Posts tagged ‘BPC’

Why are underrepresented minorities and poor over-represented in Code.org courses?

Code.org has a blog post describing their latest demographics results showing that they have remarkably high percentages of women (45%) and under-represented minorities (48%). In fact, their students are 49% on free and reduced meals.

Only 38% of students in the US are on free and reduced lunch.  44% of students in the US are Black or Hispanic (using US Department of Education data).

What does it mean that Code.org classes are over-sampling under-represented groups and poorer students?

I don’t know. Certainly, it’s because Code.org targeted large, urban school districts.  That’s who’s there.  But it’s not like the classes are unavailable to anyone else.  If the perception was these are valuable, shouldn’t more suburban schools be wanting them, too?

One explanation I can imagine is that schools that are majority poor and/or minority might be under-funded, so Code.org classes with their well-defined curriculum and clear teacher preparation models are very attractive. Those schools may not have the option of hiring (say) an AP CS teacher who might pick from one of the non-Code.org curriculum options, or even develop his or her own.

The key question for me is: Why aren’t the more majority and wealthier schools using Code.org classes?  CS is a new-to-schools, mostly-elective subject.  Usually those new opportunities get to the wealthy kids first.  Unless they don’t want it. Maybe the wealthy schools are dismissing these opportunities?

It’s possible that Code.org classes (and maybe CS in high school more generally) might get end up stigmatized as being for the poor and minority kids?  Perhaps the majority kids or the middle/upper-class kids and schools avoid those classes? We have had computing classes in Georgia that were considered “so easy” that administrators would fill the classes with problem students — college-bound students would avoid those classes.  We want CS for all.

Code.org has achieved something wonderful in getting so many diverse students into computing classes. The questions I’m raising are not meant as any criticism of Code.org.  Rather, I’m asking how the public at large is thinking about CS, and I’m using Code.org classes as an exemplar since we have data on them.  Perceptions matter, and I’m raising questions about the perceptions of CS classes in K-12.

I do have a complaint with the claim in the post quoted below.  The citation is to the College Board’s 2007 study which found that AP CS students are more likely to major in CS than most other AP’s, with a differentially strong impact for female and under-represented minority students.  “Taking AP CS” is not the same as “learn computer science in K-12 classrooms.”  That’s too broad a claim — not all K-12 CS is likely to have the same result.

Today, we’re happy to announce that our annual survey results are in. And, for the second year in a row, underrepresented minorities make up 48% of students in our courses and females once again make up 45% of our students…When females learn computer science in K-12 classrooms, they’re ten times more likely to major in it in college. Underrepresented minorities are seven to eight times more likely.

Source: Girls and underrepresented minorities are represented in Code.org courses

July 21, 2017 at 8:00 am 8 comments

“Algorithms aren’t racist. Your skin is just too dark.”: Teaching Ethics to future Software Developers

In my Ethics class this summer, I had my students watch Joy Buolamwini’s TED talk when we talked about professional ethics and responsibility.  My students had not before considered the possibility that bias is being built into software, but they recognized the importance of her message. Our students who will be software engineers have to be thinking about her message, about the racism that we build into our machines.

She’s been getting a lot of press since her TED talk, including this recent piece in The Guardian.  In her blog post quoted below, she responds to her critics in a careful and respectful tone, which took an enormous amount of maturity and patience.  “Suggesting people with dark skin keep extra lights around to better illuminate themselves misses the point.”  She is more patient and well-spoken than me. I think my response to the critics would have included the phrase, “Are you kidding me?!?” (with perhaps a couple more words in there).

One of the goals of the Algorithmic Justice League is to highlight problems with artificial intelligence so we can start working on solutions. We provide actionable critique while working on research to make more inclusive artificial intelligence. In speaking up about my experiences, others have been encouraged to share their stories. The silence is broken. More people are aware that we can embed bias in machines. This is only the beginning as we start to collect more reports.

Source: Algorithms aren’t racist. Your skin is just too dark.

July 17, 2017 at 7:00 am Leave a comment

Teaching the students isn’t the same as changing the culture: Dear Microsoft: absolutely not. by Monica Byrne

A powerful blog post from Monica Byrne with an important point. I blogged a while back that teaching women computer science doesn’t change how the industry might treat them.  Monica is saying something similar, but with a sharper point. I know I’ve heard from CS teachers who are worried about attracting more women into computing.  Are we putting them into a unpleasant situation by encouraging them to go into the computing industry?

Then—gotcha!—they’re shown a statistic that only 6.7% of women graduate with STEM degrees. They look crushed. The tagline? “Change the world. Stay in STEM.”

Are you f***ing kidding me?

Microsoft, where’s your ad campaign telling adult male scientists not to rape their colleagues in the field? Where’s the campaign telling them not to steal or take credit for women’s work? Or not to serially sexually harass their students? Not to discriminate against them? Not to ignore, dismiss, or fail to promote them at the same rate as men? Not to publish their work at a statistically significant lower rate?

Source: Dear Microsoft: absolutely not. | monica byrne

June 30, 2017 at 7:00 am 3 comments

Using tablets to broaden access to computing education: Elliot Soloway and truly making CS for All

I recently had the opportunity to visit with my PhD advisor, Elliot Soloway. Elliot has dramatically changed the direction of his research since we worked together. And he’s still very persuasive, because now I keep thinking about his challenge to push educational technology onto the least expensive devices.

When I worked with Elliot in the late 1980’s and early 1990’s, we emphasized having lots of screen real estate. Though the little Macintosh Plus was still popular through much of that time, Elliot was hooking up 21-inch, two page displays for all our development and at the high schools where we worked. The theoretical argument was the value of multiple-linked representations (like in this paper from Bob Kozma). By giving students multiple representations of their program and their design, we would facilitate learning across and between representations. The goal was to get students to see programming as design.

But in the mid 1990’s, Elliot changed his direction to emphasize inexpensive, handheld devices. I remember asking him why at the time, and he pointed out that you could give 10 students access to these low-cost devices for one of the higher-end devices. And access trumps screens.

Now, Elliot has a project, Intergalactic Mobile Learning Center, that produces software for learning that runs on amazingly inexpensive computers. Go to http://www.imlc.io/apps and try out their all-HTML software on any of your devices.

I purchased an Amazon Fire HD 8 tablet last year as a media consumption device (reading, videos, and music). For less than $100, it’s an amazingly useful device that I carry everywhere since it’s light and mostly plastic. Here’s some of IMLC’s software running on my inexpensive tablet.

Teaching Computer Science on a Tablet

I have been arguing in this blog that we need a greater diversity of teaching methods in computer science, to achieve greater diversity and to teach students (and reach students) who fail with our existing methods. Elliot’s argument for inexpensive tablets has me thinking about the value for computing education.

If our only CS teaching method is “write another program,” then a tablet makes no sense. Typing on a tablet is more difficult than on a laptop or desktop computer. I have been arguing that we can actually teach a lot about coding without asking students to program. If we expand our teaching methods to those that go beyond simply writing programs, then a tablet makes a lot of sense.

Could a focus on using tablets to teach computer science drive us to develop new methods? If more CS teachers tried to use tablets, might that lead to greater adoption of a diverse range of CS teaching methods?

Elliot’s argument is about bridging the economic and digital divide. Can we use the low cost of tablets to break down economic barriers to learning computer science? Computing education via tablets may be key to the vision of CS for All. We can outfit a whole classroom with tablets much more cheaply than buying even mid-range laptops for an elementary or middle school classroom.  There are people suggesting that if we buy kids iPads, we’ll improve learning (e.g., Los Angeles schools).  I’m making the inverse argument.  If we as computing curriculum/technology developers and teachers figure out how to teach computing well with tablets, we’ll improve learning for everyone.

I started checking out what I could do with my less than $100 tablet. I was amazed! Moore’s Law means that the low-end today is surprisingly capable.

GP, the new blocks-based programming language that I’ve been working with (see posts here and here), runs really well on my Fire HD 8 tablet. In fact, it runs better (more functionality, more reliable, greater stability) in the browser of my Fire tablet than the browser-based GP does on my iPad Pro (which costs about a magnitude more).  (There is an iOS version of GP which is fast and stable, but doesn’t have all the features of the browser-based version.)

GP running on a Fire HD 8 Tablet — two Media Computation projects (mirroring on left, removing red eye on right)

Our ebooks run well on the Fire HD 8 tablet. I can program Python in our ebook using the tablet. Our approach in the ebooks emphasizes modification to existing programs, not just coding from scratch. Tweaking text works fine on the tablet.

Running Python code on the Fire HD 8 Tablet

A wide range of CS education practice activities, from multiple choice questions to Parsons Problems, work well on the Fire HD 8.

Parsons Problem on Fire HD 8 Tablet

I tried out WeScheme on my Fire HD 8, too.

I bought the cheapest Chromebook I could find for this trip. I wanted a laptop alternative to take to China and for commuting on the Barcelona subway, rather than my heavier and more expensive MacBook Air. All of these browser-based tools (GP, Python programming in the ebook, Parsons Problems) run great on my $170 Acer Chromebook, plus I get a keyboard. Even a Chromebook would require different teaching and learning methods than what we use in many CS courses. I’m not going to run Eclipse or even JES on a Chromebook. (Though Emacs has been ported to the Chromebook, it only runs on certain Chromebooks and not mine). Google is aiming to merge Chromebook and Android development so that apps run on both. I don’t really understand all the differences between tablets and Chromebooks, but I do know that Chromebooks are becoming more common in schools.

A Chromebook costs about twice what a low-end tablet costs. While that is still much less than most laptops, twice is a big markup for a poor student or a budget-strapped school. It’s worth pushing for the lowest end.

CS education researchers, developers, and teachers should explore teaching computing with tablets. Some are doing this already. The next version of Scratch will run on mobile phones, and the current version will already run on some phones and tablets. Creating CS learning opportunities on low-end tablets will make computing education more affordable and thus accessible to a broader range of potential CS students.  My proposal isn’t about offering the poor a cheaper, low-quality alternative. Tablets force us to expand and diversify our teaching methods, which will lead us to create better and more accessible computing education for all.

June 14, 2017 at 7:00 am 9 comments

Congratulations to Owen, Valerie, and Chris — ACM Award Winners!

Sharing Amber Settle’s note about ACM awardees from the computing education community, with her kind permission.

The SIGCSE Board would like to congratulate Owen Astrachan, Valerie Barr, and Chris Stephenson on their recent ACM awards.

Owen Astrachan was named recipient of the 2016 ACM Karl V. Karlstrom Outstanding Educator Award for three decades of innovative computer science pedagogy and inspirational community leadership in broadening the appeal of high school and college introductory computer science courses. His citation can be found here: http://awards.acm.org/award_winners/astrachan_3068814

Valerie Barr has received the 2016 Outstanding Contribution to ACM Award for reinventing ACM-W, increasing its effectiveness in supporting women in computing worldwide and encouraging participation in ACM.  Since becoming Chair of ACM-W in 2012, Barr has been a driving force in more than tripling the number of ACM-W chapters around the world. Her citation can be found here: http://awards.acm.org/award_winners/barr_3211646

Chris Stephenson, Head of Computer Science Education Programs at Google Inc., was recognized for creating the Computer Science Teachers Association, an international organization dedicated to supporting teachers and pursuing excellence in CS education for K-12 students. More information can be found here: http://awards.acm.org/about/2016-presidential-award-stephenson

Owen, Valerie, and Chris will receive their awards at the ACM Awards Banquet later this month in San Francisco. Please join us in congratulating them for their achievements.

Amber Settle

SIGCSE chair, 2016-2019

June 7, 2017 at 7:00 am 2 comments

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

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