Posts tagged ‘BPC’

How the Imagined “Rationality” of Engineering Is Hurting Diversity — and Engineering

Just a few weeks ago, Richard Thaler won the Nobel prize in Economics. Thaler is famous for showing that real human beings are not the wholly rational beings that Economic theory had previously assumed.  It’s timely to consider where else we assume rationality, and where that rational assumption may lead us into flawed decisions and undesirable outcomes.  The below article from Harvard Business Review considers how dangerous the Engineering “purity” argument is.

Just how common are the views on gender espoused in the memo that former Google engineer James Damore was recently fired for distributing on an internal company message board? The flap has women and men in tech — and elsewhere — wondering what their colleagues really think about diversity. Research we’ve conducted shows that while most people don’t share Damore’s views, male engineers are more likely to…

But our most interesting finding concerned engineering purity. “Merit is vastly more important than gender or race, and efforts to ‘balance’ gender and race diminish the overall quality of an organization by reducing collective merit of the personnel,” a male engineer commented in the survey. Note the undefended assumption that tapping the full talent pool of engineers rather than limiting hiring to a subgroup (white men) will decrease the quality of engineers hired. Damore’s memo echoes this view, decrying “hiring practices which can effectively lower the bar for ‘diversity’ candidates.”

Google and taxpayer money, Damore opines, “is spent to water only one side of the lawn.” Many male engineers in our survey agreed that women engineers are unfairly favored. “As regards gender bias, my workplace offers women more incentives and monetary support than it does to males,” commented one male engineer. Said another, women “will always be safe from a RIF [reduction in force]. As well as certain companies guaranteeing female engineers higher raises.”

Source: How the Imagined “Rationality” of Engineering Is Hurting Diversity — and Engineering

December 11, 2017 at 7:00 am 1 comment

NSF funds FLIP Alliance to diversify CS professoriate #CSEdWeek

This is an exciting new project from Valerie Taylor (University of Chicago), Charles Isbell (Georgia Tech), and Jeffrey Forbes (Duke University). It’s based on an observation that Charles has made before, that we can diversify CS faculty by impacting just a handful of schools.

The goal of the NSF-funded FLIP (Diversifying Future Leadership in the Professoriate) Alliance is to address the broadening participation challenge of increasing the diversity of the future leadership in the professoriate in computing at research universities as a way to achieve diversity across the field.  In particular, the problem that we address is stark and straightforward: only 4.3% of the current tenure-track faculty in computing at these universities are from underrepresented groups.

The FLIP Alliance solution is equally stark and straightforward: we intentionally bring together the very small number of departments responsible for producing the majority of the professoriate with individuals and organizations that understand how to recruit, retain, and develop students from underrepresented groups in order to create a network that can quickly and radically change the demographic diversity of the professoriate across the entire field.

from CMD-IT FLIP Alliance

December 7, 2017 at 7:00 am 5 comments

US National Academics Report Investigates the Growth of CS Undergraduate Enrollments #CSEdWeek

The new National Academies report on the growth of CS undergraduate enrollments came out last month. It’s important because it reflects the recommendations of scholars across disciplines in dealing with our enormous enrollment growth (see Generation CS report for more findings on the surge).

I wrote about this report in my Blog@CACM post for this month, The Real Costs of a Computer Science Teacher are Opportunity Costs, and Those Are Enormous.  The report talks about how hard it is to hire new faculty to deal with the enrollment boom, because the Tech industry is increasing its share of new PhD’s and recruiting away existing faculty.

Eric Roberts at Stanford was part of the report writing, and points out that the committee did not reach agreement that there is a problem with participation by underrepresented minorities. Quoting Eric’s message to SIGCSE-members, “the committee did not find comparable evidence that departmental limitations have historically had a negative effect on participation by underrepresented minorities. In fact, the total number of degrees awarded to students in the largest of the underrepresented demographic groups (African American and Latino/Latina) has roughly matched the percentages at which students from those communities obtain bachelor’s degrees.”  It’s surprising, and Eric’s note goes on to explain why that result is so concerning. The report does say clearly, “Institutions should take deliberate actions to support diversity in their computer science and related programs.”

Since 2006, computer science departments in the U.S and Canada have experienced a surge in the number of undergraduate majors and course enrollments. The resulting strain on departmental and institutional resources has been significant for many departments, especially with respect to faculty hiring and overall workload. The National Academy of Sciences (NAS) has recently addressed the issue with the release a report titled “Assessing and Responding to the Growth of Computer Science Undergraduate Enrollments.”

The NAS report discusses strategies central for managing enrollment and resources, and makes recommendations for departments and institutions. Its findings and recommendations provide much-needed guidelines on how institutions can allocate resources to meet growing student demand and to adequately support their computer science department in the increasingly central role of computer science in education and research. “The way colleges and universities respond to the surge in student interest and enrollment can have a significant impact on the health of the field,” said Susanne Hambrusch, co-chair of the report’s committee and a professor of computer science at Purdue University.  “While there is no one-size-fits-all answer, all institutions need to make strategic plans to address realistically and effectively the growing demand for the courses.”

Source: NAS Report Investigates the Growth of Computer Science Undergraduate Enrollments

December 6, 2017 at 7:00 am 1 comment

Is (Scaled) Online Learning an Engine for Diversity? Not according to the data

There are lots of women and minority students in online CS. Numbers are high. Proportions are low.  Reach (what percentage of women and minority get access to online CS) is low.  Diversity in terms of economic success is low (as discussed in this blog post and in this one too), so scaled online learning is unlikely to be an engine to bridge economic divides.  There are a large number of (rich) female and minority students in the OMS CS populations (higher numbers but lower proportion than in our face-to-face MS CS program), but if they remain a small proportion of the whole and the reach is low, then not much is changing. The graduate pool and the Tech industry over all does not become more diverse.

If Georgia Tech is indeed able leverage scaled online learning to graduate underrepresented minorities at much higher rates than comparable residential programs, then it seems that all of us in higher ed should be taking notice. I remain skeptical that an online degree program that is not built around intensive interaction, mentoring, and coaching between faculty and students can be successful.  Going to scale in order to drive down the costs seems to require a transactional, rather than relational, approach to teaching and learning.

Source: Is (Scaled) Online Learning an Engine for Diversity? | Technology and Learning

October 27, 2017 at 7:00 am Leave a comment

Why Tech Leadership May Have a Bigger Race Than Gender Problem

The Wired article linked below suggests that race is an even bigger issue than gender in Tech industry leadership.  While Asians are over-represented in the Tech labor force, they are under-represented in Tech leadership, even more than women.  I was somewhat surprised that this article considers “Asians” so generally.  The most-often visited blog post I’ve written is the one that shows the differential success rates of different Asian populations in US educational attainment (see post here).

Gee says this study came about because an earlier report in 2015 that used EEOC data from companies like Google and LinkedIn ended up on the desk of Jenny Yang, the outgoing commissioner of the EEOC. Yang asked if the lower proportion of Asian executives was the result of discrimination and might be applicable for lawsuits, Gee says. He told her no. “We have never seen any overt discrimination or policies that create these disparities,” Gee explains. Rather, after conversations with 60 or 70 Asian executives, the authors say they noticed a pattern of cultural traits among some Asians that did not align with leadership expectations in Western corporate culture, such as risk-taking and being confrontational.

Gee gave the example of an executive who started the first Asian affinity group at Intel decades ago. He noticed that Chinese engineers were unhappy and not succeeding in Intel’s culture of “constructive conflict,” which involved heated debates during meetings.

“Some people call it unconscious bias. For Asians, it’s actually a very conscious bias,” says Gee. Studies show that assumptions that Asians are good at math, science, and technology make it easier for them to get in the door, but the same bias is reversed when it comes to leadership roles, he says.

Source: Why Tech Leadership May Have a Bigger Race Than Gender Problem | WIRED

October 23, 2017 at 7:00 am 1 comment

Why should we teach programming (Hint: It’s not to learn problem-solving)

This is a revision of the original post. Several readers pointed out on Twitter that my original post was insensitive. It read like an attack on Brenda, a woman of color, from a senior white guy (me). That was not my intent, and I apologize for that. I am grateful to Joseph P. Wilson who helped me understand how to avoid that impression. I can’t change the post that went out yesterday, but I will be more careful in future blog posts.


At the CS for All Consortium Celebration Tuesday, Brenda Wilkerson gave the closing keynote. The full livestream of the CS for All Summit is available here, and it includes Brenda’s talk. I’m a huge fan of Brenda, and she’s done fabulous work in Chicago. She is a leader in bringing CS to All.

I have not seen Brenda’s talk or any of the livestream. My experience of the Consortium Celebration was through reading the Twitter stream as I found time during the day. Brenda had one slide (which you can see in the tweet linked here) that I disagreed with, and because it’s an important point, I’m going to respond to it here.

It says, “Computer science builds the mental discipline for breaking down problems, and solving them.” There are few studies that test this claim as “computer science,” but there have been lots of studies looking for transfer from teaching programming to general problem-solving skills. Probably the first study investigating this claim is Roy Pea and Midian Kurland’s paper On the cognitive effects of learning computer programming. You can find this claim in a paper by Henry Walker to which I responded in this blog. You can see it in posts all over the Internet, from this blog post to this article from a teacher in England. There is a strong belief out there that learning computer science, and programming called out specifically, leads to new problem-solving and “a new way to think.”

There is simply not evidence in support of these claims. I talk about these in my book, I reference the Palumbo meta-review in this blog post, and NYTimes wrote about it this last spring. Like “learning styles” and “Latin teaches thinking,” this is a persistent myth that learning computing leads to problem-solving skills, and we have no support the claim.

I tweeted in response to Brenda’s slide, and several CS teachers asked me, “So why teach programming or computing at all?”  That’s a great question!  Here are some of my top reasons:

  1. To understand our world. The argument that Simon Peyton Jones made in England for their computer science curriculum is that Computer Science is a science like all the others. We teach Chemistry to students because they live in a world with chemical interactions. We teach Biology because they live in a world full of living things. We teach Physics because they live in a physical world. We should teach Computer Science because they live in a digital world.
  2. To study and understand processes. Alan Perlis (first ACM Turing Award laureate) argued in 1961 that everyone on every campus should learn to program. He said that computer science is the study of process, and many disciplines need people to know about process, from managers who work on logistics, to scientists who try to understand molecular or biological processes. Programming automates process, which creates opportunities to simulate, model, and test theories about processes at scale. Perlis was prescient in predicting computational science and engineering.
  3. To be able to ask questions about the influences on their lives. C.P. Snow also argued for everyone to learn computing in 1961, but with more foreboding. He correctly predicted that computers and computing algorithms were going to control important aspects of our lives. If we don’t know anything about computing, we don’t even know how to ask about those algorithms. It shouldn’t be magic.  Even if you’re not building these algorithms, simply knowing about them gives you power. C.P. Snow argues that you need that power.
  4. To use an important new form of literacy. Alan Kay made the argument in the 1970’s that computing is a whole new medium. In fact, it’s human’s first meta-medium — it can be all other media, and it includes interactivity so that the medium can respond to the reader/user/viewer. Computing gives us a new way to express ideas, to communicate to others, and to explore ideas.  Everyone should have access to this new medium.
  5. To have a new way to learn science and mathematics. Mathematics places a critical role in understanding our world, mostly in science. Our notation for mathematics has mostly been static equations. But code is different and gives us new insights. This is what Andy diSessa has been saying for many years. Bruce Sherin, Idit Harel, Yasmin Kafai, Uri Wilensky, and others have shown us how code gives us a powerful new way to learn science and mathematics. Bootstrap explicitly teaches mathematics with computing.  Everyone who learns mathematics should also learn computing, explicitly with programming.
  6. As a job skill. The most common argument for teaching computer science in the United States is as a job skill.  The original Code.org video argued that everyone should learn programming because we have a shortage of programmers. That’s just a terrible reason to make every school child learn to program. That’s what Larry Cuban was arguing this last summer. Tax payers should not be funding a Silicon Valley jobs program. Not everyone is going to become a software developer, and it doesn’t make any sense to train everyone for a job that only some will do. But, there’s some great evidence from Chris Scaffidi (that I learned about from Andy Ko’s terrific VL/HCC summary) showing that workers (not software developers) who program make higher wages than those comparable workers who do not. Learning to program gives students new skills that have value in the economy. It’s a social justice issue if we do not make this economic opportunity available to everyone.
  7. To use computers better. This one is a possibility, but we need research to support it. Everyone uses computers all the time these days. Does knowing how the computer works lead to more effective use of the computer?  Are you less likely to make mistakes? Are you more resilient in bouncing back from errors? Can you solve computing problems (those that happen in applications or with hardware, even without programming) more easily?  I bet the answer is yes, but I don’t know the research results that support that argument.
  8. As a medium in which to learn problem-solving. Finally, computer programming is an effective medium in which we can teach problem-solving. Just learning to program doesn’t teach problem-solving skills, but you can use programming if you want to teach problem-solving. Sharon Carver showed this many years ago. She wanted students to learn debugging skills, like being able to take a map and a set of instructions, then figure out where the instructions are wrong. She taught those debugging skills by having students debug Logo programs. Students successfully transferred those debugging skills to the map task. That’s super cool from a cognitive and learning sciences perspective. But her students didn’t learn much programming — she didn’t need much programming to teach that problem solving skill.But here’s the big caveat: They did not learn enough programming for any of the other reasons on this list!  The evidence we have says that you can teach problem-solving with programming, but students won’t gain more than that particular skill. That is a disservice to students.

Certainly there are more reasons than these, and I’ve seen several in the response to this blog post, and some in the comments below.

This was just one slide in Brenda’s talk. Her overall point was much more broader and more significant. I strongly agree with Brenda’s key point: CS for All is a social justice issue. Learning computing is so important that it is unjust to keep it from some students. Currently, CS is disproportionately unavailable to poorer students, to females, and to minority ethnic groups. We need CS for All.

October 18, 2017 at 12:30 pm 12 comments

Study says multiple factors work together to drive women away from STEM

I wrote recently in a blog post that we don’t know enough why women aren’t going into computing, and I wrote in another blog post that CRA is finding that we lose women over the years of an undergraduate degree in CS.  Here’s an interesting study offering explanations for why we are not getting and keeping women:

The study analyzed a large, private university on the East Coast, using data from 2009-16, broken down semester-by-semester to track students’ changes in grades and majors in as close to real time as possible. While other studies have suggested that women came out of high school less prepared, or that increasing female STEM faculty could help provide women mentors, the Georgetown study didn’t support those findings.

“Women faculty don’t seem to attract more women into a field, and that was sort of sad news for us,” Kugler said. “We were hoping we could make more of a difference.”

One of the reasons women might feel undue pressure in STEM fields might actually be because of how recruiting and mentoring is framed. Many times, those efforts actually end up reinforcing the idea that STEM is for men.“Society keeps telling us that STEM fields are masculine fields, that we need to increase the participation of women in STEM fields, but that kind of sends a signal that it’s not a field for women, and it kind of works against keeping women in these fields,” Kugler said.

And while many STEM majors are male-dominated, the framing of recruitment and mentorship efforts can sometimes paint inaccurate pictures for STEM fields that aren’t male-dominated, and contribute to an inaccurate picture for STEM as a whole, the paper says:

While men may not have a natural ability advantage in STEM fields, the numerous government and other policy initiatives designed to get women interested in STEM fields may have the unintended effect of signaling to women an inherent lack of fit.

While computer science, biophysics and physics tend to be male-dominated, Kugler said, neurobiology, environmental biology and biology of global health tend to be female-dominated.

Source: Study says multiple factors work together to drive women away from STEM

October 13, 2017 at 7:00 am 1 comment

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