Women: Their Underrepresentation and Career Differentials in Science and Engineering: Proceedings of a Conference (1987)

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

DISCUSSION: EQUITABLE SCIENCE AND MATHEMATICS EDUCATION Susan F. Chipman In attempting to understand what .causes the differences between men and women with respect to their participation in mathematics, sci- ence, and engineering, Kahle and Matyas—and all of us—address a very complex situation. Their paper discusses many factors in precollege education that plausibly could have some influence on the representa- tion of women. Many points of difference between male and female stu- dents and the way that others treat them are described and documented. If we are to either gain real understanding or have a basis for deciding where leverage can be placed in order to effect change, we need to organize all of this information with a dynamic theoretical model of the processes determining individual lives. That is, we need to approach this problem as a scientific problem in its own right. We must use a theoretical model to guide our research and data analysis efforts so that we can begin to determine which of the many plausible variables are actually important and to understand how they act and interact. How do all these variables act on individual life decisions? In an earlier paper (Chipman and Thomas, l984) for a National Re- search Council committee, I attempted to formulate a reasonably comprehensive and general version of such a model. It was based on a theoretical approach that others (Casserly and Rock, l985; Eccles- Parsons, et al., l983; Lantz and Smith, l98l) had taken to understand the case of female participation in high school mathematics courses. As Figure l illustrates, the outcome—participation—is understood as being influenced by two major factors: expectancy of success and value assigned to the outcome. Each of these, in turn, has many contributing determinants, as shown in Figures 2 and 3. Expectancy of success is likely to be influenced by such factors as cognitive ability—in which there are important individual differences and in which some claim that there are relevant sex differences (Benbow and Stanley, l980). Confidence in one's ability—an area in which large sex differences are found—also affects expectancy. General stereotypes of the abilities of particular population groups might affect their expectancy of success, either directly or through an effect on their confidence. The value of participation in a particular field of endeavor is also subject to many influences of the sort that Kahle and Matyas 43

School Policies & Practices Figure l Core of the model. Prior Achievements/ Difficulties Social Stereotypes of Capacity Figure 2 Influences on expectancy. 44

o C0 0) g ro OJ 45

describe. Immediate reinforcement or lack of reinforcement for par- ticipation may be important, as coming from parental encouragement, the expression of negative attitudes by male peers, or generally prev- alent stereotypes of social suitability. The anticipation of future family-career conflict fits in here. (I must point out that this per- ception may well be valid: those who are scientists, who work with scientists, and who study scientists know that successful scientists typically work extremely hard and extremely long hours—well beyond the 40-hour work week.) The expectation or lack of expectation that long-term rewards will be available in the form of employment oppor- tunities and fair compensaton is another potentially important factor. Finally, individual global interest patterns (which Kahle and Matyas did not discuss in a serious way) clearly influence the perceived value of career and courses of study and have substantial effects upon the selection of scientific careers. Furthermore, there are large sex differences in these interest patterns that can account for much of the sex difference in career selection (Dunteman, et al., l979), and such interest patterns are established at a very early age (Tyler, l964). Unfortunately, with only two or three exceptions, research to date does not demonstrate that the vast majority of these variables are actually important in determining the outcomes of interest, nor, of course, has it provided us with quantitative measures of relative importance. For individuals, it is clear that cognitive ability is an important predictor of persistence in mathematical, scientific, and technical fields, but it is rather unlikely that sex differences in ability contribute significantly to the observed sex differences in participation. In contrast, basic interest patterns—such as the relative interest in things versus people—are also significant pre- dictors for individuals and provide a possible account for much of the observed sex differences in participation. More research attention needs to be given to the early development and possible determinants of those interest patterns. It is possible that confidence in ability —which varies somewhat independently of actual ability—also provides some of the explanation for observed sex differences in participation. More attention needs to be given to understanding the relationship be- tween actual and perceived ability and their mutual relationships to continued participation. Most of the variables discussed by Kahle and Matyas probably have small effects on either expectancy of success or the value of participation. By focusing on the points where such variables would be expected to have their most direct effects—some- thing that has not been done in past research—it may be possible to measure those small effects (see Chipman and Wilson, l985, for a rele- vant discussion of the above points in the context of female partici- pation in mathematics). It seems obvious that experimental efforts at intervention should focus on those few variables shown to have significant effects. Other- wise, to have any hope of effect by altering variables, which at best have small effects, one would have to have an extremely broad-based intervention, broader than is likely to be practical. As an example of intervention that makes sense given research results, minority par- 46

ticipation in mathematical, scientific, and technical fields undoubt- edly can be improved most effectively by concentrating on improving achievement in the early school years. It is not obvious that it is still possible to change the basic interest patterns that are most relevant to female participation at the relatively advanced ages, where interventions are normally attempted. Indeed, it is not obvious how they can be changed by intervention at any age. It is probably worthwhile to attempt to experimentally alter the confidence of female students in a positive direction. In closing, I would like to comment on the presumption that underlies the paper that Kahle and Matyas have written, as it under- lies most discussions of this kind: the presumption that the desired goal is perfectly even representation of every identifiable population group in every occupation. Should that, indeed, be our goal? If the choices that we observe are found to reflect individual and cultural differences in values—rather than arbitrary discriminatory barriers or discouraging treatment—should we regard that as a problem? is it in any way appropriate to attempt to modify those values? Bibliography Benbow, C. P., and J. C. Stanley. l980. Sex differences in mathematical ability: Fact or artifact? Science 2l0:l262-l264. Casserly, P., and D. Rock. l985. Factors related to young women's persistence and achievement in advanced placement mathematics. In Women and Mathematics: Balancing the Equation, S. F. Chipman, L. R. Brush, and D. M. Wilson, eds. Hillsdale, N.J.: Lawrence Erlbaum Associates. Chipman, S. F., and V. G. Thomas. l984. The participation of women and minorities in mathematical, scientific and technical fields. Unpublished paper commissioned by the Committee on Research in Mathematics, Science, and Technology Education of the National Research Council's Commission on Behavioral and Social Sciences and Education (revision to be published in the Review of Research in Education, vol. l4). Chipman, S. F., and D. M. Wilson. l985. Understanding mathematics course enrollment and mathematics achievement: A synthesis of the research. In Women and Mathematics: Balancing the Equation, S. F. Chipman, L. R. Brush, and D. M. Wilson, eds. Hillsdale, N.J.: Lawrence Erlbauiit Associates. Dunteman, G. H., J. Wisenbaker, and M. E. Taylor. l979. Race and Sex Differences in College Science Program Participation. Report submitted to the National Science Foundation under contract no. SED-7-l8728. Eccles-Parsons, J., T. F. Adler, R. Futterman, S. Goff, C. Kaczala, J. L. Meece, and C. Midgely. l983. Expectancies, values and academic choice. In Achievement and Academic Motivation, J. Spence, ed. San Francisco: W. H. Freeman. Lantz, A., and G. P. Smith. l98l. Factors influencing the choice of nonrequired mathematics courses. Journal of Educational Psychol- ogy 73:825-837. 47

Tyler, L. H. l964. The antecedents of two varieties of vocational interests. Genetic Psychology Monographs 70:l77-277. 48

WOMEN IN ENGINEERING AND SCIENCE: AN UNDERGRADUATE RESEARCH PERSPECTIVE William K. LeBold Introduction A variety of sources have been used in developing this paper, in- cluding a comprehensive analysis of statistical data on the character- istics and education of scientists and engineers and the related lit- erature. Primary attention has been given to data and literature related to and within the various engineering and scientific disci- plines, especially those where women are underrepresented at the undergraduate level (e.g., engineering, physical science, and computer science). Comparative data and information in areas where women are almost equally represented at the undergraduate level (e.g., psychology and health science) are presented but are not the primary focus of this document. This paper focuses on these major objectives: • To identify the areas of engineering and science in which women are underrepresented in undergraduate education; • To identify the factors contributing to that underrepresenta- tion; • To identify and to compare the factors associated with attri- tion and retention rates of men and women in undergraduate science and engineering education programs; • To examine the factors influencing women's decisions to attend graduate school in engineering and science, including the impact of financial aid and other sources of support; • To examine policies and practices that may influence the dif- ferential enrollment of women and men in undergraduate and graduate engineering and science programs; and • To identify areas of future research needed to better under- stand the factors associated with the underrepresentation of women in science and engineering. Although theoretical perspectives and empirical research will be exam- ined, major attention is focused on presenting the key data regarding the underrepresentation of women in science and engineering, examining the factors influencing their underrepresentation and identifying policies and practices that reduce inequities in the representation of women in science and engineering. 49

Underrepresentation of Women in Engineering and Science, by Field DegreeData The l986 biennial report of the National Science Foundation (NSF) to the U.S. Congress, Women and Minorities in Science and Engineering, indicated that in l984 there were 3,995,500 engineers and scientists in the United States, including l,78l,400 scientists and 2,2l4,000 en- gineers (NSF, l986b). These figures reported 5l2,600 women engineers and scientists (l2.8 percent of the total) including 438,l00 scientists (23.9 percent) and 74,500 engineers (3.4 percent). Hence, even if parity (50 percent men and 50 percent women) were reached in the coming decade, it would be well beyond the year 2000 before employment equity in science and engineering might be reached or even approximated. On the positive side, it is important to note that very significant strides have been made by women in the United States during the past two decades. Women in l984 constituted 5l.3 percent of the U.S. popu- lation and 43.7 percent of those employed in the United States. In early l984, more women (52 percent) were attending higher educational institutions in the United States than men, comprising 52 percent of the undergraduates, 53 percent of the freshman, and 48 percent of the graduate students (Chronicle of Higher Education, January 22, l986). Although beyond the scope of this report, it is important to note that the data presented in this report are based on enrollment and degree information from U.S. educational institutions. Relatively large numbers of engineers and scientists in the U.S. work force do not have U.S. degrees in science and engineering; many engineers and scientists have either degrees in other disciplines or degrees from other countries, and many engineers and some scientists have no formal degree of any kind. Estimates of the numbers of scientists and engi- neers in the United States vary considerably, depending on the data sources used and the definitions employed. Estimates for l984 vary from almost 4 million (NSF, l986a) to the less than 2.5 million reported in the latest report of the Bureau of Labor Statistics (l986). There are wide differences in the degree to which women are repre- sented in various engineering and science fields. Figure l provides an excellent perspective for examining the trends and differences in the rates of their participation. At the bachelor's and master's degree levels, women reached equity (50 percent) in all fields in the l980s, but remain largely underrepresented at the doctorate level. However, the overall bachelor's and master's equity levels are due largely to the overrepresentation of women in education and the human- ities and approximate parity in psychology and the social sciences. Underrepresentation of women at the bachelor's degree level is excep- tionally prevalent in engineering (l4.5 percent in l985) and in the physical sciences (less than 30 percent in l985). At the master's level in l985, there was even lower representation of women than at the B.S. level in most fields: Underrepresentation was again espe- cially critical in engineering (ll.4 percent) and physical sciences (under 25 percent); in mathematics and social sciences, less than 50

M -O 0) C » 10 o Is *s 0} Oi C m TO Is 3: c o •O iH Oi •O C 0i 4) 4) 0) Oi •a c 0) o •D 0) •o u CO <0 C0 0 0> kl 10 JJ C u kl a jj e CO -a c 0) u 0) I O •H ft. 5l

40 percent of the degrees were awarded to women, but in the biological sciences women rapidly approached the 50 percent level. However, rep- resentation of women is above or at parity in education, the humani- ties, and psychology. The most serious inequities in the representation of women occur at the doctorate level, where parity has only recently been achieved in education and psychology but is rapidly approaching it in the humanities. The gross underrepresentation of women at the doctoral level in engineering (5.7 percent), in physical sciences (less than l5 percent), and in mathematics (less than 20 percent in l985) is especially significant. These areas represent fields that are of increasing importance nationally and internationally. Those holding doctoral degrees in engineering, physical sciences, and mathematics are most likely to have major responsibility for basic and applied research in academic institutions, for key research and development roles in high technology industries, and for public works projects supported with federal funds. To provide a more detailed perspective by disciplines within fields, a variety of data sources are available, including those sup- ported by the National Science Foundation, U.S. Department of Educa- tion, U.S. Department of Labor, Engineering Manpower Commission, Col- lege Entrance Examination Board, American College Testing Service, and American Council on Education. Fortunately, the Commission on Profes- sionals in Science and Technology (formerly the Scientific Manpower Commission) has performed the Herculean task of compiling information from a wide variety of sources as part of its manpower data resource service, which publishes annually Professional Women and Minorities (Vetter and Babco), the standard data reference on women and minorities in science and engineering. Between annual editions, the Commission also publishes Manpower Comments, which provides a periodical digest and selected new data in regard to the supply, demand, and educational utilization of scientists and engineers (including information on women and minorities). These data sources not only provide a contemporary perspective, but also document particular trends over the past two decades as well as general trends over the past 50 years. Data compiled by the Commission on Professionals in Science and Technologyl indicate that by l982-83 over half of the bachelor's and master's degrees awarded in the United States were earned by women. At the bachelor's level, women received over half of the degrees awarded in the health sciences (70.3 percent) and psychology (67.5 per- cent) and were approaching parity in the biological sciences (46.l per- cent). However, while the percentage of bachelor's degrees awarded to women in some science and engineering areas has increased during the past decade, they remain significantly below parity: computer and in- formation science (36.3 percent), physical science (27.3 percent), and .'.See U.S. Department of Education, National Center for Education Statistics, Earned Degrees Conferred series (l948-l98l), and National Research Council, Doctorate Recipients from U.S. Universities: Summary Report (l970-l983). 52

engineering (l3.3 percent). The only areas having a lower percentage of bachelor's degrees awarded in l982-83 were engineering technology (8.0 percent) and military science (l0.9 percent). Beginning College Data To provide early time perspectives on current and future trends regarding the representation of women in science and engineering, ex- cellent data are available on the educational and career plans of col- lege freshmen [from the joint studies of the University of California, Los Angeles (UCLA) and the American Council on Education (ACE)] and of college-bound high school seniors (from the Educational Testing Service's College Entrance Examination Board). Data on probable major field of study of college freshmen in all U.S. institutions of higher education (see Table l) document the trends, as well as the signi- ficant gender differences, in the educational plans of college freshmen. ACE data on probable career plans reflect similar gender differences (see Table 2, pages 58-59). These data sets clearly indicate the major factor underlying the underrepresentation of women in science and engineering: college-bound women do not plan to major or have careers in engineering and the physical sciences in the same proportions as college-bound men. There has been some increased interest among college-bound women and freshmen in engineering and science fields and careers, but the changes have been relatively small in the l980s and have even declined in some areas (engineering and physical science) in recent years. Near parity exists in biological sciences and most business-related fields, but women beginning college continue to be more interested than men in pursuing undergraduate education and later careers in the arts. Physical science, mathematics, computer science, and engineering continue to appeal to about three times as many beginning college men as women, with engineering representing ratios of about 6-l in l985 (a significant change from the over 50-l ratios of l97l) and physical science with ratios of about 3-l (up from the 5-l ratio of l97l). Mathematics and statistics are very close to equal representation at the freshman level; and in the rapidly growing computer science and systems analysis fields, ratios of about three men to two women characterize the contemporary freshman scene. Detailed Field Differences The data previously presented clearly indicate that the major fields in which women are underrepresented at the undergraduate level are in engineering and physical sciences. Physical Science. Table 3 (page 60) presents information on B.S. degrees in physical sciences by field including detailed data for astronomy, biochemistry, chemistry, geological and earth sciences, and physics from l97l through l983. These data indicate that underrepre- sentation of undergraduate women is especially high in physics, where only l in 8 of the B.S. degrees in l983 was awarded to women (up from 53

TABLE l: Percentage Distribution of Freshmen, by Probable Major Field l97l-l984 Probable Major Field of Study l97l Men l973 l975 Women Men Women Men Women Agriculture/forestry Arts and humanities* Biological sciences Business Education Engineering Health professions (non-M.D.) Mathematics/statistics Computer science Physical sciences Premedical, Predentistry, Preveterinary Social sciences* Other fields (technical) Other fields (nontechnical) Undecided 5.4 0.7 l6.8 20.5 4.4 2.7 l8.3 l4.2 4.6 l5.9 l3.2 0.3 2.6 l6.l 2.6 2.9 3.l 0.8 5.6 l2.2 7.3 2.6 l.4 5.0 2.3 2.3 4.4 l.0 l0.l l5.0 8.2 5.7 2l.l l4.0 5.2 l9.6 l2.l 0.7 4.6 l6.5 l.8 l.6 4.2 l.l 5.5 ll.7 8.4 2.0 7.l 3.5 4.5 4.9 5.7 l.9 l2.7 l2.8 7.l 5.5 20.l l7.5 4.6 l5.5 l4.0 l.3 l.8 l3.2 l.l l.l 4.0 l.3 3.7 l0.3 l0.2 4.6 8.9 6.7 8.8 5.5 NOTE: Totals may not equal l00% due to rounding. *Political Science is included in Arts and Humanities through l975; in SOURCE: American Council on Education, The American Freshman: National Research Program, University of California, l97l-l985. Comparable data l in l6 in l97l). In l983 about l in 4 B.S. degrees was awarded to women in astronomy and geophysics (up from about l in l2 and l in 8, respectively, in l98l) and about l in 3 in chemistry (up from about l in 5 in l97l). Mathematics, Computer Science, and Statistics. In the quantitatively- oriented science fields, participation rates for women are somewhat higher than in the physical sciences. Table 4 (page 60) indicates that in l983 the proportion of women receiving bachelor's degrees in computer science was more than twice as high (36.3 percent) as in l97l (l4.6 percent), and the women's share of bachelor's degrees in mathe- matics increased from 38.2 percent in l97l to 45.7 percent. For the same period, the number of B.S. degrees awarded to women in statistics was very close to parity (48.7 percent), having almost doubled since l97l (25.3 percent). Engineering. Detailed data on bachelor's degrees in engineering fields for selected years between l97l and l983 (see Table 5, pages 62-63), 54

of Study in All Institutions of Higher Education, for Selected Years, l978 l980 l982 l983 l984 Men Women Men Women Men Women Men Women Men Women 4 .5 2.0 4.l l. 8 3.8 l.4 2.9 0.9 3.3 l.0 7 .4 l0.6 6.4 l0. l 6.8 9.7 6.8 9.0 6.6 8.8 4 .8 4.4 3.7 3. 8 3.7 3.8 4.l 3.4 4.l 4.2 25 .0 23.l 22.9 24. 5 22.3 25.7 22.7 26.0 25.l 27.5 3 .3 l2.l 3.3 ll. 6 2.4 9.0 2.9 8.9 2.8 9.6 l8 .8 2.3 2l.0 3. 2 22.3 3.6 20.6 3.5 20.l 3.0 2 .0 l4.6 l.9 l3. 3 l.6 l7.8 2.l l4.9 2.3 l3.8 l .l 0.8 0.7 0. 6 0.6 0.7 0.8 0.8 0.8 0.9 l .6 l.2 2.7 2. 4 4.9 4.0 5.4 3.7 4.3 2.7 3 .5 l.3 3.6 l. 6 2.6 l.0 2.5 l.0 2.5 l.l 4 .0 2.9 3.6 3. 2 3.2 3.0 3.3 3.2 3.2 3.l 5 .0 9.5 4.5 8. 6 4.2 7.2 4.2 7.6 5.l 8.4 7 .0 2.0 8.5 2. 9 9.7 4.3 9.9 3.8 7.7 2.4 8 .l 7.9 9.3 6. 9 8.2 3.3 8.l 7.l 8.0 7.6 3 .9 5.3 3.8 5. 5 3.7 5.5 4.0 5.7 4.l 6.2 Social Sciences after l975. Norms, Los Angeles: Office of Research and Cooperative Institutional is available from the College Entrance Examination Board. indicate that women in engineering are most likely to be underrepre- sented in aeronautical, electrical, mechanical, and mining engineering, where about l in l0 B.S. degrees was awarded to women in l983 (up from about l in l00 in l97l) compared with about l in 7 overall. The high- est representations of women in major engineering fields in l983 were in chemical, industrial, and metallurgical engineering, where they were awarded about l in 4 B.S. degrees (up from about l in 50 in l97l-l975). More detailed information on engineering enrollments (see Table 6, page 64) is presented to illustrate ways in which the data may be used to predict future degree output. Table 6 provides data on first-, second-, third-, and fourth-year undergraduate enrollments and numbers of B.S., M.S., and Ph.D. degrees awarded. Note that the percentage of first-year women enrolled in engineering in l97l (2.6 percent) closely corresponds to the l972 second-year (2.6), the l973 third-year (2.7 percent), and the l974 fourth-year enrollments (2.8 percent), as well as the B.S. degrees awarded in l975 (2.3 per- cent). However, it does not provide insight into master's and 55

-U g £ CO w o> WJ Cu 0) 0) s o tn OJ o •rH O 0> 0) kl 0) 57 O 00 je " o - co c u O «J •H 0) •H 0) U JJ 4J O co o> •H -H Q 0) w fl s~ 2 « £ € £ " ™ <0 U O J -H 00 -U < <0 H Z CO oo CM 00 a\ oo 01 o oo oo r- VOOOrH COrHrHrHOrHO ^ OOOCMOOOOOrHOCO rH inOCMrH OCMTfrHOOO r^ rHOOOOrHOOOOOrH^ " rH rH VOOOrH f>OrHrHOrHO r- OOOmOOOOOrHOm rH o oo cri m ro CO o rn in in ro CM rH o» rH oo ^i ^i o rH o r^- oo 0-1 inOrHrH OrH-^rHOOO O rHOOOOrHOOOOOrH'* rH iH rH inovorH mi—iincMrH^oj o minvovoTrr-cMorooino^ VOrHOCM mOrHrHOrHO O0 OOOmOOOrHOCMOCO •H rH r- CM ro ro oo o» rn in co CM r^* co o* rH \o o *»i o rH rH in <j> r^- inOCMrH OOCOrHOOO Oi rHOOOCMOOOOOiH^" rH CM VOrHOCM mOirHrHOrHO VO OOOCMOOOrHOrHOCO rH rH cMooo^" tncMrocMrH^CM cri r-r-r-ofN^vocMommvoin VOrHOCM mOirHrHOrHO ^ OOOCMOOOrHOCMOrO 'S'OlOOf COrHrHrHt^^"CM IO ^"CMrHrHO^frHrHOVOOOOO inOCMrH OrHTtrHOOO in rHrHOOlCMOOOOOl-l^" rH rH oOrHOOrH i-icMcMinrHvocM m t~-vor^roinvo^'rH'r)t--r^'* inrHOCM •*COrHrHOrHO <n OOOCMOOOrHOCMOCO inOCMrH OrH^frHOOO '»• rHrHOVOCMOOOOOrHin rH rH VOrHOCM ^-r-rHrHOi-IO CO OOrHCMOOOrHOCOOCO ^i oo in o i-*") m rH CM oo in ro o cyi ^Ji rH m oo ro o rH IH r-- CM m VOOCMrH OrH^'rHOOO ^ rHrHOVOiHOOOOOCMin u 0) C C « >|rH UUa 100) 3CC JJ-HrO u its i3 JJ 0) \ c -u -P 03 C U 4J a> a> U 0) O >, JJS <I> -Q -r<\ klC O, O 0>O«0 >MU <a-HCXo> U <1) .C0)t-l >iU 0) -r^ .* 0) H E O-HU 3 JJ O IJJ (T O LjCJrH 4) to u -H 0> C O 0) -H -H 14-1 (7>M-I >i O J3 \4J C C C O -HU W U -U Ot W Ol JJ -u -u a> rH u W <T5 -M c COl-l OM CO) — <D u U 0> CT> "O 4) -H O iO M aj c M a 0) VM 0) -C O T-I Q J W <<<<m u o u o O o - 0>-iHC<UOOCC«J<0 56

CNrHOOO^OOrHOOOOrHOrHCMinOO rr>ino>ir>vo<v)inoo rHrHOOOiTOOrHOOOOrHOrHCMinOO OrHr~OO(MOOrHCMOrO*jOCMrH(MOOOrH i-HrHOOOTJ1OOCMOOOOrHOrHnVOCO rHOOOTOOC^OOOOrHOrHCOinOO i-Hi-HOOO^OOCMOOOOCMOrHCSVOCri l-l >1 ia u *J 10 c -a a> c e o cu u CO c c rH 01 (0 01 CO -H 3 -I- —. — i-4 O CO 10 -r- .H kl k i C \ CO CD u (0 'O 0) 10 J= u u <0 (0 4J -H 0> 01 01 l-i kl 01 rH 01 4J rH k i U 01 01 .c -o 4J C 01 o .. co CO <* CU rH rH i 0) OO en t~ c <r> CO O <D .H 4J (0 O 3 'n o> o CO c 0 a, rHrHOOO^OOCMOOOOCMrHrHromcri Q) l-l >i C k i (0 10 -H 4J O 'H -iH ^1 CO .^ 3 ac s: 4J k i O, 0> 3 J2 m o kl rH « o 10 o> rH O< CO 01 -H 4> co o >-i c c 3 -H U C O k i -H <o u ex "w 4J U -H -H 01 <0 U rH rH 4J o) e e -H o o c co o i-i co o o cu 3 Qi £ .C O O O z O ex ix co co co 4J «O JJ .H W o c o .H a 0> kl u a> kl •-HrHOJrHCOCXO)O) o -a .H C « 10 <! o u (0 .. fl) u co U 01 « X O <4-l CO O 57

TABLE 3: Percentage of B.S. Degrees Awarded to Women in Physical Science Areas Year Astronomy Biochemistry Chemistry Geosciences Physics l97l 7.8 24.3 l8.7 ll.4 6.8 l972 l6.5 28.2 l9.8 l2.7 7.0 l973 20.9 22.4 l9.2 l2.7 7.3 l974 2l.7 23.l 20.l l6.5 8.5 l975 l7.4 26.5 22.4 l7.4 9.7 l976 l2.9 29.6 22.5 l8.8 l0.9 l977 l5.6 29.2 22.8 2l.6 l0.5 l978 2l.8 29.5 25.l 22.4 ll.l l979 2l.5 32.9 26.7 23.5 l2.0 l980 l6.7 35.4 28.6 24.7 l2.8 l98l l6.4 35.7 29.9 25.l l2.6 l982 l9.8 35.8 3l.l 26.4 l3.2 l983 26.7 38.2 34.l 25.8 l2.7 SOURCES: National Center for Education Statistics, Earned Degrees Conferred series, Washington, D.C. : : U.S. Office of Education, l97l-l983 0 TABLE 4: Percentage of B.S. Degrees Awarded to Women in Computer Science, Mathematics, and Statistics Year Computer Science Mathematics Statistics l97l l4.6 38.2 25.3 l972 l3.5 39.2 27.9 l973 l4.9 40.3 34.8 l974 l6.4 4l.0 36.6 l975 l8.9 42.l 3l.9 l976 l9.8 40.9 35.7 l977 23.9 4l.5 43.4 l978 25.8 4l.4 39.2 l979 28.l 4l.7 38.3 l980 30.3 42.3 42.l l98l 32.5 42.8 47.0 l982 34.8 43.2 4l.l l983 36.3 45.7 48.7 SOURCE: See Table 3. 58