While the schedule for the International Computing Education Research (ICER) 2012 conference is now up, the papers aren’t linked to it. I’m guessing that it’s because of the snafu that ACM had with their publishing contractor. I was waiting for the papers to be linkable before I started talking about our other two papers. Instead, I’ll just link to versions of our submitted papers (but not the final ones). I’ve already talked about Lauren’s paper on using subgoal analysis to improve instruction about App Inventor, which I’ve made available here. Here I’ll tell you a bit about Briana Morrison’s paper on adapting the Disciplinary Commons model for high school CS teachers.

The Disciplinary Commons is a model for professional development that Sally Fincher and Josh Tenenberg developed. We received NSF CPATH funding during the last three years to create the Disciplinary Commons for Computing Education (DCCE), which included both high school and university faculty. The university part wasn’t all that successful, and wasn’t the most interesting part of the work. The really interesting part was how Briana, Ria Galanos, and Lijun Ni adapted the DC model to make it work for high school teachers. There are really two big needs that high school CS teachers have that are different than university CS teachers:

Recruiting strategies: There are no majors in high school (in general) in the United States. High school CS teachers have no guaranteed flow of students into their classes. High school computer science is an elective in the US. If you want to teach CS, you recruit students into your class, or else you’ll end up teaching something else (or you lose your job). A Community: While I’m sure they exist, I’ve not yet met a higher education CS faculty member who is his or her own department. Most high school CS teachers are the only CS teachers in their school. They rarely know any other high school CS teachers. Providing them with a community makes a big difference in terms of their happiness, teaching quality, and retention.

Briana does a great job in her paper of explaining what happened in the DCCE over the three years that we ran it, and providing the evidence that good things happened. The evidence that the recruiting strategies worked is astounding.According to these self reported numbers, the high school teacher participants increased the number of AP CS students in the year following their participation in the DCCE by 302%. One teacher in Year 3 had a 700% increase in students in her AP CS class and attributed it to the recruiting help received from the DCCE. The evidence that the community-building helped is actually even stronger. We had The Findings Group as our external evaluators on DCCE, and they used social network analysis (SNA). The diagram is compelling, and the stats on the network show that the teachers dramatically increased their awareness and use of the network of high school CS teachers.



Briana is continuing to work with DCCE, to help other high school disciplinary commons start up around the country. NSF CPATH is allowing us to spend out the remaining money to fund her travel to help out other groups. Briana is now a PhD student working with me, and she’s figuring out what her dissertation is going to look like, and if it’ll build on the success of DCCE. (NSF CPATH funded DCCE. All the claims and opinions here are mine, not necessarily those of any of the funders.)

Deepa Singh
Business Developer
Web Site:-http://www.gyapti.com
Blog:- http://gyapti.blogspot.com
Email Id:-deepa.singh@soarlogic.com

Daphne Koller’s TED Talk: What’s new about MOOCs

While the schedule for the International Computing Education Research (ICER) 2012 conference is now up, the papers aren’t linked to it. I’m guessing that it’s because of the snafu that ACM had with their publishing contractor. I was waiting for the papers to be linkable before I started talking about our other two papers. Instead, I’ll just link to versions of our submitted papers (but not the final ones). I’ve already talked about Lauren’s paper on using subgoal analysis to improve instruction about App Inventor, which I’ve made available here. Here I’ll tell you a bit about Briana Morrison’s paper on adapting the Disciplinary Commons model for high school CS teachers.

The Disciplinary Commons is a model for professional development that Sally Fincher and Josh Tenenberg developed. We received NSF CPATH funding during the last three years to create the Disciplinary Commons for Computing Education (DCCE), which included both high school and university faculty. The university part wasn’t all that successful, and wasn’t the most interesting part of the work. The really interesting part was how Briana, Ria Galanos, and Lijun Ni adapted the DC model to make it work for high school teachers. There are really two big needs that high school CS teachers have that are different than university CS teachers:

Recruiting strategies: There are no majors in high school (in general) in the United States. High school CS teachers have no guaranteed flow of students into their classes. High school computer science is an elective in the US. If you want to teach CS, you recruit students into your class, or else you’ll end up teaching something else (or you lose your job). A Community: While I’m sure they exist, I’ve not yet met a higher education CS faculty member who is his or her own department. Most high school CS teachers are the only CS teachers in their school. They rarely know any other high school CS teachers. Providing them with a community makes a big difference in terms of their happiness, teaching quality, and retention.

Briana does a great job in her paper of explaining what happened in the DCCE over the three years that we ran it, and providing the evidence that good things happened. The evidence that the recruiting strategies worked is astounding.According to these self reported numbers, the high school teacher participants increased the number of AP CS students in the year following their participation in the DCCE by 302%. One teacher in Year 3 had a 700% increase in students in her AP CS class and attributed it to the recruiting help received from the DCCE. The evidence that the community-building helped is actually even stronger. We had The Findings Group as our external evaluators on DCCE, and they used social network analysis (SNA).  The diagram is compelling, and the stats on the network show that the teachers dramatically increased their awareness and use of the network of high school CS teachers.



Briana is continuing to work with DCCE, to help other high school disciplinary commons start up around the country. NSF CPATH is allowing us to spend out the remaining money to fund her travel to help out other groups. Briana is now a PhD student working with me, and she’s figuring out what her dissertation is going to look like, and if it’ll build on the success of DCCE. (NSF CPATH funded DCCE. All the claims and opinions here are mine, not necessarily those of any of the funders.)


Deepa Singh
Business Developer
Web Site:-http://www.gyapti.com
Blog:- http://gyapti.blogspot.com
Email Id:-deepa.singh@soarlogic.com

While the schedule for the International Computing Education Research (ICER) 2012 conference is now up, the papers aren’t linked to it. I’m guessing that it’s because of the snafu that ACM had with their publishing contractor. I was waiting for the papers to be linkable before I started talking about our other two papers. Instead, I’ll just link to versions of our submitted papers (but not the final ones). I’ve already talked about Lauren’s paper on using subgoal analysis to improve instruction about App Inventor, which I’ve made available here. Here I’ll tell you a bit about Briana Morrison’s paper on adapting the Disciplinary Commons model for high school CS teachers.

The Disciplinary Commons is a model for professional development that Sally Fincher and Josh Tenenberg developed. We received NSF CPATH funding during the last three years to create the Disciplinary Commons for Computing Education (DCCE), which included both high school and university faculty. The university part wasn’t all that successful, and wasn’t the most interesting part of the work. The really interesting part was how Briana, Ria Galanos, and Lijun Ni adapted the DC model to make it work for high school teachers. There are really two big needs that high school CS teachers have that are different than university CS teachers:

Recruiting strategies: There are no majors in high school (in general) in the United States. High school CS teachers have no guaranteed flow of students into their classes. High school computer science is an elective in the US. If you want to teach CS, you recruit students into your class, or else you’ll end up teaching something else (or you lose your job). A Community: While I’m sure they exist, I’ve not yet met a higher education CS faculty member who is his or her own department. Most high school CS teachers are the only CS teachers in their school. They rarely know any other high school CS teachers. Providing them with a community makes a big difference in terms of their happiness, teaching quality, and retention.

Briana does a great job in her paper of explaining what happened in the DCCE over the three years that we ran it, and providing the evidence that good things happened. The evidence that the recruiting strategies worked is astounding.According to these self reported numbers, the high school teacher participants increased the number of AP CS students in the year following their participation in the DCCE by 302%. One teacher in Year 3 had a 700% increase in students in her AP CS class and attributed it to the recruiting help received from the DCCE. The evidence that the community-building helped is actually even stronger. We had The Findings Group as our external evaluators on DCCE, and they used social network analysis (SNA).  The diagram is compelling, and the stats on the network show that the teachers dramatically increased their awareness and use of the network of high school CS teachers.



Briana is continuing to work with DCCE, to help other high school disciplinary commons start up around the country. NSF CPATH is allowing us to spend out the remaining money to fund her travel to help out other groups. Briana is now a PhD student working with me, and she’s figuring out what her dissertation is going to look like, and if it’ll build on the success of DCCE. (NSF CPATH funded DCCE. All the claims and opinions here are mine, not necessarily those of any of the funders.)


Deepa Singh
Business Developer
Web Site:-http://www.gyapti.com
Blog:- http://gyapti.blogspot.com
Email Id:-deepa.singh@soarlogic.com

ICER2012 Preview: Surveying the Whole State of introductory undergraduate CS in Georgia

One of the biggest final efforts in “Georgia Computes!” has been trying to get a measure of the whole state’s CS1/CS2 population. Who are they? Where did they come from? What influenced their decision to take a CS course? Did “Georgia Computes!” have any influence on them? Our third ICER2012 paper (available here) documents our effort to answer those questions.

Of the 35 colleges and universities in Georgia, 29 offer computer science coursework, and 19 participated in our statewide survey. (Why only 19 or 29? Great question, and worthy of another study in itself.) In total, 1,434 introductory computer science students (in either a first or second semester course, but all in the same semester without duplication of students) completed the survey. Our analysis had three parts:

General description of who’s taking CS and why An attempt to answer the question, “Did Georgia Computes have an effect?”Regression analysis on what variables impact decisions to pursue computing.

The general description required a GT vs. non-GT lens. 673 of the students in the survey came from Georgia Tech, and most of those were not CS majors, since GT requires everyone to take CS1. When GT is included, the pool is 31% female, but without GT, it’s only 25% female. Most of the pool had no interest in CS in middle or high school, but the percent expressing interest rises dramatically when you take GT out (since there are so many non-majors being forced to take CS at GT). Having some middle school out-of-school computing experience is pretty much the same with GT (57%) or without GT (56%) which is somewhat surprising. Only 56% of students who ended up as CS majors (not at GT) did anything with CS in middle school? Even larger percentage 57% of students (at GT, thus part of the “required” and “not likely to be CS majors” cohort) had some middle school CS, but did not choose a CS major? One explanation might be that GT is a prestigious school and the kids who go there (CS majors or not) had more out-of-school experiences in general.

We did ask students that if they were NOT a computing major, what were the reasons? Here were the top three answers I don’t want to do the kind of work that a computing major/minor leads to, 30%. I don’t enjoy computing courses, 20% I don’t think I belong in computing (don’t fit the stereotype), 13%. In general, GaComputes out-of-school activities were not mentioned by many students. Girl Scout events and summer camps are still too small in Georgia to touch a significant percentage of students who end up in CS. A big part of our analysis was figuring out if the students may have been influenced by a teacher who had professional development through Barbara’s Institute for Computing Education (ICE). We asked every student what high school they went to, then deciphered their scrawl, and figured out if we had an ICE teacher there. (We didn’t try to figure out if the student actually interacted with that teacher.) Yes, in general, schools that have ICE teachers do produce more women in our CS1/CS2 data set and more under-represented minorities (in some categories), but neither is a significant difference. Right direction, not not enough to make a strong claim.

Finally, we looked at what influenced student interest in pursuing computing career, disaggregated by gender and race/ethnicity. There were several statistically significant differences that we noted, like men are more interested in computer games and programming than women, and women are more interested in using computing to help people or society. These aren’t new, but at the size and scope of the survey, it’s an important replication. Most interesting is the mediation analysis that Tom McKlin and Shelly Engelman did. They found that women and under-represented minorities are statistically more influenced by encouragement and a sense of belonging than by a sense of ability, compared to men and white/Asian groups, with outcome variables of (a) satisfaction in choosing to study computing, (b) likelihood in completing a computing major/minor, and (c) likelihood of pursuing a career in computing. Again, these are expected results, but it’s useful to get a large, broad replication.

As I said before, we’re getting to the end of “Georgia Computes!” This was one of our last big analysis efforts. It’s really hard to do these kinds of studies (e.g., each of those school that did not participate still got our time and effort in trying to convince them, then there’s the data cleaning and analysis and…). I’m glad that we got this snapshot, but wish that we got it at an even larger scale and more regularly. That would be useful for us to use as a yardstick over time. (NSF BPC funded “Georgia Computes!”. All the claims and opinions here are mine and my colleagues’, not necessarily those of any of the funders.)

Deepa Singh

Business Developer

Web Site:-http://www.gyapti.com

Blog:- http://gyapti.blogspot.com

Email Id:-deepa.singh@soarlogic.com

How White and Male the AP CS Really Is: Measuring Quality as well as Quantity

We spent a significant amount of time this summer discussing with NSF our proposal to create an alliance around Expanding Computing Education Pathways (ECEP). One of the issues that we got pressed on was how to not just improve the numbers of women and members of under-represented minorities entering computer science, but to improve the quality of their learning and of their performance on metrics like the Advanced Placement Computer Science exam. Barbara Ericson started digging into the AP CS data at the College Board site, and found some pretty amazing things. I’m helping with some of the statistics (using my new “Computational Freakonomics” knowledge). We’re not sure what we’re going to do with this yet (SIGCSE paper, perhaps?), but Barb agreed that I could share some of the stats with you. The results in this post are Barb’s analysis of the AP CS results from 2006-2011, the years in which “Georgia Computes!” and CAITEwere both in existence.

Nationally, here are the pass rates per year. The gap from the blue line at top and the red line below is explained by the gender gap. In 2011, the pass rate was 63.7% overall, 57.6% for females. The even larger gap from those two lines down to the rest is the race/ethnicity gap: 31.7% for Blacks, and 37.2% for Hispanics in 2011. I didn’t expect this: Hispanic females do statistically significantly better than Black females at passing the AP CS over this time frame (t-test, one-tailed, p=.01). (I’m using “Black” because that’s the demographic category that the College Board gives us. We are collapsing “Mexican American,” “Other Hispanic,” and “Puerto Rican” into the “Hispanic” category.) There’s still a big gap between the orange Hispanic line (37.2% in 2011) and the light blue Hispanic females line (25% in 2011).

While Hispanics are doing better than Blacks on AP CS, I was still surprised at this: No Hispanic female has scored a passing grade (3, 4, or 5) on the AP CS test in Georgia, Michigan, Indiana, South Carolina, or Alabama in the last six years. Only one Hispanic female has passed in Massachusetts in the same time frame. Why these states? ECEP is starting from Georgia and Massachusetts, next involving California and South Carolina, and we want to compare to states of similar size or similarly sized minority populations. We haven’t looked at all 50 states — the College Board doesn’t make it easy to grab these numbers.

The Black pass rate is quite a bit smaller than the Hispanic, in part because the participation rate is so low. Michigan has 1.4 million Blacks (out of 9.8 million overall population, so 14% Black), but only 2 Black men have passed the AP CS in the last six years. In 2011, 389 students took the AP CS in Michigan, only 2 of whom were Black. Only one Black female has even taken the AP CS in Michigan in the last six years. (No, she didn’t get a passing grade.)

Considering the population of the state is really important when considering these numbers. Last year, Georgia had 884 people take the AP CS Level A test (the most ever), 79 of whom were Black (about 9%). 17 passed. for a 21.5% pass rate. In contrast, California had a 51.7% pass rate among Black test-takers, 15 of the 29 test takers. That’s 29 test-takers out of 3101 AP CS Level A tests in California (0.9%)! California has an enormous test-taking population, but few Blacks and relatively few Hispanics (230 Hispanic test takers (49 female) out of the 3101 overall test takers). California has 37.6 million people, and 2.2 million Blacks (5.8%). Georgia has 9.8 million people, 2.9 million Blacks (30%). Bottomline: Georgia had many more Black test-takers than California, with a similarly-sized Black population. Georgia’s test-taking numbers aren’t representative of the population distribution overall (9% vs. 30%), but California’s are even more out-of-whack (0.9% vs. 5.8%).

Barb’s still digging into the numbers (e.g., to compare regionally, as well as by similarly sized). If we get ECEP, this is the first step — to know where we are, so we can measure how we do. Updated August 22: When I wrote this up, I didn’t realize that Barb had created several datasets. She has data back into the 1990′s, but the dataset she gave me was just 2006-2011, the years in which our NSF BPC Alliances existed. So my claims of “ever” in the original post were too strong. We don’t know that the claims are wrong, but we haven’t actually checked back further than 2006 yet. My sincere apologies for mis-stating the scope of my claims! I’m glad that we discovered this problem when it’s just a blog post, not a paper submitted for publication. I’ve updated the text of the post to reflect the claims that I can actually make.

Deepa Singh
Business Developer
Web Site:-http://www.gyapti.com
Blog:- http://gyapti.blogspot.com/
Email Id:-deepa.singh@soarlogic.com