Transcript Slide 1

2011 New Faces in Engineering
Hearing the Female
Voices in Quality
Creating a Diverse Workforce
Sharyn Mlinar
Sr. Quality Engineer
The Boeing Company
Philadelphia, Pennsylvania
[email protected]
INTRODUCE A GIRL TO ENGINEERING DAY FEBRUARY 24, 2011
Women are severely underrepresented in the engineering profession. Research shows that girls and young
women lose interest in subjects and the fields of study leading to engineering careers long before they enter
college.
As part of our focus on girls, we will publicize the need for more women in engineering and will reach K-12 girls
with positive messages about math and science education and engineering careers. Additionally we are striving to
have engineering societies and other organizations incorporate their own focus on women engineers with a hope
that these various entities can continue to collaborate in the future.
Currently only 20 percent of engineering undergraduates are women. Only ten percent of the engineering
workforce are women. For years, false notions of girls’ innate inability in math, lack of science preparation in high
school, and assumptions about the effects of historical and institutional discrimination, have been offered as
causes for the startling disproportion. Recent surveys, however, refute most of those theories, including the ones
that question girls’ academic readiness to study engineering when they leave high school. Girls and boys take
requisite courses at approximately the same rate, with girls’ enrollment often exceeding that of boys. Instead,
experts contend that the major culprit is one of perception among girls and the people who influence them,
including teachers, parents, peers, and the media.
In short, girls have to perceive they can be engineers before they can be engineers. According to the National
Engineers Week Foundation, nothing conveys that message as effectively as mentors and role models and no
program more effectively brings girls and role models together than Introduce a Girl to Engineering Day, now in its
8th year.
Agilent Technologies, Inc. and the S.D. Bechtel, Jr. Foundation are lead sponsors for Introduce a Girl to
Engineering Day, with additional funding from the Motorola Foundation.
Some suggested reading material for girls are:
Girls Think of Everything: Stories of Ingenious Inventions by Women
Girls just wanna have fun in engineering: Techbridge can help you Introduce a Girl to Engineering
For more information about Introduce A Girl to Engineering Day, visit The National Engineers Week Foundation
For specific information about what schools, companies and organizations are doing for Introduce a Girl to
Engineering Day, check out EWeek.org's National Pledge Roster
From Jean Piaget’s early studies of boys
at school and Carol Gilligan’s studies of
females (1982) to the compilation of
longitudinal studies edited by Ceci and
Williams (2007) the data appear to
substantiate that males and females
approach life and its circumstances with
differences but that cognitive ability
with regard to sciences and the arts
is not different.
Table 1 Educational Attainment
2006 - 2008
Subject
Population 18 to 24
years
Less
High
Margin of
Error
(+/-)
Total
Margin of
Error
(+/-)
Male
Female
Margin of
Error
(+/-)
29,636,552
18,253
15,267,203
10,671
14,369,349
12,187
than high
school
graduate
17.1%
0.1
19.8%
0.1
14.3%
0.1
school
graduate
(includes
equivalency)
32.5%
0.1
34.9%
0.1
30.0%
0.1
41.4%
0.1
38.2%
0.2
44.8%
0.2
9.0%
0.1
7.2%
0.1
10.9%
0.1
Some college or
associate's
degree
Bachelor's degree
or higher
U.S. Census Bureau, 2006-2008 American Community Survey
Table 2 Educational Attainment
2006 - 2008
Subject
Population 25 years and
over
Margin of
Error
(+/-)
Total
Margin of
Error
(+/-)
Male
Margin of
Error
(+/-)
Female
197,794,576
28,830
95,374,767
17,334
102,419,809
15,872
Less than 9th grade
6.4%
0.1
6.6%
0.1
6.2%
0.1
9th to 12th grade, no
diploma
9.1%
0.1
9.5%
0.1
8.7%
0.1
school graduate
(includes
equivalency)
29.6%
0.1
29.5%
0.1
29.6%
0.1
Some college, no degree
20.1%
0.1
19.5%
0.1
20.6%
0.1
Associate's degree
7.4%
0.1
6.7%
0.1
8.1%
0.1
Bachelor's degree
17.3%
0.1
17.5%
0.1
17.2%
0.1
Graduate or professional
degree
10.1%
0.1
10.7%
0.1
9.5%
0.1
Percent high school
graduate or higher
84.5%
0.1
83.9%
0.1
85.1%
0.1
Percent
bachelor's
degree or higher
27.4%
0.1
28.2%
0.1
26.7%
0.1
High
U.S. Census Bureau, 2006-2008 American Community Survey
Subject
Margin of
Error
(+/-)
Total
Margin of
Error
(+/-)
Male
Female
Margin of Error
(+/-)
Population 25 to 34 years
40,125,972
14,231
20,407,842
9,724
19,718,130
9,587
High school graduate or
higher
86.2%
0.1
84.1%
0.1
88.4%
0.1
Bachelor's
degree
higher
29.2%
0.1
25.8%
0.1
32.7%
0.1
43,140,679
12,910
21,602,724
9,177
21,537,955
7,867
High school graduate or
higher
87.2%
0.1
85.6%
0.1
88.9%
0.1
Bachelor's
degree
higher
30.4%
0.1
29.0%
0.1
31.7%
0.1
or
Population 35 to 44 years
or
Table 3 Educational Attainment 2006 - 2008
Population 45 to 64 years
76,547,789
14,648
37,355,336
10,409
39,192,453
7,968
High school graduate or
higher
87.3%
0.1
86.5%
0.1
88.0%
0.1
Bachelor's
degree
higher
28.8%
0.1
30.2%
0.1
27.5%
0.1
Population 65 years and
over
37,980,136
7,120
16,008,865
4,220
21,971,271
4,849
High school graduate or
higher
74.2%
0.1
75.2%
0.1
73.4%
0.1
Bachelor's
degree
higher
19.4%
0.1
25.4%
0.1
15.0%
0.1
or
or
Table 4 Poverty rate for the population 25 years
and over for whom poverty status is determined
by educational attainment level
Total
Less than high school
graduate
Margin of
Error
(+/-)
Margin of
Error
(+/-)
Male
Female
Margin of
Error
(+/-)
23.6%
0.1
19.4%
0.1
27.7%
0.1
school graduate
(includes
equivalency)
11.5%
0.1
9.3%
0.1
13.5%
0.1
Some
college
or
associate's degree
7.8%
0.1
6.0%
0.1
9.4%
0.1
4.1%
0.1
3.6%
0.1
4.5%
0.1
3.0%
0.1
2.7%
0.1
3.3%
0.1
High
Bachelor's degree
Graduate or professional
degree
Table 5 Median Earnings 2008 by
Educational Attainment Level
Total
Subject
Population 25 years
and over with
earnings
Margin of
Error
(+/-)
Male
Margin of
Error
(+/-)
Female
Margin of
Error
(+/-)
34,483
44
41,298
49
28,104
43
than high
school
graduate
19,989
53
23,638
97
14,682
54
school
graduate
(includes
equivalency)
27,448
28
33,506
74
21,711
35
Some college or
associate's
degree
33,838
51
41,861
58
27,663
62
Bachelor's degree
47,853
81
59,079
163
39,571
79
Graduate
or
professional
degree
63,174
115
79,276
210
52,301
100
Less
High
Table 6 Science and engineering
degrees awarded, by degree level and
sex of recipient 1966-2006
 Tabulated by National Science
Foundation/Division of Science Resources
Statistics (NSF/SRS); data from Department of
Education/National Center for Education
Statistics: Integrated Postsecondary Education
Data System Completions Survey and
NSF/SRS: Survey of Earned Doctorates

(NSF, 2009)
Academic
Bachelor's
Master's
Doctorate
year ending
Men
Women
% women
Men
Women
% women
Men
Women
% women
1966
138,679
45,634
24.8
35,580
5,469
13.3
10,646
924
8.0
1967
149,045
50,787
25.4
38,682
6,306
14.0
12,013
1,096
8.4
1968
165,200
61,397
27.1
41,551
7,209
14.8
13,328
1,317
9.0
1969
189,272
72,917
27.8
44,182
8,200
15.7
14,781
1,507
9.3
1970
204,528
79,702
28.0
43,973
9,722
18.1
16,404
1,648
9.1
1971
209,318
85,039
28.9
46,116
10,338
18.3
17,385
1,996
10.3
1972
216,422
90,037
29.4
48,721
11,328
18.9
17,191
2,151
11.1
1973
225,090
95,995
29.9
50,233
11,813
19.0
16,853
2,520
13.0
1974
223,652
102,578
31.4
49,528
12,711
20.4
16,043
2,671
14.3
1975
210,741
102,814
32.8
49,410
13,788
21.8
15,870
2,929
15.6
1976
205,570
103,921
33.6
49,992
15,015
23.1
15,375
3,097
16.8
1977
198,805
104,993
34.6
50,899
16,498
24.5
14,775
3,233
18.0
1978
195,888
107,667
35.5
50,034
17,230
25.6
14,199
3,454
19.6
1979
193,247
109,915
36.3
46,614
17,612
27.4
14,128
3,744
20.9
1980
191,215
113,480
37.2
46,004
18,085
28.2
13,814
3,961
22.3
1981
190,977
115,815
37.8
45,505
18,861
29.3
14,056
4,201
23.0
1982
193,624
121,399
38.5
46,557
20,011
30.1
13,923
4,350
23.8
1983
194,380
123,191
38.8
46,734
20,999
31.0
13,920
4,714
25.3
1984
199,150
125,134
38.6
47,049
21,533
31.4
13,954
4,791
25.6
1985
203,402
128,871
38.8
48,247
22,331
31.6
14,043
4,891
25.8
1986
204,743
130,662
39.0
48,621
23,219
32.3
14,268
5,167
26.6
1987
199,981
131,545
39.7
48,759
23,844
32.8
14,580
5,312
26.7
1988
191,549
130,933
40.6
49,820
23,835
32.4
15,267
5,662
27.1
1985
203,402
128,871
38.8
48,247
22,331
31.6
14,043
4,891
25.8
1986
204,743
130,662
39.0
48,621
23,219
32.3
14,268
5,167
26.6
1987
199,981
131,545
39.7
48,759
23,844
32.8
14,580
5,312
26.7
1988
191,549
130,933
40.6
49,820
23,835
32.4
15,267
5,662
27.1
1989
189,338
133,483
41.3
50,845
25,580
33.5
15,623
6,109
28.1
1990
189,082
140,012
42.5
51,230
26,558
34.1
16,498
6,369
27.9
1991
189,328
148,347
43.9
50,441
27,927
35.6
16,982
6,932
29.0
1992
195,779
159,486
44.9
52,157
28,950
35.7
17,420
7,080
28.9
1993
200,315
165,720
45.3
55,454
30,971
35.8
17,568
7,652
30.3
1994
202,284
170,977
45.8
57,970
33,441
36.6
18,163
7,922
30.4
1995
202,217
175,931
46.5
58,518
35,791
38.0
18,117
8,286
31.4
1996
203,341
181,333
47.1
57,860
37,453
39.3
18,454
8,648
31.9
1997
201,471
187,011
48.1
55,223
38,262
40.9
18,080
8,934
33.1
1998
200,221
190,397
48.7
55,335
38,583
41.1
17,809
9,348
34.4
1999
NA
NA
NA
NA
NA
NA
16,734
9,081
35.2
2000
197,669
200,953
50.4
54,213
41,470
43.3
16,519
9,393
36.2
2001
197,623
202,583
50.6
55,593
43,393
43.8
16,186
9,298
36.5
2002
204,408
211,203
50.8
55,701
43,472
43.8
15,387
9,172
37.3
2003
218,698
222,389
50.4
61,199
46,711
43.3
15,762
9,519
37.7
2004
225,909
229,939
50.4
66,798
51,672
43.6
16,418
9,856
37.5
2005
230,806
235,197
50.5
66,974
53,051
44.2
17,407
10,539
37.7
2006
234,260
239,273
50.5
66,262
54,075
44.9
18,341
11,469
38.5
Machine Design
reported in December
2009 “only 1 in 10 male
engineers leave the field
by the time they hit 30,
but about 1 in 4 women
leave engineering after
getting their degree.”
Table X
Maternity
Leave
Country
Women
in Labor
Force %F
Unemployed
%F / %M
Part-time
Employed
%F / %M
Service/
Manufacturing
%F / %F
Maternity Leave
and Pay
(weeks/%pay)
Austria
51
4.2/4.3
24.4/2.6
NA
16/100
Belgium
40
8.9/7.7
NA
88.2/10.7
15/a
Denmark
73
6.2/5.0
22.9/10.3
85.9/12.2
18/90
Finland
64
8.9/9.2
14.7/7.5
81.9/14.1
13.5/70
France
49
10.9/8.7
24.1/5.1
86.6/12.4
16/100
Germany
49
9.5/10.4
35.2/5.5
82.4/15.6
14/100
Greece
38
14.6/6.2
10/2.9
65.7/12.9
17/100
Iceland
79
2.9/3.6
31.2/10.2
NA
12/80
Ireland
49
3.9/4.8
33.2/7.1
82.5/15.6
18/70
Italy
37
11.6/6.7
23.4/4.8
76.8/19.2
20/80
Japan
48
4.9/5.5
40.2/13.7
NA
14/60
Netherlands
56
4.4/4.2
59.9/15
89.0/8.6
16/a
Norway
69
4.0/4.9
33.0/9.2
NA
16/80-100
Portugal
55
7.2/505
NA
67.8/12.9
18/100
Spain
43
15.9/8.2
16.3/2.4
81.3/13.9
16/100
Sweden
76
4.4/5.3
20.3/7.3
87.5/11.1
16/100
Switzerland
59
4.5/3.8
45.3/7.7
NA
14/80
United
Kingdom
55
4.1/5.5
39.7/8.8
87.3/11.9
18/a
United
60
5.7/6.3
17.1/6.9
80.0/64.0
12/0
Table X
 Note: Service/Manufacturing industry data from the
United Nations Statistical Yearbook 2000 (2004). Labor
force, unemployment, part-time employment data from
United nations Statistics 2000-2003. Data are rounded.
Note that women are over represented in both part-time
and service professions, indicating a lower wage base.


F = female, M = male, NA = no data available.
The rates in these countries, where the initial amount is
higher that the amount for remaining leave. Moreover, in
some countries such as the United Kingdom and
Sweden, the leave may be longer, but there is less pay
for longer leave periods.

(see http://www.childpolicyintl.org) (Watt & Eccles, 343344)
Celebrate Diversity
Caring
Perspective
Helping
Those
In need
Peace
Traditions
Apples &
Oranges & Nurturing
Limes & …
Moving together
change
Faith in
Mans
Humanity
Partnerships
Legacy
Appreciating
Differences
Free Speech
Politics Tempered
With Patriotism
Self-expression
Religious
Freedom Different
Viewpoints
Wisdom
On Occasion
Challenges
Veterans
Learning
Teamwork
Hope
Reflection
No Fear
Harmony