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The Computer Science Pipeline and Diversity: Part 2 - Some positive signs, and looking towards the future
Thursday, July 09, 2015
Posted by Maggie Johnson, Director of Education and University Relations, Google
(
Cross-posted on the
Google for Education Blog
)
The disparity between the growing demand for computing professionals and the number of graduates in Computer Science (CS) and Information Technology (IT) has been highlighted in many
recent publications
. The tiny pipeline of diverse students (women and underrepresented minorities (URMs)) is even more troubling. Some of the factors causing these issues are:
The historical lack of STEM (Science, Technology, Engineering and Mathematics) capabilities in our younger students; lack of proficiency has had a substantial impact on the overall number of students pursuing technical careers. (
PCAST Stem Ed report, 2010
)
On the lack of girls in computing, boys often come into computing knowing more than girls because they have been doing it longer. This can cause girls to lose confidence with the perception that computing is a man’s world. Lack of role models, encouragement and relevant curriculum are additional factors that discourage girls’ participation. (
Margolis 2003
)
On the lack of URMs in computing, the best and most enthusiastic minority students are effectively discouraged from pursuing technical careers because of systemic and structural issues in our high schools and communities, and because of unconscious bias of teachers and administrators. (
Margolis, 2010
)
Over the last 3-4 years, however, we have seen some significant positive signals in STEM education in general, and in CS/IT in particular.
Math
1
and Science
2
results as measured by the National Assessment of Educational Progress (NAEP) have improved slightly since 2009, both in general and for female and minority students.
Over the last 10 years, there has been an increase in the number of students earning STEM degrees, but the news on women graduates is not as positive.
“Overall, 40 percent of bachelor's degrees earned by men and 29 percent earned by women are now in STEM fields. At the doctoral level, more than half of the degrees earned by men (58 percent) and one-third earned by women (33 percent) are in STEM fields. At the bachelor's degree level, though, women are losing ground. Between 2004 and 2014, the share of STEM-related bachelor's degrees earned by women decreased in all seven discipline areas: engineering; computer science; earth, atmospheric and ocean sciences; physical sciences; mathematics; biological and agricultural sciences; and social sciences and psychology. The biggest decrease was in computer science, where women now earn 18 percent of bachelor's degrees (18 percent). In 2004, women earned nearly a quarter of computer science bachelor's degrees, at 23 percent.”
- (
U.S. News, 2015
)
There has been a steady growth in investment in education companies, particularly those focused on innovative uses of technology.
The number of publications in
Google Scholar
on STEM education that focus on gender issues or minority students has steadily increased over the last several years.
Results from Google Scholar, using “STEM education minority” and “STEM education gender” as search terms
Successful marketing campaigns such as
Hour of Code
and
Made with Code
have helped raise awareness on the accessibility and importance of coding, and the diverse career opportunities in CS.
There has been growth in
developer bootcamps
over the last few years, as well as online “learn to code” programs (
code.org
,
CS First
,
Khan Academy
,
Codecademy
,
Blockly Games
,
PencilCode
, etc.), and an increase in opportunities for K12 students to
learn coding in their schools
. We have also seen non-profits emerge focused specifically on girls and URMs (
Technovation
,
Girls who Code
,
Black Girls Code
,
#YesWeCode
, etc.)
One of the most positive signals has been the growth of graduates in CS over the past few years.
Source:
2013 Taulbee Survey
,
Computing Research Association
So we are seeing small improvements in K-12 STEM proficiency and undergraduate STEM and CS degrees earned, a significant growth in investment in education innovation, more and more research on the issues of gender and ethnicity in STEM fields and increased opportunities for
all
students to learn coding skills online, through non-profit programs, through developer boot camps or in their schools.
However, an interesting, and potentially threatening development resulting from this positive momentum is the
lack of capacity and faculty
in CS departments to handle the increased number of enrollments and majors in CS. Colleges and universities, as a whole, aren’t adequately prepared to handle the surge in CS education demand - Currently there just aren’t enough instructors to teach all the students who want to learn.
This has happened in the past. In the 80’s, with the introduction of the PC, and again during the dot-com boom, interest in CS surged. CS departments managed the load by increasing class sizes as much as they possibly could, and/or they put enrollment caps in place and made CS classes harder. The effect of the former was some faculty left for industry while the effect of the latter was a decrease in the diversity pipeline.
“
These kinds of caps have two effects which limit access by women and under-represented minorities:
First, the students who succeed the most in intro CS are the ones with prior experience.
Second, creating these kinds of caps creates a perception of CS as a highly competitive field, which is a deterrent to many students. Those students may not even try to get into CS.”
-(
Guzdial, 2014
)
If we allow the past to repeat itself, we may again find CS faculty leaving for industry and less diversity students going into the field. In addition, unlike the dot-com boom where interest in CS plummeted with the bust, it’s unlikely we will see a decrease in enrollments, particularly in the introductory CS courses. “CS+X”, which represents the application of CS in other fields, is illustrated by the following sample list of interdisciplinary majors in various universities:
Yale: "Computer Science and Psychology is an interdepartmental major..."
USC: "B.S in Physics/Computer Science for students with dual interests..."
Stanford: "Mathematical and Computational Sciences for students interested in..."
Northeastern: "Computer Science/Music Technology dual major for students who want to explore connections between..."
Lehigh: "BS in Computer Science and Business integrates..."
Dartmouth: "The M.D.-Ph.D. Program in Computational Biology..."
The number of non-major students taking CS courses, particularly the introductory ones, is growing, which makes the capacity issues worse.
At Google, we recently funded a number of universities via our
3X3 award program
(3 times the number of students in 3 years), which aims to facilitate innovative, inclusive, and sustainable approaches to address these scaling issues in university CS programs. Our hope is to disseminate and scale the most successful approaches that our university partners develop. A positive development, which was not present when this happened in the past, is the recent innovation in online education and technology. The increase in bandwidth, high-quality content and interactive learning opportunities may help us get ahead of this challenging capacity issue.
1
Average mathematics scores for fourth- and eighth-graders in 2013 were 1 point higher than in 2011, and 28 and 22 points higher respectively in comparison to the first assessment year in 1990. Hispanic students made gains in mathematics from 2011 to 2013 at both grades 4 and 8. Fourth- and eighth-grade female students scored higher in mathematics in 2013 than in 2011, but the scores for fourth- and eighth-grade male students did not change significantly over the same period. (
Nation’s Report Card
)
2
The average eighth-grade science score increased two points, from 150 in 2009 to 152 in 2011. Scores also rose among public school students in 16 of 47 states that participated in both 2009 and 2011, and no state showed a decline in science scores from 2009 to 2011. A five-point gain from 2009 to 2011 by Hispanic students was larger than the one-point gain for White students, an improvement that narrowed the score gap between those two groups. Black students scored three points higher in 2011 than in 2009, narrowing the achievement gap with White students. (
Nation’s Report Card
)
The Computer Science Pipeline and Diversity: Part 1 - How did we get here?
Wednesday, July 08, 2015
Posted by Maggie Johnson, Director of Education and University Relations, Google
(
Cross-posted on the
Google for Education Blog
)
For many years, the Computer Science industry has struggled with a pipeline problem. Since 2009, when the number of undergraduate computer science (CS) graduates hit a low mark, there have been many efforts to increase the supply to meet an ever-increasing demand. Despite these efforts, the projected demand over the next seven years is significant.
Source:
2013 Taulbee Survey
,
Computing Research Association
Even if we are able to sustain a positive growth in graduation rates over the next 7 years, we will only fill 30-40% of the available jobs.
“By 2022, the computer and mathematical occupations group is expected to yield more than 1.3 million job openings. However, unlike in most occupational groups, more job openings will stem from growth than from the need to replace workers who change occupations or leave the labor force.”
-
Bureau of Labor Statistics Occupational Projection Report, 2012
.
More than 3 in 4 of these 1.3M jobs will require at least a Bachelor’s degree in CS or an Information Technology (IT) area. With our current production of only 16,000 CS undergraduates per year, we are way off the mark. Furthermore, within this too-small pipeline of CS graduates, is an even smaller supply of diverse - women and underrepresented minority (URM) - students. In 2013, only 14% of graduates were women and 20% URM. Why is this lack of representation important?
The workforce that creates technology should be representative of the people who use it, or there will be an inherent bias in design and interfaces.
If we get women and URMs involved, we will fill more than 30-40% of the projected jobs over the next 7 years.
Getting more women and URMs to choose computing occupations will reduce social inequity, since computing occupations are among the fastest-growing and pay the most.
Why are so few students interested in pursuing computing as a career, particularly women and URMs? How did we get here?
One fundamental reason is the lack of STEM (Science, Technology, Engineering and Mathematics) capabilities in our younger students. Over the last several years, international comparisons of K12 students’ performance in science and mathematics place the U.S. in the middle of the ranking or lower. On the National Assessment of Educational Progress,
less than one-third of U.S. eighth graders show proficiency in science and mathematics
. Lack of proficiency has led to lack of engagement in technical degree programs, which include CS and IT.
“In the United States, about 4% of all bachelor’s degrees awarded in 2008 were in engineering. This compares with about 19% throughout Asia and 31% in China specifically. In computer sciences, the number of bachelor’s and master’s degrees awarded decreased sharply from 2004 to 2007.”
-
NSF: Higher Education in Science and Engineering
.
The lack of proficiency has had a substantial impact on the overall number of students pursuing technical careers, but there have also been shifts resulting from trends and events in the technology sector that compound the issue. For example, we saw an increase in CS graduates from 1997 to the early 2000’s which reflected the growth of the dot-com bubble. Students, seeing the financial opportunities, moved increasingly toward technical degree programs. This continued until the collapse, after which a steady decrease occurred, perhaps as a result of disillusionment or caution.
Importantly, there are additional factors that are minimizing the diversity of individuals, particularly women, pursuing these fields. It’s important to note that there are no biological or cognitive reasons that justify a gender disparity in individuals participating in computing (
Hyde 2006
). With similar training and experience, women perform just as well as men in computer-related activities (
Margolis 2003
). But there can be important differences in reinforced predilections and interests during childhood that affect the diversity of those choosing to pursue computer science .
In general, most young boys build and explore; play with blocks, trains, etc.; and engage in activity and movement. For a typical boy, a computer can be the ultimate toy that allows him to pursue his interests, and this can develop into an intense passion early on. Many girls like to build, play with blocks, etc. too. For the most part, however, girls tend to prefer social interaction. Most girls develop an interest in computing later through social media and YouTubers, girl-focused games, or through math, science and computing courses. They typically do not develop the intense interest in computing at an early age like some boys do – they may never experience that level of interest (
Margolis 2003
).
Thus, some boys come into computing knowing more than girls because they have been doing it longer. This can cause many girls to lose confidence and drive during adolescence with the perception that technology is a man’s world - Both girls and boys perceive computing to be a largely masculine field (
Mercier 2006
). Furthermore, there are few role models at home, school or in the media changing the perception that computing is just not for girls. This overall lack of support and encouragement keeps many girls from considering computing as a career. (
Google white paper 2014
)
In addition, many teachers are oblivious to or support the gender stereotypes by assigning problems and projects that are oriented more toward boys, or are not of interest to girls. This lack of relevant curriculum is important. Many women who have pursued technology as a career cite relevant courses as critical to their decision (
Liston 2008
).
While gender differences exist with URM groups as well, there are compelling additional factors that affect them.
Jane Margolis
, a senior researcher at UCLA, did a study in 2000 resulting in the book
Stuck in the Shallow End
. She and her research group studied three very different high schools in Los Angeles, with different student demographics. The results of the study show that across all three schools, minority students do not get the same opportunities. While all of the students have access to basic technology courses (word processor, spreadsheet skills, etc.), advanced CS courses are typically only made available to students who, because of opportunities they already have outside school, need it less. Additionally, the best and most enthusiastic minority students can be effectively discouraged because of systemic and structural issues, and belief systems of teachers and administrators. The result is a small, mostly homogeneous group of students have all the opportunities and are introduced to CS, while the rest are relegated to the “shallow end of computing skills”, which perpetuates inequities and keeps minority students from pursuing computing careers.
These are some of the reasons why the pipeline for technical talent is so small and why the diversity pipeline is even smaller. Over the last two years, however, we are starting to see some positive signs.
Many students are becoming more aware of the relevance and accessibility of coding through campaigns such as
Hour of Code
and
Made with Code
.
This increase in awareness has helped to produce a steady increase in CS and IT graduates, and there’s every indication this growth will continue.
More opportunities to participate in CS-related activities are becoming available for girls and URMs, such as
CS First
,
Technovation
,
Girls who Code
,
Black Girls Code
,
#YesWeCode
, etc.
There’s much more that can be done to reinforce these positive trends, and to get more students of all types to pursue computing as a career. This is important not only to high tech, but is critical for our nation to compete globally. In the next post of this series, we will explore some of the positive steps that have been taken in increasing the diversity of graduates in Computer Science (CS) and Information Technology (IT) fields.
What we can learn about effective, meaningful and diverse organizations
Thursday, December 04, 2014
Posted by Beryl Nelson, Software Engineering Manager
By becoming more conscious of our own stereotypes and biases, and making use of the insights revealed by the research on bias and stereotype threat, unconscious decision making, and cognitive illusions, each of us can bring more to our work and create diverse, innovative, and meaningful organizations.
Since 2009, I’ve been reading literature about the challenges and successes in making diverse teams effective, and speaking about this research. My goal is to help everyone understand more about unconscious decision-making and other barriers to inclusion, and through knowledge, combat these effects.
A short summary:
A team that is heterogeneous in meaningful ways is good for innovation, and good for business.
There are many challenges to making such teams effective, such as unconscious decision making, stereotype threat, and other cognitive illusions.
There is repeatable quantitative research which shows ways to combat some of these effects.
The barriers to effectiveness may seem overwhelming, but there is hope! Meaningful change is possible, and some examples of successful change are cited below.
In a bit more detail:
Diversity is good for innovation and business.
There is a correlation between financial success and the diversity of leadership teams, as shown in research by
Catalyst
,
McKinsey
and
Cedric Herring
. Further, research shows a
strong correlation between having women on teams and innovation
; concluding that there is a strong correlation between the presence of women and the social skills required to get ideas percolating into the open.
We all make decisions unconsciously, influenced by our implicit associations.
As an example of these effects,
a large proportion of CEOs are taller than the average population
and
height is strongly correlated with financial and career success
. It’s long been argued that women and underrepresented minorities are not represented in CEO leadership because there aren’t enough qualified individuals in the labor pool. This “pipeline issue” argument can’t be made for short and average-height people, however. Simple,
repeatable tests
measure, via response time and error rate, the implicit associations we have between concepts. These associations are created as an adaptive response, but we must understand our own implicit biases in order to make better decisions.
Stereotype threat plays a role in preventing people from being fully effective.
The
low representation of women and minorities in Science
has long been the source of a troubling question: is this an indication of a difference in innate ability (see
Ben Barre’s response
to Lawrence Summers’ remarks), or the result of some other effect?
Claude Steele
and his colleagues elegantly showed that
two groups of people can have similar or opposite reactions, depending on the way a situation is presented
. These and other experiments show that stereotype threat can compromise the performance of the subject of a stereotype, if he or she knows about the stereotype and cares about it.
Change is possible.
The above and other challenges may make it seem nearly impossible to create a diverse and highly functioning organization, but dramatic change can be made. Take, for example, the discovery of biased decision making and effective changes made via the use of data in the
MIT Science Faculty Study
, or the amazing changes at
Harvey Mudd college
, which not only increased participation of women as Computer Science majors from 12% to 40% in five years, but also increased the total number of CS majors from 25 to 30 per year to 70 CS graduates in the class of 2014.
If you’re interested in learning more, watch the video about the data on diversity below. You can read the full
research
in the
November issue of Communications of the Association of Computing Machinery
. You can read even more using the
full bibliography
.
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