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Gender and Technology

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Physical therapist assistants 26 44. Dental hygienists 68 43 ... Dental assistants 114 43. Personal and home care aides 287 41 ... – PowerPoint PPT presentation

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Title: Gender and Technology


1
Gender and Technology
  • Elaine Rich
  • Dept. of Computer Sciences

2
Males and Females are Different
  • The Womens Health Initiative
  • http//www.nhlbi.nih.gov/whi/whywhi.htm
  • Games and entertainment
  • http//www.microsoft.com/windowsxp/using/games/le
    arnmore/womeningames.mspx
  • Communication styles
  • http//www.cs.utexas.edu/ear/JustTannenPart.ppt

3
Is Inequity a Problem?
  • Women buy more jewelry than men do. Is this a
    problem?

4
No, but it is for computing
  • The consumer perspective Do women reap equal
    benefits from technology?
  • The good jobs perspective
  • The pipeline effect on our economy perspective.
    Is global competitiveness at stake?

5
The Consumer Perspective
  • Are women taught to use computing?
  • Is technology marketed to women?
  • Is technology designed for women?

6
Teaching Computing to Girls
  • 16 of students who take the AP CS exam are
    girls.
  • The learning environment is key.
    http//www.ao.uiuc.edu/ijet/v1n1/bain/index.html
  • And all-girls robotics clubs are taking off.

7
Advertising
  • http//www.utpjournals.com/jour.ihtml?lpsimile/is
    sue21/johnson1.html

8
Technology Advertising
Time for Casio to Grow Up DisGraceful Award for
March 13, 2001 ad.
9
Software Advertising
October 2002 GraceNet Award scooped by Peter
deLevett, reporter for the San Jose Mercury News.
10
Gender-Matched Software
  • Gender neutral looks a lot like the male version
  • Stress at using other software increases in
    public settings
  • Correlated with expectations of success vs.
    failure
  • See Huff paper

11
The Jobs Perspective
From Bureau of Labor Statistics Employment
change 2004-2014 (in 1000s)
Home health
aides 350
56 Network systems and data
communications analysts 126 55
Medical assistants
202 52 Physician assistants
31 50
Computer software engineers, applications
222 48 Physical therapist
assistants 26 44
Dental hygienists
68 43 Computer
software engineers, systems software 146
43 Dental assistants
114 43 Personal and home care
aides 287 41 Network
and computer systems administrators 107
38 Database administrators
40 38 Physical therapists
57
37 Forensic science technicians
4 36
12
The Jobs Perspective
Veterinary technologists and technicians
21 35 Diagnostic medical sonographers
15 35 Physical
therapist aides
15 34 Occupational therapist assistants
7 34 Medical
scientists, except epidemiologists
25 34 Occupational therapists
31 34 Preschool teachers,
except special education 143 33
Cardiovascular technologists and technicians
15 33 Postsecondary teachers
524
32 Hydrologists
3 32 Computer systems
analysts 153
31 Hazardous materials removal workers
12 31 Biomedical engineers
3
31 Employment, recruitment, and placement
specialists 55 30 Environmental
engineers 15
30 Paralegals and legal assistants
67 30
13
Who Will Fill Those Jobs?
  • Either we will.
  • Or someone else will.

14
Who Designs and Builds Computer Technology?
  • Attracting students to study it
  • Retaining students
  • Career paths

15
A Bit of History
1945 ENIAC The first electronic digital
computer
16
The Early Programmers
  • The women of the Eniac
  • Grace Murray Hopper

17
Rear Admiral Grace Murray Hopper, USNR,
(1906-1992)
The first compiler The high-level programming
language Cobol A computer bug
http//www.jamesshuggins.com/h/tek1/first_compute
r_bug_large.htm
18
Some Trends
  • Women studying CS in the US peaked in about 1983.
    The number has declined since then, while other
    measures of womens academic achievements have
    increased.

19
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20
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21
The Rest of the World
Country women Year
Botswana 10 1998
Nigeria 31 1997
South Africa 32 1998
India 20 2002
Iran 41 1999
Malaysia 51 1991
Germany 10 2000
Iceland 24 2000
Spain 25 1998
Mexico 39 1999
22
Why Have the US Numbers Gone Down?
  • Games attract boys The Turing Scholars evidence.
  • High school students think they know what
    computing is about (and who is supposed to do
    it).
  • Its solitary.
  • It doesnt benefit society.
  • Its for boys.
  • Its for geeks.
  • Not cool.
  • Dont have other interests.
  • The self-confidence factor.

23
Women Students the CMU Story
  • In 1995 - entering class in CS 7 women
  • In 2000 - entering class in CS 42 women
  • Studies in the 90s Women reported feeling
    isolated, intimidated
  • Studies circa 2005 Many fewer differences
    between women and men.
  • Why?
  • Women no longer an extreme minority
  • Recruiting changed to emphasize talent rather
    than prior programming experience.
  • See
  • Unlocking the Clubhouse
  • Blum and Frieze paper

24
Women Students - the UT Story
  • First Bytes
  • Women in Turing Scholars
  • But today only 12 of our undergraduate students
    are women.

25
Career Paths
  • Books and specializations
  • ACM programming languages study

26
Whats Your Specialization?Authors in a Sample
from the P-H CS List 2006
Men Women Men Women
Ethics 3 4 42.9 57.1
Multimedia and Web Design 17 14 54.8 45.2
Intro to CS 12 9 57.1 42.9
Human Computer Interaction 20 9 69.0 31.0
Software Engineering 20 5 80.0 20.0
Artificial Intelligence 23 3 88.5 11.5
Game Programming 27 3 90.0 10.0
Graphics and Image Processing 10 1 90.9 9.1
Operating Systems 23 2 92.0 8.0
Networking 28 2 93.3 6.7
Theory 28 1 96.6 3.4
Compilers 9 0 100.0 0.0
Computer Architecture 40 0 100.0 0.0
27
What Programming Languages Do You Know?
  • A survey conducted between June, 2000 and April,
    2001. (CACM 471, Jan. 2004)
  • 83 of respondents were male.
  • Average number of programming languages was 3.25
    (males), 2.53 (females).
  • For people with lt 1 year experience, average
    number was 2.38 (males) 2.03 (females).
  • For workers over 40, average number was 2.92
    (males) 2.23 (females).

28
What Programming Languages Do You Know?
All workers.
29
What Programming Languages Do You Know?
Workers with lt 1 year experience.
30
And Now Add Ethnic Diversity
  • The numbers are so small that statistics tell us
    little.
  • See the short note by Valerie Taylor

31
Summary
  • Computing needs women.
  • Women need computing.
  • There is no evidence that women arent good at
    it.
  • There is no compelling evidence that many of them
    couldnt be fascinated by it.
  • There are steps we can take to turn the tide,
    particularly with girls before they enter college.
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