The Pipeline Crisis in Computing

1
The Pipeline Crisis in Computing
Taking the Initiative
SIGCSE 2007 Symposium Covington, Kentucky March
9, 2007
Eric Roberts Professor of Computer Science,
Stanford University Co-chair of the ACM Education
Board
2
Reframing the Issue

• All too often, those of us who teach computing
  have looked at the declining interest in the
  discipline as an enrollment crisis.

• This characterization is self-defeating and makes
  it harder to attract allies to our cause.
• In a typical university, every department wants
  to increase its enrollment, and we become merely
  another player in a parochial game of resources.
• The real concern is that we have a pipeline
  crisis in that we are producing far too few
  graduates to fill the growing number of positions
  that require computing skills. Judging by
  demand, we were producing too few graduates even
  at the top of the boom.
• Failure to respond to the pipeline crisis will
  place significant constraints on the computing
  industry and compromise national competitiveness.

3
The Looming Pipeline Crisis

• The Bureau of Labor Statistics projects much
  faster growth in computing employment than in
  other science/engineering areas.

4
A Graphic Indicator of the Shortage
Graphic created by Greg Lavender at the
University of Texas.
5
Economic Utility of Disciplinary Degrees
Working in the life sciences typically requires a
degree in biology or some closely related field,
but relatively few biology majors actually end up
working in the field.

• 80 of workers in the life sciences have degrees
  in the life sciences.

6
Economic Utility of Disciplinary Degrees
In computing, the pattern of degree production
vs. employment is reversed.

• 39 of workers in computing have degrees in
  computing.

These data suggest a significant underproduction
of students with computing degrees at the
university level.
7
Why Other Sciences Should Be Concerned
Though the information technology-powered
revolution is accelerating, this country has not
yet awakened to the central role played by
computational science and high-end computing in
advanced scientific, social science, biomedical,
and engineering research defense and national
security and industrial innovation. Together
with theory and experimentation, computational
science now constitutes the third pillar of
scientific inquiry, enabling researchers to build
and test models of complex phenomenasuch as
multi-century climate shifts, multidimensional
flight stresses on aircraft, and stellar
explosionsthat cannot be replicated in the
laboratory, and to manage huge volumes of data
rapidly and economically. . . .
8
What We Need To Do

• Develop greater understanding of the reasons
  behind the decline in student interest in
  computing disciplines.

• Forge alliances with individuals and groups in
  other disciplines to bring new voices into the
  discussion.
• Increase public awareness of the range of
  opportunities.
• Press government and industry to support
  computing education.
• Expand efforts to increase diversity.
• Encourage experimentation in curricular
  strategies.
• Develop tools and materials that can be used off
  the shelf.
• Improve distribution channels for best practices.
• Promote interdisciplinary curricular connections.
• As Grady Booch encouraged us this morning, help
  students rediscover the passion, beauty, joy,
  and awe of software

9
Reasons for the Decline
10
Changes in Student AttitudesorWhy Students No
Longer Like Programming
For much of our fields history, programming was
the most popular aspect of the major. That seems
to have changed.

• Students have adopted over time an increasingly
  instrumental attitude toward education.
• For many students, opportunities for wealth are
  more attractive than simply having good prospects
  for a high-paying job.
• A factor analysis by my colleague Mehran Sahami
  revealed an 88 correlation between the number of
  CS majors at Stanford and the average level of
  the NASDAQ the year before.
• Students are primarily choosing careers that they
  perceive to fall on the capital side of the
  capital/labor divide. Despite the fact that
  software development is highly paid, it is
  generally viewed as labor.

11
Some Encouraging Signs
Matt Jacobsen, Senior, UC Berkeley
A common misconception is that many people think
CS means sitting in front of a computer all day
long. This may often be the case for programming,
but CS is a large field. There are many
applications that require CS skills that involve
little or no programming. . . .
From Dan Garcias Faces of CS web site.
12
More Encouraging Signs

• Many large universities have reported significant
  increases in enrollments this year. Some have
  recovered much of the loss from the past five
  years.

13
The Growing Challenge of High School CS

• People who have software development skills
  command high salaries and tend not to teach in
  high schools for very long.

• In many schools, computing courses are seen as
  vocational rather than academic. The NCAA, for
  example, no longer accepts computer science
  courses for academic eligibility.
• Students who are heading toward top universities
  are often advised to take courses other than
  computer science to bolster their admissions
  chances.
• Because schools are evaluated on how well their
  students perform in math and science, many
  schools are shifting teachers away from computer
  science toward these disciplines.
• Teachers have very few resources to keep abreast
  of changes in the field.

14
CS is Losing Ground in the AP Exam

• The Computer Science exam is the only Advanced
  Placement exam that has shown declining student
  numbers in recent years.

15
CS Is Tiny Compared with Other Sciences
16
Computing Is Getting Harder
Many faculty in our discipline believe that
teaching computing has become more difficult.
The contributing factors include

• Complexity. The number of programming details
  that students must master has grown much faster
  than the corresponding number of high-level
  concepts.

• Instability. The rapid evolution of the field
  creates problems for computing education that are
  qualitatively different from those in most fields.

Concern over these has sparked several
initiatives including the ACM Java Task Force.
17
Positive Initiatives

• The National Science Foundation sponsored four
  regional conferences on Integrated Computing and
  Research (ICER) and launched the new Computing
  Pathways (C-PATH) initiative.

• Several ACM Education Board projects are proving
  helpful
• A brochure for high-school students
• The CC2001 series of curriculum reports
• The Computer Science Teachers Association
• A community effort to develop Java tools (the ACM
  Java Task Force)
• There are many interesting ideas in the community
  that are showing promise
• Mark Guzdials media computation strategy at
  Georgia Tech
• Stuart Regess back to basics strategy at the
  University of Washington
• Jeannette Wings computational thinking
  concepts
• Interdisciplinary curricula at a variety of
  schools
• The many efforts to enhance diversity from so
  many people
• All the good ideas that come out here at SIGCSE

18
Dangers on the Horizon
We have met the enemy and he is us.

Walt Kelly
Unfortunately, the sense of crisis in recent
years carries with it the risk that our community
will adopt desperate measures that are
self-defeating in the long run

• Engaging in resource competition with fields that
  should be our allies in seeking to increase
  support of science and technology.
• Changing our curricula in ways that might
  increase the number of students but will not meet
  the needs of their eventual employers. Every
  technical person in the industry with whom Ive
  spoken is horrified by the prospect of reducing
  the emphasis on programming in the undergraduate
  curriculum.
• Losing hope in the darkness before the dawn.
  Enrollments are already recovering in many
  institutions. This too shall pass, but only if
  we keep the faith and make it happen.

19
A Thought Experiment about Offshoring

• Suppose that you are Microsoft and that you can
  hire a software developer from Stanford whose
  loaded costs will be 200,000 per year. Over in
  Bangalore, however, you can hire a software
  developer for 75,000 per year. Both are equally
  talented and will create 1,000,000 annually in
  value. What do you do?

• Although the developer in Bangalore has a higher
  return, the optimal strategy is to hire them
  both. After all, why throw away 800,000 a year?
• Any elementary economics textbook will explain
  that one hires as long as the marginal value of
  the new employee is greater than the marginal
  cost. The essential point is that companies seek
  to maximize return, and not simply to minimize
  cost.

20
The End