Diversifying Computing: Its Contradictions And Challenges
Richard Tapia
Department of Computational and Applied Mathematics Center for Excellence and Equity in Education
CRA Snowbird Conference July 15, 2002
Diversifying Computing: Its Contradictions And Challenges Richard - - PowerPoint PPT Presentation
Diversifying Computing: Its Contradictions And Challenges Richard Tapia Department of Computational and Applied Mathematics Center for Excellence and Equity in Education CRA Snowbird Conference July 15, 2002 Outline 1. Motivating the need
CRA Snowbird Conference July 15, 2002
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The easy fix (importation of solutions).
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Source: National Science Board, Science and Engineering Indicators-2002
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Source: National Science Board, Science and Engineering Indicators-2002
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Source: National Science Board, Science and Engineering Indicators-2002
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Source: National Science Board, Science and Engineering Indicators-2002
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Source: National Science Board, Science and Engineering Indicators-2002
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Severe underrepresentation of minorities in science, engineering, mathematics, and technology.
Percent of the doctoral degrees in science, math, engineering, and technology earned by people of various races/ethnicities, 1977-1998.
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Very one-dimensional; yet many view them as fair. Very traditional – the question is not do they include bad
Gets worse as we go up the ladder – k-12, undergraduate,
Creativity – we value what we measure because we don’t
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Youth (especially minority) hold a negative view of
Value system for today’s youth dictated by society (city)
Lack of science and engineering role models that youth
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Closing gaps that are meaningless. Meaningless accountability. Very non-homogenous in terms of quality.
Selective schools – minority students migrate
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Selective schools – minority students not guided to
Minority serving institutions – often don’t give
Colleges and universities are not held accountable
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25.0 Computer Science 29.0 Mathematics 40.0 Mechanical Engineering and Material Science 40.0 Computational & Applied Mathematics 42.9 Electrical and Computer Engineering 48.6 Physics and Astronomy 56.0 Chemical Engineering 61.0 Biochemistry & Cell Biology 65.0 Chemistry 71.4 Ecology & Evolutionary Biology 71.4 Statistics
Percentage Department Name
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6 Possessing talent in the field of study 20 Hard workers 26 Under-prepared for graduate work 27 Lacking in research experience 27 Prepared for graduate work 34 Requiring a lot of time and effort 63 Preparation depends on quality of the undergraduate institution
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