Carol B. Muller

Bio: Carol B. Muller is an academic researcher from Stanford University. The author has contributed to research in topics: E-mentoring & Engineering education. The author has an hindex of 13, co-authored 36 publications receiving 792 citations. Previous affiliations of Carol B. Muller include Dartmouth College & San Jose State University.

Matching by Race and Gender in Mentoring Relationships: Keeping our Eyes on the Prize

Abstract: This study examined the extent to which science, technology, engineering, and math (STEM) students reported having had mentors of their own race and gender and the extent to which they have adopted the idea that matching by race and gender matters. The study also documented the effects of race and gender matching on three academic outcomes, self-reported grade point average, efficacy, and confidence, based on data collected from 1,013 undergraduate and graduate students and postdoctoral scholars actively participating in MentorNet's online community. Analyses indicated that having a mentor of one's own gender or race was felt to be important by many students, especially women and students of Color. Students who had a mentor of their own gender or race reported receiving more help, but matching by race or gender did not affect academic outcomes. Key findings are discussed in terms of implications for future research and mentoring in the STEM fields.

Building a Better Bridge: Testing e-training to improve e-mentoring programmes in higher education

Abstract: Uniting mentoring with e-mail results in expanded opportunities for mentoring, making it possible to overcome the constraints of time limitations and distance to achieve successful mentoring relationships. With these opportunities however, come many of the same challenges that have already been identified through the research on formal mentoring programmes. This article addresses one of these challenges by reporting on the impact of one model of training on e-mentoring outcomes. A series of interactive, web-based case studies was developed as training modules for mentors and prote´ge´s participating in the MentorNet programme. The target group for this research study was undergraduate students. Using a control group experimental design, we randomly assigned half the study group to a condition where interactive on-line training was required. The other half was assigned to a condition where the training was optional. Those in the mandatory group exhibited improved outcomes; specifically, they exchanged e-ma...

Gender differences and performance in science.

Abstract: On 14 Jan., Harvard University President Lawrence Summers, speaking at a meeting of the National Bureau of Economic Research, suggested that since fewer girls than boys have top scores on science and math tests in high school, genetic, rather than social, differences may explain why so few women are successful in these fields (“Summers's comments draw attention to gender, racial gaps,” News of the Week, A. Lawler, 28 Jan., p. [492][1]). Well-accepted, pathbreaking research on learning [for example, ([1][2], [2][3])] shows that expectations heavily influence performance, particularly on tests. If society, institutions, teachers, and leaders like President Summers expect (overtly or subconsciously) that girls and women will not perform as well as boys and men, there is a good chance many will indeed not perform as well. At the same time, there is little evidence that those scoring at the very top of the range in standardized tests are likely to have more successful careers in the sciences. Too many other factors are involved. Finally, well-documented evidence demonstrates that women's efforts and achievements are not valued, recognized, and rewarded to the same extent as those of their male counterparts ([3][4]). As leaders in science, engineering, and education, we are concerned by the suggestion that the status quo for women in science and engineering may be natural, inevitable, and unrelated to social factors. Counterexamples to this suggestion are drawn from the fields of law and medicine. In 1970, women represented just 5% of law school students and 8% of medical school students ([4][5]). These low percentages have increased substantially in response to social changes and concerted institutional and individual effort and are now about 50% in each case. Obviously, the low rates of participation in 1970 were indicative of social, and not genetic, barriers to success. We must continue to address the multitude of small and subtle ways in which people of all kinds are discouraged from pursuing interest in scientific and technical fields. Society benefits most when we take full advantage of the scientific and technical talent among us. It is time to create a broader awareness of those proven and effective means, including institutional policies and practices, that enable women and other underrepresented groups to step beyond the historical barriers in science and engineering. 1. 1.[↵][6] 1. J. Bransford 2. et al. , How People Learn: Brain, Mind, Experience, and School: Expanded Edition, ed. 1 (National Academies Press, Washington, DC, 2000). 2. 2.[↵][7] 1. C. M. Steele , Atlantic Monthly 284(no. 2), 44 (Aug. 1999). [OpenUrl][8] 3. 3.[↵][9] 1. V. Valian , Why So Slow? The Advancement of Women (MIT Press, Cambridge, MA, 1999). 4. 4.[↵][10] Trends in Educational Equity of Girls and Women: 2004 (National Center for Education Statistics, Washington, DC, 2004) (available at ). [1]: /lookup/doi/10.1126/science.307.5709.492 [2]: #ref-1 [3]: #ref-2 [4]: #ref-3 [5]: #ref-4 [6]: #xref-ref-1-1 "View reference 1. in text" [7]: #xref-ref-2-1 "View reference 2. in text" [8]: {openurl}?query=rft.jtitle%253DAtlantic%2BMonthly%26rft.volume%253D284%26rft.spage%253D44%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [9]: #xref-ref-3-1 "View reference 3. in text" [10]: #xref-ref-4-1 "View reference 4. in text"

When Email and Mentoring Unite: The Implementation of a Nationwide Electronic Mentoring Program--MentorNet, the National Electronic Industrial Mentoring Network for Women in Engineering and Science.

Abstract: Electronic mentoring (e-mentoring) programs are providing unprecedented opportunities for establishing mentoring relationships. E-mentoring is the merger of mentoring with electronic communications and links mentors with protégés independent of geography or scheduling constraints. In this case study, the authors apply a model of structured mentoring to the implementation of MentorNet (www.MentorNet.net), a nationwide structured e-mentoring program for women engineering and science students, to identify issues related to the use of electronic communications as a delivery system for mentoring and to begin the development of best practices for e-mentoring.

Mentor-protege matching system and method

Abstract: A computer-implemented method for bi-directionally matching a proteege and a mentor among participants in an online environment includes registering the protege so that he or she can be uniquely identified within the online environment. A mentor profile is received including demographic and/or personal information about the mentor, as well as the mentor's preferences regarding potential proteges. A protege profile is also received including demographic and/or personal information about the protege, as well as the protege's preferences regarding potential mentors. One or more recommended mentor-protege matches are bi-directionally calculated based on the information and preferences. One or more coaching prompts and evaluation requests are sent to matched participants.

The Science of Sex Differences in Science and Mathematics

Abstract: SUMMARY—Amid ongoing public speculation about the reasons for sex differences in careers in science and mathematics, we present a consensus statement that is based on the best available scientific evidence. Sex differences in science and math achievement and ability are smaller for the mid-range of the abilities distribution than they are for those with the highest levels of achievement and ability. Males are more variable on most measures of quantitative and visuospatial ability, which necessarily results in more males at both high- and low-ability extremes; the reasons why males are often more variable remain elusive. Successful careers in math and science require many types of cognitive abilities. Females tend to excel in verbal abilities, with large differences between females andmalesfound whenassessmentsincludewriting samples. High-level achievement in science and math requires the ability to communicate effectively and comprehend abstract ideas, so the female advantage in writing should be helpful in all academic domains. Males outperform females on most measures of visuospatial abilities, which have been implicated as contributing to sex differences on standardized examsin mathematics and science. An evolutionary account of sex differences in mathematics and science supports the conclusion that, although sex differences in math and science performance have not directly evolved, they could be indirectly related to differences in interests and specific brain and cognitive systems. We review the brain basis for sex differences in science and mathematics, describe consistent effects, and identify numerous possible correlates. Experience alters brain structures and functioning, so causal statements about brain differences and success in math and science are circular. A wide range of sociocultural forces contribute to sex differences in mathematics and science achievement and ability—including the effects of family,neighborhood,peer,andschoolinfluences;training and experience; and cultural practices. We conclude that early experience, biological factors, educational policy, and cultural context affect the number of women and men who pursue advanced study in science and math and that these effects add and interact in complex ways. There are no single or simple answers to the complex questions about sex differences in science and mathematics.

Women in Academic Science: A Changing Landscape

Abstract: Summary Much has been written in the past two decades about women in academic science careers, but this literature is contradictory. Many analyses have revealed a level playing field, with men and women faring equally, whereas other analyses have suggested numerous areas in which the playing field is not level. The only widely-agreed-upon conclusion is that women are underrepresented in college majors, graduate school programs, and the professoriate in those fields that are the most mathematically intensive, such as geoscience, engineering, economics, mathematics/ computer science, and the physical sciences. In other scientific fields (psychology, life science, social science), women are found in much higher percentages. In this monograph, we undertake extensive life-course analyses comparing the trajectories of women and men in math-intensive fields with those of their counterparts in non-math-intensive fields in which women are close to parity with or even exceed the number of men. We begin by examining early-childhood differences in spatial processing and follow this through quantitative performance in middle childhood and adolescence, including high school coursework. We then focus on the transition of the sexes from high school to college major, then to graduate school, and, finally, to careers in academic science. The results of our myriad analyses reveal that early sex differences in spatial and mathematical reasoning need not stem from biological bases, that the gap between average female and male math ability is narrowing (suggesting strong environmental influences), and that sex differences in math ability at the right tail show variation over time and across nationalities, ethnicities, and other factors, indicating that the ratio of males to females at the right tail can and does change. We find that gender differences in attitudes toward and expectations about math careers and ability (controlling for actual ability) are evident by kindergarten and increase thereafter, leading to lower female propensities to major in math-intensive subjects in college but higher female propensities to major in non-math-intensive sciences, with overall science, technology, engineering, and mathematics (STEM) majors at 50% female for more than a decade. Post-college, although men with majors in math-intensive subjects have historically chosen and completed PhDs in these fields more often than women, the gap has recently narrowed by two thirds; among non-math-intensive STEM majors, women are more likely than men to go into health and other people-related occupations instead of pursuing PhDs. Importantly, of those who obtain doctorates in math-intensive fields, men and women entering the professoriate have equivalent access to tenure-track academic jobs in science, and they persist and are remunerated at comparable rates—with some caveats that we discuss. The transition from graduate programs to assistant professorships shows more pipeline leakage in the fields in which women are already very prevalent (psychology, life science, social science) than in the math-intensive fields in which they are underrepresented but in which the number of females holding assistant professorships is at least commensurate with (if not greater than) that of males. That is, invitations to interview for tenure-track positions in math-intensive fields—as well as actual employment offers—reveal that female PhD applicants fare at least as well as their male counterparts in math-intensive fields.

Study of Mathematically Precocious Youth After 35 Years: Uncovering Antecedents for the Development of Math-Science Expertise:

Abstract: This review provides an account of the Study of Mathematically Precocious Youth (SMPY) after 35 years of longitudinal research. Findings from recent 20-year follow-ups from three cohorts, plus 5- or 10-year findings from all five SMPY cohorts (totaling more than 5,000 participants), are presented. SMPY has devoted particular attention to uncovering personal antecedents necessary for the development of exceptional math-science careers and to developing educational interventions to facilitate learning among intellectually precocious youth. Along with mathematical gifts, high levels of spatial ability, investigative interests, and theoretical values form a particularly promising aptitude complex indicative of potential for developing scientific expertise and of sustained commitment to scientific pursuits. Special educational opportunities, however, can markedly enhance the development of talent. Moreover, extraordinary scientific accomplishments require extraordinary commitment both in and outside of school. The theory of work adjustment (TWA) is useful in conceptualizing talent identification and development and bridging interconnections among educational, counseling, and industrial psychology. The lens of TWA can clarify how some sex differences emerge in educational settings and the world of work. For example, in the SMPY cohorts, although more mathematically precocious males than females entered math-science careers, this does not necessarily imply a loss of talent because the women secured similar proportions of advanced degrees and high-level careers in areas more correspondent with the multidimensionality of their ability-preference pattern (e.g., administration, law, medicine, and the social sciences). By their mid-30s, the men and women appeared to be happy with their life choices and viewed themselves as equally successful (and objective measures support these subjective impressions). Given the ever-increasing importance of quantitative and scientific reasoning skills in modern cultures, when mathematically gifted individuals choose to pursue careers outside engineering and the physical sciences, it should be seen as a contribution to society, not a loss of talent.

The role of efficacy and identity in science career commitment among underrepresented minority students

Abstract: A web-based survey of members of the Society for the Advancement of Chicanos and Native Americans in Science tested a model that proposed that the effects of science support experiences on commitment to science careers would be mediated by science self-efficacy and identity as a scientist. A sample of 327 undergraduates and 338 graduate students and postdoctoral fellows described their science support experiences (research experience, mentoring, and community involvement); psychological variables (science self-efficacy, leadership/teamwork self-efficacy, and identity as a scientist); and commitment to pursue a career in scientific research. Structural equation model analyses supported our predictions. Among the undergraduates, science (but not leadership/teamwork), self-efficacy, and identity as a scientist fully mediated the effects of science support experiences and were strong predictors of commitment. Results for the graduate/postdoctoral sample revealed a very similar pattern of results, with the added finding that all three psychological mediators, including leadership/teamwork self-efficacy, predicted commitment.