Posts tagged ‘BPC’
Andy Kessler of the Wall Street Journal (linked below) misunderstands why we have a computing labor shortage. MOOCs definitely make “computing education” (in general) accessible to more people. But that doesn’t mean that we’ll shrink the computing labor shortage, as described by Code.org. Undergraduate computing education is “accessible” to everyone on campus, but rarely draws more than 15% women. We have to go from “accessible” to “engaging.” Unless we draw in women and under-represented minorities, we can’t close the jobs-graduates gap. We have to change how we teach to draw more women and under-represented minorities, and MOOCs don’t teach that way.
Anyone who cares about Americas shortage of computer-science experts should cheer the recent news out of Georgia Tech. The Atlanta university is making major waves in business and higher education with its May 14 announcement that the college will offer the first online masters degree in computer science—and that the degree can be had for a quarter of the cost of a typical on-campus degree. Many other universities are experimenting with open online courses, or MOOCs, but Georgia Techs move raises the bar significantly by offering full credit in a graduate program.It comes just in time. A shortfall of computer-science graduates is a constant refrain in Silicon Valley, and by 2020 some one million high-tech job openings will remain unfilled, according to the Commerce Department.
The latest Freakonomics podcast is on tipping and whether it should be banned, i.e., made illegal. One of the arguments for banning tipping is that it’s discriminatory. White servers get more than Black servers, for example. Professor Michael Lynn cited a Supreme Court case that I found described below. If a neutral practice disproportionately affects minorities or women in an adverse manner, then the practice is illegal.
I’ve raised the question here before, whether CS departments could be forced to change their teaching practices in order to comply with Title IX provisions so that more women might participate. One of the arguments I got in response was that no one adopted any practices to explicitly exclude women. This ruling says that the motivation for the practice doesn’t matter — even if it’s a “neutral” practice, if the effect is discriminatory, it has to go. We certainly have evidence that implicit bias exists in computing classrooms and that CS teachers allow their classrooms to develop a defensive climate. Further, we know a lot about how to improve women’s participation in computing. If we have a legal requirement to make computing education available to women, my guess is that we could be required to make change. For example, could we be forced to give up MOOCs as a discriminatory practice, since MOOCs have a measurable discriminatory effect?
In Griggs v. Duke Power Co., the Supreme Court decides that where an employer uses a neutral policy or rule, or utilizes a neutral test, and this policy or test disproportionately affects minorities or women in an adverse manner, then the employer must justify the neutral rule or test by proving it is justified by business necessity. The Court reasons that Congress directed the thrust of Title VII to the consequences of employment practices, not simply the motivation. This decision paves the way for EEOC and charging parties to challenge employment practices that shut out groups if the employer cannot show the policy is justified by business necessity.
Of course, I love a blog post on computing students with so much data and graphs that it could be a conference paper! Nice piece from Monica McGill on where gaming students are coming from, and what the implications are for future game designs.
Even in 2005, the IGDA report on its diversity survey found that the typical game development professional is “white, male, heterosexual, not disabled, […] and agrees that workforce diversity is important to the future success of the game industry” (pp. 9-10). The report goes on to state that “… it is reasonable to believe that diversity does have an impact on the game industry and the products we create – either via broader markets and/or a means to attract future talent” (p. 22).
Ah, attracting future talent. That phrase certainly begs the question: what future talent are we attracting? And does the prospective talent pool differ in its composition than current game industry employees? Or are we attracting more of the same, trapped in a cycle like the one Anna Anthropy describes as “straight white developers [who] make games that straight white reviewers market to straight white players, who may eventually be recruited to become the new straight white developers and reviewers” (Anthropy 2012)?
A nice piece making the argument that we can’t fix the computing employment shortage without diversifying our labor pool.
I found this quote (further along from the quote and link below): ”Geeks often have a hostile relationship to formal education. Rather than sit through a pre-programmed curriculum with problems and solutions laid out in advance, geeks like to tinker and hack to solve new problems and innovate.” If that’s true (and I believe it is), why are geeks advancing MOOCs, which are as formal and pre-programmed as you can get?
Despite a deserved reputation for progressiveness, the tech sector is highly exclusionary to those who don’t fit the geek stereotype–and this tendency is getting worse, especially in Silicon Valley. You might have heard, based on 2011 numbers, that only 25 percent of the U.S. high tech workforce is female, and the percentages have been in steady decline since the nineties. The numbers for minority women are even more dismal. Hispanic women represent 1 percent of the high tech workforce, and African-American women don’t fare much better, at 3 percent. The better the jobs, the lower the proportions are of women and non-Asian minorities. Despite the diversity of the population of the region, Silicon Valley, which boasts the highest salaries among tech regions, fares much worse than the national numbers.
Way to go, Wendy! My Georgia Tech colleague did really well at a recent AAAS forum on MOOCs. The tone between the three speakers is striking. Anant Agarwal says “Hype is a good thing!” Kevin Wehrbach says that a MOOC is “an extraordinary teaching and learning experience.” Then Wendy Newstetter lets loose with concerns supported with citations and hard research questions.
In any learning environment, students should gain “transferable knowledge” that can be applied in many contexts, said Newstetter, citing a 2012 National Academies’ report on Education for Life and Work. Specifically, she said, researcher James Pellegrino has identified an array of cognitive, interpersonal and intrapersonal skills that all students need in order to succeed. How can the array of new online learning models help students achieve those goals?
Newstetter proposed a series of questions that should be answered by research. Educators need to know, for example, under what conditions technology-mediated experiences can result in enhanced learning competencies, she said. Do MOOCs effectively encourage students to develop perseverance, self-regulation and other such skills? Is knowledge gained in a MOOC “transferable,” so that what students learn can help them solve problems in other contexts? How can MOOCs be enhanced to promote interpersonal skills, and what intrapersonal attributes are needed for optimal learning in MOOCs?
Some observers have suggested that MOOCs tend to work best for more affluent students, Newstetter noted. She mentioned the 2013 William D. Carey lecture, presented at the AAAS Forum by Freeman Hrabowski III, president of the University of Maryland, Baltimore County, who focused on strategies for helping underrepresented minorities succeed in science fields. “What he described was high-contact, intensive mentoring,” she pointed out.
Diana Franklin has just published a new book with Morgan & Claypool, A Practical Guide to Gender Diversity for Computer Science Faculty. This is exciting to see. I can’t recommend it yet, just because I haven’t read it. What’s great is that it’s a book on how to teach computing — and there are just far too few of those. Other than the Logo books and the Guide to Teaching CS (from Orit Hazzan et al.), there’s not much to help new CS teachers. So glad that Diana has written this book!
Computer science faces a continuing crisis in the lack of females pursuing and succeeding in the field. Companies may suffer due to reduced product quality, students suffer because educators have failed to adjust to diverse populations, and future generations suffer due to a lack of role models and continued challenges in the environment. In this book, we draw on the latest research in sociology, psychology, and education to first identify why we should be striving for gender diversity (beyond social justice), refuting misconceptions about the differing potentials between females and males. We then provide a set of practical types (with brief motivations) for improving your work with undergraduates taking your courses. This is followed by in-depth discussion of the research behind the tips, presenting obstacles that females face in a number of areas. Finally, we provide tips for advising undergraduate independent projects or graduate students, supporting female faculty, and initiatives requiring action at the institutional level (department or above).
This is interesting to me both as an example of connecting Native American students with STEM education and as something cool that my alma mater is doing.
While attracting and retaining Native Americans has remained elusive due to a perceived lack of cultural relevance and/or support for STEM, Ferreira believes there is a way to break down this barrier.
“Native youth are taught to respect elders, and many elders are ‘keepers of traditional knowledge’ which interfaces with science,” said Ferreira. “Linking elders to postsecondary STEM education for Natives will improve perceptions of STEM as culturally relevant and culturally supportive of Natives, and impact Native student interest, pursuit and endurance in STEM careers.”
Congratulations to Juan Gilbert and his colleagues (see list) who have just launched a new NSF Broadening Participation in Computing Alliance, Institute for African-American Mentoring in Computing Sciences. This new alliance extends the work of multiple NSF BPC Alliances (A4RC, ARTSI, EL Alliance) and Demonstration Projects (AARCS) that utilized different strategies toward broadening the participation of African-Americans in computing sciences.
The National Science Foundation (NSF) has awarded Clemson University a $5 million grant to launch the Institute for African-American Mentoring in Computing Sciences.
The institute will serve as a national resource and emphasize mentoring as the primary strategy for increasing African-American participation in computing under the direction of Juan Gilbert, Presidential Endowed Professor and chairman of the Human-Centered Computing Division at Clemson, and Shaundra Daily, assistant professor in the School of Computing.
“African-Americans represent about 1 percent of the computer science faculty and researchers in the U.S.,” Gilbert said. “We formed this institute to increase the number of underrepresented groups earning computing science doctoral degrees and researchers in the academy, government and private sector.”
Farnam Jahanian visited Georgia Tech last month. Farnam is the Assistant Director at the US National Science Foundation, in charge of all computing related funding (CISE Division). He spoke to issues about computing education funding, and I got to ask some of my questions, too.
He said that the Office of Management and Budget has really been driving the effort to consolidate STEM education funding programs. OMB was unhappy that Biology, Engineering, and CISE all had their own STEM education programs. However, CISE got to keep their education research program (as the new STEM-C program) because it was already a collaboration with the education division in NSF (EHR). All the rest (including TUES) is being collapsed into the new EHR programs.
In his talk, he made an explicit argument which I’ve heard Jan Cuny make, but hadn’t heard an NSF AD make previously:
- We have a dramatic underproduction of computing degrees, around 40K per year.
- We have a dramatic under-representation of certain demographic groups (e.g., women, African-Americans, Hispanics), and we can’t solve #1 without solving that under-representation. He says that the basic arithmetic won’t work. We can’t get enough graduates unless we broaden participation in computing.
- We have a lack of presence in primary and secondary school in the United States (K-12). He claims that we can’t solve #2 without fixing #3. We have to have a presence so that women and under-represented minority groups will discover computing and pursue degrees (and careers) in it.
I’ve just started reading the new report, and I’m going to be recommending it often — lots of detail, connections to lots of literature, and useful synthesis. As usual, NCWIT does a great job with resources. They provide the report, and also a nice infographic and charts & graphs for others to use.
Girls in IT: The Facts, sponsored by NCWIT’s K-12 Alliance, is a synthesis of the existing literature on increasing girls’ participation in computing. It aims to bring together this latest research so that readers can gain a clearer and more coherent picture of 1) the current state of affairs for girls in computing, 2) the key barriers to increasing girls’ participation in these fields, and 3) promising practices for addressing these barriers.
On May 17, I am going to be attending a summit for computing education in Maryland at the University of Maryland, Baltimore County (UMBC). Rick Adrion and I are going to talk about the efforts in Massachusetts and Georgia, and elsewhere through ECEP. I’m looking forward to it (but observant readers will note that I’m traveling to Maryland the day after returning from Denmark!).
On Friday, May 17, 2013, CE21-Maryland will host a Summit for Computing Education at the University of Maryland, Baltimore County (UMBC) campus in Catonsville, Maryland. We invite teachers, administrators, legislators, industry leaders, and others who have an interest in expanding computer science in high school or middle school to attend. Space is limited to 150 people.
At this summit, the attendees will:
Learn more about computer science high school education across the state of Maryland.
Network with others with an interest in computer science education.
Exchange strategies with other education professionals.
Plan with others to help expand student interest and to increase the number and diversity of students studying computer science in Maryland.
We’ve heard stories like this before, about the implicit bias in how STEM professionals are judged. This one is striking because the participants are graduate students, not established researchers who reflect years of experience in the community. These are the new researchers, and they’re already biased.
The research found that graduate students in communication — both men and women — showed significant bias against study abstracts they read whose authors had female names like “Brenda Collins” or “Melissa Jordan.”
These students gave higher ratings to the exact same abstracts when the authors were identified with male names like “Andrew Stone” or “Matthew Webb.”
In addition, the results suggested that some research topics were seen as more appropriate for women scholars — such as parenting and body image — while others, like politics, were viewed as more appropriate for men.
These findings suggest that women may still have a more difficult time than men succeeding in academic science, said Silvia Knobloch-Westerwick, lead author of the study and associate professor of communication at The Ohio State University.
“There’s still a stereotype in our society that science is a more appropriate career for men than it is for women,” Knobloch-Westerwick said.
This theme has appeared here before. Why do Tech companies get to keep secret their lack of diversity?
OK, I’ll stipulate that tech companies get to fight tooth and nail to keep secret how awful they are at hiring women, blacks and Latinos.
And they do, according to CNN and the Mercury News.
But you know what? If they get to do that – as Facebook, LinkedIn, Netflix, Twitter, Yelp, Zynga, Amazon, Groupon, Hulu, LivingSocial, Apple, Google, Hewlett Packard, IBM and Microsoft have done – then we get to criticize them mercilessly.
My thinking on computing education has been significantly influenced by a podcast about hand-washing and financial illiteracy. I suspect that education is an ineffective strategy for achieving the goal of Computing Literacy for Everyone. I have a greater appreciation for work like Alan Kay’s on STEPS, Andy Ko’s work on tools for end-user programming, and the work on Racket.
On Hand-Washing and Financial Illiteracy
I have been listening to Freakonomics podcasts on long drives. Last month, I listened to “What do hand-washing and financial illiteracy have in common?” I listened to it again over the next few days, and started digging into the literature they cited.
At hospitals, hand-washing is far less common than our knowledge of germ theory says it ought to be. What’s most surprising is that doctors, the ones with the most education in the hospital, are the least likely to wash their hands often enough. The podcast describes how one hospital was able to improve their hand-washing rates through other behavioral methods, like shaming those who didn’t wash their hands and providing evidence that their hands were likely to be filled with bacteria. More education doesn’t necessarily lead to behavioral change.
Much more important was the segment on financial illiteracy. First, they present the work of Annamuria Lusardia who has directly measured the amazing financial illiteracy in our country. There is evidence that much of the Great Recession was caused by poor financial decisions by individuals. Less than a third of the over-50-year-old Americans that Lusardia studied could correctly answer the question, “If you put $100 in a savings account with 2% annual interest, at the end of five years you will have (a) less than $102, (b) exactly $102, or (c) more than $102?” More mathematics background did lead to more success on her questions, but she calls for a much more concerted effort in financial education. Her arguments are supported by some pretty influential officials, like Fed Reserve Chair Ben Bernanke and former Secretary of the Treasury Paul O’Neill. It makes sense: If people lack knowledge, we should teach them.
Lauren Willis strongly disagrees, and she’s got the data to back up her argument. She has a 2008 paper with the shocking title, Against Financial Literacy Education that I highly recommend. She presents evidence that financial literacy education has not worked — not that it couldn’t work, but it isn’t working. She cited several studies that showed negative effects of financial education. For example, high school students who participated in the Jump$start program become much more confident about their ability to make financial decisions, and yet made worse decisions than those students who did not participate in the program.
The problem is that financial decisions are just too complicated, and education (especially universal education) is expensive to do well (though Willis doesn’t offer an estimated cost). Educational curricula (even if tested successful) is not always implemented well. The gap between education in teen years and making decisions in your 40′s and 50′s is huge. Instead of education, we should try to prevent damage from ignorance. Willis suggests that we should create a cadre professional of financial advisors and make them available to everyone (for some “pro bono”), and that we should increase regulation of financial markets so that there are fewer riskier investments for the general public. It costs the entire society enormously when large numbers of people make poor financial decisions, and it’s even more expensive to provide enough education to prevent the cost of all that ignorance.
This was a radical idea for me. Education is not free, and sometimes it’s cheaper to prevent the damage of ignorance than correcting the ignorance.
Implications for Computing Literacy Education
I share the vision of Andy DiSessa and others of computing as a kind of literacy, and a goal of “Computing for All” where everyone has the knowledge and facility to build programs (for modeling, simulations, data analyses, etc.) for their needs. Let’s call that a goal of “Universal Computing Literacy,” and we can consider the costs of using education to reach that goal, e.g., “Universal Computing Education to achieve Universal Computing Literacy.”
The challenge of computing literacy may be even greater than the challenge of financial literacy. People know even less about computing than they do about finance. We don’t know the costs of that ignorance, but we do know that it has been difficult and expensive to provide enough education to correct that ignorance.
Computing may be even more complicated than finance. Willis talks about the myriad terms that people need to know to make good financial decisions (like “adjustable rate mortgages”), but they are at least compounds of English words! I attended a student talk this week, where terms like “D3” and “GreaseMonkey” were bandied about like they were common knowledge. We invent so much language all the time.
The problem is that education is often inefficient and ineffective. Jeremy Roschelle pointed out that education improvements rarely impact economic outputs. Greg Wilson shared a great paper with me in response to some tweets I sent about these ideas. Americans have always turned to education to solve a wide variety of ills, but surprisingly, without much evidence of efficacy. We can teach kids all about healthy eating, but we still have a lot of obesity. Smokers often know lots of details about how bad smoking is for them. Education does not guarantee a change of behavior. This doesn’t mean that education could not be made more effective and more efficient. But it might be even more expensive to fix education than to deal with ignorance.
Universal education is always going to be expensive, and some things are worth it. Text illiteracy and innumeracy are very expensive for our society. We need to address those, and we’re not doing a great job at that yet. Computing education to achieve real literacy is just not as important.
I am no longer convinced that providing computing education to everyone is going to be effective to reach the goal of making everyone computing literate, and I am quite convinced that it will be very expensive. Requiring computing education for STEM professionals at undergraduate level may still be cost-effective, because those are the professionals most likely to see the value of computing in their careers, which reduces the costs and makes the education more likely to be effective.
Barb sees a benefit in Universal Computing Education, but not to achieve Universal Computing Literacy. We need to make computing education available everywhere for broadening participation in computing. To get computing into every school, Barb argues that we have to make it required for everyone. Without the requirement, schools won’t go to the effort of including it. Without a requirement, female and URM students who might not see themselves in computing, would never even give it a chance. In response to my argument about cost, she argues that the computing education for everyone doesn’t have to be effective. We don’t have to achieve lifelong literacy for everyone. Merely, it has to give everyone exposure, to give everyone the opportunity to discover a love for computing. Those that find that love will educate themselves and/or will pursue more educational opportunities later. I heard Mike Eisenberg give a talk once many years ago, where he said something that still sticks with me: that the point of school is to give everyone the opportunity to find out what they’re passionate about. For that reason, we have to give everyone the chance to discover computing, and requiring it may be the only way to reach that goal.
It’s always possible that we’ll figure out to educate more effectively at lower cost. For example, integrating computing literacy education into mathematics and science classes may be cheaper — students will be using it in context, teachers in STEM are better prepared to learn and teach computing, and we may improve mathematics and science teaching along the way. My argument about being too expensive is based on what we know now how to do. Economic arguments are often changed by improved science (see Malthus).
As Willis suggests for financial literacy, we in computing literacy are probably going to be more successful for less cost by focusing on the demand side of the equation. We need to make computing easier, and make tools and languages that are more accessible, as Alan Kay, Andy Ko, and the Racket folks are doing. We have to figure out how to change computing so that it’s possible to learn and use it over an entire career, without a PhD in Computer Science. We have to figure out how to get these tools into use so that students see use of such tools as authentic and not a “toy.”
“Computing for All” is an important goal. “Access to Computing Education for All” is critical. “Universal Computing Education to achieve Universal Computing Literacy” is likely to be ineffective and will be very expensive. On the other hand, requiring computing education may be the only way to broaden participation in computing.
All these efforts to draw in more girls to computing are great, but the last sentence is a big deal. How do we keep them? How do we help girls to survive the thousand paper cuts?
Girls Who Code is among the recent crop of programs aiming to close the gender gap in tech by intervening early, when young women are deciding what they want to study. With names like Hackbright Academy, Girl Develop It, Black Girls Code and Girls Teaching Girls to Code, these groups try to present a more exciting image of computer science.
The dearth of women in the tech industry has been well documented. Even though women represent more than half the overall work force, they hold less than a quarter of computing and technical jobs, according to the National Center for Women and Information Technology based at the University of Colorado, Boulder. At the executive and founder levels, women are even scarcer.