Transcript Commonly Held Perceptions

Professional Practice and
Computing Curricula 2001
Eric Roberts
Professor of Computer Science
Senior Associate Dean of Engineering
Stanford University
CPHC
Milton Keynes
October 25, 2002
Computing Curricula 2001
(CC2001)
Charter: To review the Joint ACM and IEEE/CS Computing
Curricula 1991 and develop a revised and enhanced
version for the year 2001 that will match the latest
developments of computing technologies in the past
decade and endure through the next decade.
Final version of CS report released on December 15, 2001
http://www.computer.org/education/cc2001/
http://www.acm.org/sigcse/cc2001/
CC2001 Task Force
ACM
Education Board chair:
Peter Denning
Task Force co-chairs:
Eric Roberts ( editor)
Russ Shackelford
Steering committee members:
Richard Austing
Fay Cover
Gordon Davies
Andrew McGettrick
Michael Schneider
Ursula Wolz
IEEE Computer Society
VP for Education:
Carl Chang
Task Force co-chairs:
James Cross
Gerald Engel ( editor)
Steering committee members:
Doris Carver
Richard Eckhouse
Willis King
Francis Lau
Susan Mengel
Robert Sloan ( secretary)
Pradip Srimani
CC2001 Volumes
Computing Curricula 2001
Computing Curricula 2001
Computing Curricula 2001
Computing Curricula 2001
Computer Science
Computer Engineering
Softw are Engineering
Inf ormation Systems
The Joint Task For ce
on Computing Curr icula
The Joint Task For ce
on Computing Curr icula
IEEE Computer Society
Association for Computing Machiner y
IEEE Computer Society
Association for Computing Machiner y
The Joint Task For ce on
Software Eng ineeri ng Educati on
Project
(SWEEP)
Association for Computing Machiner y
IEEE Computer Society
Association for Information Systems
Computing Curricula 2001
Computing Curricula 2001
Tw o-Year Colleges
Overview
The Joint Task For ce
on Computing Curr icula
The Joint Task For ce
on Computing Curr icula
IEEE Computer Society
Association for Computing Machiner y
IEEE Computer Society
Association for Computing Machiner y
Coverage of Professional Practice in CC2001
Professional practice is addressed in the following sections of the
report:
• Chapter 5 (Principles)
• Chapter 9 (Completing the Curriculum)
• Chapter 10 (Professional Practice)
• Chapter 11 (Characteristics of CS Graduates)
• Chapter 12 (Computing across the Curriculum)
• Body of Knowledge areas SE and SP
Principle on Professional Practice
10. CC2001 must include professional practice as an integral
component of the undergraduate curriculum. These practices
encompass a wide range of activites including management,
ethics and values, written and oral communication, working as
part of a team, and remaining current in a rapidly changing
discipline. We further endorse the position articulated in the
CC1991 report that “mastery of the discipline includes not only
an understanding of basic subject matter, but also an
understanding of the applicability of the concepts to real-world
problems.”
—CC2001, Chapter 4 (Principles)
CC2001: General Requirements
• Mathematics
– Discrete mathematics
– Additional mathematics is required, but not constrained to calculus
• Science
– Students must be exposed to the scientific method
– Science training can come from a wide variety of fields
• Applications of computing
– All students must study some area that uses computing in a
substantive way
• Communications skills
– Writing
– Oral presentation
– Critiquing
• Working in teams
– Team work should begin early in the curriculum
– All students should engage in a significant team project
Top Ten Criteria for Employers
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Communication skills (verbal and written)
Honesty/integrity
Teamwork skills
Interpersonal skills
Motivation/initiative
Strong work ethic
Analytical skills
Flexibility/adaptability
Computer skills
Self-confidence
Assessing Professional Practice
• Outcomes-based assessment
• Reviewing assignments, projects, and exams for appropriate
inclusion of professional practice material
• Critically reviewing and establishing sound measurements on
student work to show student progress and improvement
• Getting students involved in the review and assessment process
so that they get a better sense of how it works
• Employing professionals in the private and public sectors to
help in assessing student project work
• Using standardized tests to measure overall student progress
• Taking post-graduation surveys of alumni to see how well
alumni thought their education prepared them for their careers
• Obtaining accreditation to demonstrate that certain education
standards for professional practice have been met
Characteristics of CS Graduates
Cognitive capabilities
Technical capabilities
Transferable skills
Knowledge and understanding
Modeling
Requirements
Critical evaluation and testing
Methods and tools
Professional responsibility
Design and implementation
Evaluation
Information management
Human-computer interaction
Risk assessment
Tools
Operation
Communication
Teamwork
Numeracy
Self management
Professional development
Information Technology is Different
• As an academic discipline, Information Technology (IT)
is different from most traditional fields.
• Policymakers who attempt to generalize from other
disciplines often make assumptions that turn out to be
wrong when applied to computing, particularly in those
subdisciplines requiring large-scale software development
efforts.
• Understanding these differences is essential to the the
task of formulating effective educational policy in the IT
domain.
Field-Specific Issues in CS Education
• The body of knowledge and the nature of practice change
more rapidly in Computer Science than in other fields.
• Computing faces chronic labor shortages in both industry
and academia.
• Individual variations in productivity are far greater in
computing disciplines than they are in most professional
areas.
Employment Patterns by Discipline
Fraction of professionals with degrees in that discipline:
Fraction of disciplinary graduates employed in that profession:
SOURCE: National Science Foundation/Division of Science Resources Statistics, SESTAT (Scientists
and Engineers Statistical Data System), 1999, as presented by Caroline Wardle at Snowbird 2002
Effects of Overproduction
Effects of Underproduction
Variation in Programmer Productivity
• In 1968, a study by Sackman, Erikson, and Grant revealed
that programmers with the same level of experience
exhibited variations of more than 20 to 1 in the time
required to solve particular programming problems.
• More recent studies [Curtis 1981, DeMarco and Lister
1985, Brian 1997] confirm this high variability.
• Many employers in Silicon Valley argue that productivity
variance is even higher today, perhaps as much as 100 to 1.
Conclusions
• We must make sure that education policy in Information
Technology is informed by knowledge of the discipline by
becoming involved in the policy-making process.
• We must increase the number of computer science graduates.
It will be impossible to satisfy all employers until we can
satisfy a larger fraction of the demand.
• At the same time, we must often make decisions on the basis of
capacity rather than demand.
• We must incorporate more professional practice into the
curriculum, but cannot provide do everything ourselves. Some
skills must be learned on the job.
• The CC2001 report can be useful in achieving these goals.
The End