Posts tagged ‘computing for all’

From Design of Everyday Things to Teaching of Everyday People: Human error? Student error? No, Bad Design

We have to accept human behavior the way it is, not the way we would wish it to be.

Continue Reading June 26, 2017 at 7:00 am 12 comments

We need to separate Computing for All from Software Development: Claims that coding is not “fun,” it’s technically and ethically complex

The problem with the article linked below is that Code.org and the author mean two different things by the word “programming.”  Programming can be fun, insightful, sloppy, small, and still useful without demanding “superhuman focus” and “manic attention to detail.”  This is an issue I’ve talked about with respect to the thick line between programmer and user where most people will be in the future. I’m teaching an ethics course this summer — building software for others is technically and ethically complex, as the author states.  But building software as an end-user, as a hobbyist, as a scientist or engineer exploring an idea?  We need a different word.

Programming computers is a piece of cake. Or so the world’s digital-skills gurus would have us believe. From the non-profit Code.org’s promise that “Anybody can learn!” to Apple chief executive Tim Cook’s comment that writing code is “fun and interactive,” the art and science of making software is now as accessible as the alphabet.

Unfortunately, this rosy portrait bears no relation to reality. For starters, the profile of a programmer’s mind is pretty uncommon. As well as being highly analytical and creative, software developers need almost superhuman focus to manage the complexity of their tasks. Manic attention to detail is a must; slovenliness is verboten. Attaining this level of concentration requires a state of mind called being “in the flow,” a quasi-symbiotic relationship between human and machine that improves performance and motivation.

Source: Coding is not “fun,” it’s technically and ethically complex — Quartz

June 19, 2017 at 7:00 am 4 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 7 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

Profile of Ruthe Farmer: This Is How You Advocate For Girls In STEM

Nice piece on fierce CS education advocate, Ruthe Farmer.

Big change is at the forefront of her thinking. When asked what cause she most wants to advance, she has a prompt and specific reply: “I am interested in advancing women at all levels.  For women’s rights to education, autonomy, personal safety to be a topic of debate [still] is atrocious. Now is the time for women to lead. I’m particularly concerned about the safety of women on campus.  Sexual assault should not be an expected part of the college experience. I refuse to accept that as a norm.”

Source: This Is How You Advocate For Girls In STEM

May 5, 2017 at 7:00 am Leave a comment

Report on Addressing Unconscious Bias in CS Classrooms

New research report available at http://services.google.com/fh/files/misc/unconscious-bias-in-the-classroom-report.pdf from with Google and Thomas Dee of Stanford University and Seth Gershenson from American University.

In sum, Unconscious Bias (UB) is a nontrivial problem in education, especially in CS and STEM education, and it is not easily addressed via traditional educational policies and interventions. However, interventions that identify and alter the frequently unconscious psychological processes that harm individuals’ outcomes are currently being developed and piloted. Teacher-facing interventions, which can be administered to both pre- and in-service teachers, are particularly promising. In part, this is because by addressing UB among teachers, we can help shape the entire classroom context in supportive ways. Furthermore, teacher-facing interventions are potentially cost-effective and scalable, because infrastructure for teacher training is already in place.

April 26, 2017 at 7:00 am Leave a comment

NSF Report: Women, Minorities, and Persons with Disabilities in Science and Engineering

A useful report when trying to make an argument for the importance of Broadening Participation in Computing efforts:

Women, Minorities, and Persons with Disabilities in Science and Engineering provides statistical information about the participation of these three groups in science and engineering education and employment. Its primary purpose is to serve as a statistical abstract with no endorsement of or recommendations about policies or programs. National Science Foundation reporting on this topic is mandated by the Science and Engineering Equal Opportunities Act (Public Law 96-516).This digest highlights key statistics drawn from a wide variety of data sources. Data and figures in this digest are organized into five topical areas—enrollment, field of degree, occupation, employment status, and early career doctorate holders.

Source: About this report – nsf.gov – Women, Minorities, and Persons with Disabilities in Science and Engineering – NCSES – US National Science Foundation (NSF)

April 12, 2017 at 7:00 am Leave a comment

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