Posts tagged ‘BPC’

Belief in the Geek Gene may be driven by Economics and Educational Inefficiency, plus using blocks to cross language boundaries

I visited China in the first part of May. I was at Peking University (PKU) in Beijing for a couple days, and then the ACM Celebration of the Turing Award in China (TURC) in Shanghai. I mentioned the trip in this earlier blog post. I wrote a blog post for CACM on a great panel at TURC. The panelists discussed the future of AI, and I asked about the implications for computing education. Are we moving to a future where we can’t explain to students the computing in their daily lives?

A highlight of my trip was spending a day with students and teachers at PKU. I taught a seminar with 30+ advanced undergraduates with Media Computation (essentially doing my TEDxGeorgiaTech talk live). It was great fun. I was surprised to learn that several of them had learned programming first in high school in Pascal. Pascal lives as a pedagogical programming language in China!

Perhaps the most striking part of my seminar with the undergraduates was how well the livecoding examples worked (e.g., I wrote and manipulated code as part of the talk).  All the PKU students knew Java, most knew C++, some knew Python — though I knew none of that when I was planning my talk. I wanted to use a tool that would cross programming language boundaries and be immediately understandable if you knew any programming languages. I used a blocks-based language.  I did my livecoding demonstration entirely in GP. I tested their knowledge, too, asking for predictions (as I do regularly, having read Eric Mazur’s work on predictions before demos) and explanations for those predictions.  They understood the code and what was going on. The funky sound and image effects cross language barriers.  Students laughed and oohed at the results.  Isn’t that remarkable that it worked, that I could give a livecoding demonstration in China and get evidence that the students understood it?

The most interesting session at PKU was talking with faculty interested in education about their classes and issues. I’ve always wondered what it’s like for students to learn programming when English is not their native language, and particularly, when the characters are very different. I asked, “Is it harder for your students to learn programming when the characters and words are all English?” The first faculty to speak up insisted that it really wasn’t an issue. “Our students start learning English at age 6!” said one. But then some of the other faculty spoke up, saying that it really was a problem, especially for younger students. In some middle schools, they are using Squeak with Chinese characters. They told me that there was at least one programming language designed to use Chinese characters, but the other faculty scoffed. “Yi is not a real programming language.” There was clearly some disagreement, and I didn’t follow all the nuances of the argument.

Then the Geek Gene came up in the conversation. One of the most senior faculty in the room talked about her challenges in teaching computer science. “Some students are just not suited to learning CS,” she told me. I countered with the evidence of researchers like Elizabeth Patitsas that there is no “Geek Gene.” I said, “We have no evidence that there are students who can’t learn programming.” She had an effective counter-argument.

“We do not have all the time in the world. We cannot learn everything in our lifetime. How much of a lifetime should a student spend learning programming? There are some students who cannot learn programming in the time available. It’s not worth it for them.”

I had not thought of the Geek Gene as being an economic issue. Her argument for the Geek Gene is not necessarily that students cannot learn programming. They may not be able to learn programming in the time available and using the methods we have available. This is not Geek Gene as only some students can learn to program. This is Geek Gene as economic limitation — we can’t teach everyone in the resources available.

I have an answer to that one. Want to reach more students? Either expand the time it will take to teach them, or use more effective methods!  This is the same response that I had offered to my colleague, as I described in an earlier blog post.

That insight gave me a whole new reason for doing our work in efficient CS education, like the greater efficiency in using subgoal-based instruction. The work of Paul Kirschner and Mike Lee & Andy Ko also emphasizes more CS learning in less time. If we can teach the same amount of CS in less time, then we can expand the number of students who can learn enough CS with a given amount of resource (typically, time). If we can’t convince teachers that there is no Geek Gene, maybe we can give them more effective and efficient teaching methods so that they see fewer students who don’t seem have the Geek Gene, i.e., who can learn enough CS in a single semester.

Below, evidence I was really at TURC

June 5, 2017 at 7:00 am 8 comments

How to be a great (CS) teacher from Andy Ko

Andy Ko from U-W is giving a talk to new faculty about how to be a great CS teacher.  I only quote three of his points below — I encourage you to read the whole list.  Andy’s talk could usefully add some of the points from Cynthia Lee’s list on how to create a more inclusive environment in CS.  CS is far less diverse than any other STEM discipline.  Being a great CS teacher means that you’re aware of that and take steps to improve diversity in CS.

My argument is as follows:

  • Despite widespread belief among CS faculty in a “geek gene”, everyone can learn computer science.
  • If students are failing a CS class, it’s because of one or more of the following: 1) they didn’t have the prior knowledge you expected them to have, 2) they aren’t sufficiently motivated by you or themselves, 3) your class lacks sufficient practice to help them learn what you’re teaching. Corollary: just because they’re passing you’re class doesn’t mean you’re doing a great job teaching: they may already know everything you’re teaching, they may be incredibly motivated, they may be finding other ways to practice you aren’t aware of, or they may be cheating.
  • To prevent failure, one must design deliberate practice, which consists of: 1) sustained motivation, 2) tasks that build on individual’s prior knowledge, 3) immediate personalized feedback on those tasks, and 4) repetition.

Source: How to be a great (CS) teacher – Bits and Behavior – Medium

May 29, 2017 at 7:00 am Leave a comment

Jean Sammet passes away at age 89

Jean Sammet passed away on May 21, 2017 at the age of 88. (Thanks to John Impagliazzo for passing on word on the SIGCSE-members list.)  Valerie Barr, who has been mentioned several times in this blog, was just named the first Jean E. Sammet chair of computer science at Mount Holyoke.  I never met Jean, but knew her from her work on the history of programming languages which are among the most fun CS books I own.

Sammet

GILLIAN: I remember my high school math teacher saying that an actuary was a stable, high-paying job. Did you view it that way?

JEAN: No. I was looking in The New York Times for jobs for women—when I tell younger people that the want ads were once separated by gender, they’re shocked—and actuary was one of the few listed that wasn’t housekeeping or nursing, so I went.Sammet found her way to Sperry. “Everything from there, for quite a while, was self-learned,” she says. “There were no books, courses, or conferences that I was aware of.” For her next move she applied to be an engineer at Sylvania Electric Products—though the job was again listed for men.

Source: Gillian Jacobs Interviews Computer Programmer Jean E. Sammet | Glamour

May 26, 2017 at 7:00 am 1 comment

We can teach women to code, but that just creates another problem: Why Computational Media is so female

I suspect that the problem described in this Guardian article is exactly what’s happening with our Computational Media degree program.  The BS in CM at Georgia Tech is now 47% female, while the BS in CS is only 20% female.  CM may be perceived as front-end and CS as back-end.

But here’s the problem: the technology industry enforces a distinct gender hierarchy between front-end and back-end development. Women are typecast as front-end developers, while men work on the back end – where they generally earn significantly more money than their front-end counterparts. That’s not to say that women only work on the front end, or that men only work on the back end – far from it. But developers tell me that the stereotype is real.

The distinction between back and front wasn’t always so rigid. “In the earliest days, maybe for the first 10 years of the web, every developer had to be full-stack,” says Coraline Ada Ehmke, a Chicago-based developer who has worked on various parts of the technology stack since 1993. “There wasn’t specialization.”

Over time, however, web work professionalized. By the late 2000s, Ehmke says, the profession began to stratify, with developers who had computer science degrees (usually men) occupying the back-end roles, and self-taught coders and designers slotting into the front.

Source: We can teach women to code, but that just creates another problem | Technology | The Guardian

May 19, 2017 at 7:00 am 3 comments

Hidden Figures of “Computer Science for All”

Nice piece by Ruthe on some of the heroes of the effort to make CS education available to everyone.

You might have noticed computer science and “coding” have become the cause du jour. Celebrities and athletes, governors and mayors, tech icons, and media giants have come out in support of reinvigorating K-12 computer science education in US schools. Coding is now a commonly known term and in January 2016, building on the momentum from the community, President Obama announced the Computer Science for All (CSforAll) initiative, a bold national call to make rigorous computer science (CS) education available to all American students and partner initiatives have formed nationwide including CS4TX, CS4RI, CodeVA and many more. CSforAll is here to stay.

Like every social movement in history, this change didn’t materialize overnight – and like the great social movements that have shaped our country – women have been integral to this movement. I am honored to present just a few of the “Hidden Figures” of K-12 computer science education.

Source: Hidden Figures of “Computer Science for All”

May 10, 2017 at 7:00 am Leave a comment

MOOCs don’t serve to decrease income inequality

At this year’s NSF Broadening Participation in Computing PI meeting, I heard a great talk by Kevin Robinson that asked the question: Do MOOCs “raise all boats” but maintain or even increase income inequality, or do they help to reduce the economic divide?  It’s not the question whether poor students take MOOCs.  It’s whether it helps the poor more, or the rich more.

Kevin has made his slides available here. The work he described is presented in this article from Science.  I want to share the one slide that really blew me away.

The gray line is the average income for US citizens at various ages.  As you would expect, that number generally increases up until retirement.  The black line is the average income for students in Harvard and MIT’s MOOC participants.  The MOOC participants are not only richer, but as they get older, they diverge more.  These are highly-privileged people, the kind with many advantages.  MOOCs are mostly helping the rich.

May 1, 2017 at 7:00 am 6 comments

Discussing the film “Code: Debugging the Gender Gap”

Barbara Ericson and I were invited to be discussants at a showing of “Code: Debugging the Gender Gap.”  I highly recommend the movie.  It was fascinating to watch, made all the more fun by seeing heroes that I know appear, like Nathan Ensmenger, Avis Yates Rivers, Jane Margolis, Ari Schlesinger, Colleen Lewis, and Maria Klawe.

Afterward, I got to make a few comments — expanding on some of the movie’s points, and disagreeing with others.

The movie makes the argument that men and women aren’t wired differently.  We are all capable of learning computer science.  They didn’t have to make a biological argument.  In the Middle East and many other parts of the world, computer science is female-dominated. Clearly, it’s not biology.  (Perhaps surprisingly, I recently got asked that question at one of the top institutes of technology in the United States: “Don’t women avoid CS because their brains work differently?”  REALLY?!?)

The movie talks about how companies like IBM and RCA started advertising in the 1970’s and 1980’s for “men” with “the right stuff,” and that’s when the field started masculinizing.  They don’t say anything about the role that educators played, the story that Nathan Ensmenger has talked about in his book “The Computer Boys Take Over.”  When we realized that we couldn’t teach programming well, we instead started to filter out everyone who would not become a great programmer. For example, that’s when calculus was added into computer science degree requirements.  Women were less interested in the increasingly competitive computer science programs, especially when there were obvious efforts to weed people out.  That was another factor in the masculinization of the field.

Many of those interviewed in the movie talk about the importance of providing “role models” to women in computing.  The work of researchers like the late (and great) Joanne Cohoon show that role models aren’t as big a deal as we might think.  Here’s a thought experiment to prove the point: There are biology departments where the faculty are even more male than most CS departments, yet those departments are still female-dominant.  What we do know is that women and URM students need encouragement to succeed in CS, and that that encouragement can come from male or female teachers.

Finally, several interviewed in the movie say that we have to get girls interested in CS early because high school or university is “way too late.”  That’s simply not true.  The chair of my School of Interactive Computing, Annie Antón, didn’t meet computing until she was an undergraduate, and now she’s full Professor in a top CS department.  Yes, starting earlier would likely attract more women to computing, but it’s never “too late.”

After the movie, an audience member asked me if I really believed that diversity was important to build better products, and how would we prove that.  I told him that I didn’t think about it that way.  I’m influenced by Joanna Goode and Jane Margolis.  Computing jobs are high-paying and numerous.  Women and under-represented minority students are not getting to those jobs because they’re not getting access to the opportunites, either because of a lack of access to computing education or because of bias and discrimination that keep them out.  It’s not about making better products.  This is a social justice issue.

 

April 28, 2017 at 7:00 am 5 comments

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