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"Engineering mathematics Study and teaching (Graduate)"
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Structure and belonging: Pathways to success for underrepresented minority and women PhD students in STEM fields
The advancement of underrepresented minority and women PhD students to elite postdoctoral and faculty positions in the STEM fields continues to lag that of majority males, despite decades of efforts to mitigate bias and increase opportunities for students from diverse backgrounds. In 2015, the National Science Foundation Alliance for Graduate Education and the Professoriate (NSF AGEP) California Alliance (Berkeley, Caltech, Stanford, UCLA) conducted a wide-ranging survey of graduate students across the mathematical, physical, engineering, and computer sciences in order to identify levers to improve the success of PhD students, and, in time, improve diversity in STEM leadership positions, especially the professoriate. The survey data were interpreted via path analysis, a method that identifies significant relationships, both direct and indirect, among various factors and outcomes of interest. We investigated two important outcomes: publication rates, which largely determine a new PhD student's competitiveness in the academic marketplace, and subjective well-being. Women and minority students who perceived that they were well-prepared for their graduate courses and accepted by their colleagues (faculty and fellow students), and who experienced well-articulated and structured PhD programs, were most likely to publish at rates comparable to their male majority peers. Women PhD students experienced significantly higher levels of distress than their male peers, both majority and minority, while both women and minority student distress levels were mitigated by clearly-articulated expectations, perceiving that they were well-prepared for graduate level courses, and feeling accepted by their colleagues. It is unclear whether higher levels of distress in women students is related directly to their experiences in their STEM PhD programs. The findings suggest that mitigating factors that negatively affect diversity should not, in principle, require the investment of large resources, but rather requires attention to the local culture and structure of individual STEM PhD programs.
Journal Article
Take me where I want to go: Institutional prestige, advisor sponsorship, and academic career placement preferences
Placement in prestigious research institutions for STEM (science, technology, engineering, and mathematics) PhD recipients is generally considered to be optimal. Yet some doctoral recipients are not interested in intensive research careers and instead seek alternative careers, outside but also within academe (for example teaching positions in Liberal Arts Schools). Recent attention to non-academic pathways has expanded our understanding of alternative PhD careers. However, career preferences and placements are also nuanced along the academic pathway. Existing research on academic careers (mostly research-centric) has found that certain factors have a significant impact on the prestige of both the institutional placement and the salary of PhD recipients. We understand less, however, about the functioning of career preferences and related placements outside of the top academic research institutions. Our work builds on prior studies of academic career placement to explore the impact that prestige of PhD-granting institution, advisor involvement, and cultural capital have on the extent to which STEM PhDs are placed in their preferred academic institution types. What determines whether an individual with a preference for research oriented institutions works at a Research Extensive university? Or whether an individual with a preference for teaching works at a Liberal Arts college? Using survey data from a nationally representative sample of faculty in biology, biochemistry, civil engineering and mathematics at four different Carnegie Classified institution types (Research Extensive, Research Intensive, Master's I & II, and Liberal Arts Colleges), we examine the relative weight of different individual and institutional characteristics on institutional type placement. We find that doctoral institutional prestige plays a significant role in matching individuals with their preferred institutional type, but that advisor involvement only has an impact on those with a preference for research oriented institutions. Gender effects are also observed, particularly in the role of the advisor in affecting preferred career placement.
Journal Article
Educating Software and AI Stakeholders About Algorithmic Fairness, Accountability, Transparency and Ethics
This paper discusses educating stakeholders of algorithmic systems (systems that apply Artificial Intelligence/Machine learning algorithms) in the areas of algorithmic fairness, accountability, transparency and ethics (FATE). We begin by establishing the need for such education and identifying the intended consumers of educational materials on the topic. We discuss the topics of greatest concern and in need of educational resources; we also survey the existing materials and past experiences in such education, noting the scarcity of suitable material on aspects of fairness in particular. We use an example of a college admission platform to illustrate our ideas. We conclude with recommendations for further work in the area and report on the first steps taken towards achieving this goal in the framework of an academic graduate seminar course, a graduate summer school, an embedded lecture in a software engineering course, and a workshop for high school teachers.
Journal Article
Is it transformation or reform? The lived experiences of African women doctoral students in STEM disciplines in South African universities
Science, Technology, Engineering and Mathematics (STEM) fields have historically been disciplines dominated by white men. The colonial ideology designated Africans as subhuman, inferior intellectually, socially, and culturally to the white masculine norm in STEM disciplines. STEM education and careers were thus constructed to attract white, heterosexual, middle-to-upper class, Christian, able-bodied men. This positioning ensured that STEM environments remained inhospitable to anyone whose identity was outside the constructed somatic norm. The calls and imperatives to transform notwithstanding, the transformation process in STEM disciplines is moving at a snail-like pace. This article argues that what is occurring in STEM disciplines in South African universities is reform not transformation. It is underpinned by the intersectional theory within the qualitative paradigm. Seventy-three African doctoral and postdoctoral women students in STEM were interviewed from five South African universities. The findings highlighted how African women in STEM face challenges based on their racial and gendered identities and that what is presented as transformation is still oppressive to them. The study also found that equity through access to education in democratic South Africa does not equate to transformation. The argument presented is that despite existing policies and initiatives in South African universities to transform, the demographic inclusion of African, female staff and students does not necessarily equate to transforming the STEM environment. What needs to occur is a shift beyond reform and towards transformation through the use of strategic inventions which dismantle the racist, sexist, classist, and xenophobic ideology that permeates these environments.
Journal Article
Advancing SoTL through Boundary-Spanning Leadership: A Study of Four CIRTL Institutions
Despite Scholarship of Teaching and Learning (SoTL) advancements, general faculty adoption of effective teaching strategies has been slow, especially within science, technology, engineering, and mathematics (STEM) disciplines. One solution has been to focus on preparing future faculty. The Center for the Integration of Research, Teaching, and Learning (CIRTL) is a national network preparing future STEM faculty for the professoriate through teaching professional development. CIRTL emphasizes a SoTL-parallel concept known as teaching-as-research (TAR), which trains future faculty to integrate research with teaching to promote ongoing pedagogical improvement. The local CIRTL leaders who run institutional-level programs connect their institution to the Network and engage in vital campus-based boundary-spanning roles. However, it is not clear what individual and institutional attributes influence their boundary-spanning behaviors. This article presents the results of four CIRTL institutional case studies that identified six boundary-spanning leadership traits and three institutional characteristics found to influence local CIRTL programs. The article concludes with six boundary-spanning leadership principles that can be applied more generally within the SoTL community.
Journal Article
Walking on Gender Tightrope With Multiple Marginalities
This phenomenological research explored how Asian female international students (AFISs) understand the role of gender in their program experiences and how they cope with the challenges derived from their multiple marginalities—gender, foreign nationality, and race/ethnicity. Based on in-depth interviews with 21 Asian female international graduate students enrolled in various science, technology, engineering, and mathematics (STEM) disciplines, we analyzed the ideological undercurrents embedded in their genderblind perspectives and examined their coping strategies in the context of STEM disciplines. Our thematic findings illustrate the participants’ multiple marginalities as manifested in the concept of “gender advantage,” and the precarious power dynamics and ironic coping strategies that they adopt in undergraduate teaching contexts. This study suggests that STEM educators in higher education understand the multifaceted struggles of AFISs who inevitably embody multiple marginalities in their graduate programs and provide culturally relevant support and advocacy-based professional mentoring.
Journal Article
Regional, institutional, and departmental factors associated with gender diversity among BS-level chemical and electrical engineering graduates
Engineering remains the least gender diverse of the science, technology, engineering and mathematics fields. Chemical engineering (ChE) and electrical engineering (EE) are exemplars of relatively high and low gender diversity, respectively. Here, we investigate departmental, institutional, and regional factors associated with gender diversity among BS graduates within the US, 2010-2016. For both fields, gender diversity was significantly higher at private institutions (p < 1x10-6) and at historically black institutions (p < 1x10-5). No significant association was observed with gender diversity among tenure-track faculty, PhD-granting status, and variations in departmental name beyond the standard \"chemical engineering\" or \"electrical engineering\". Gender diversity among EE graduates was significantly decreased (p = 8x10-5) when a distinct degree in computer engineering was available; no such association was observed between ChE gender diversity and the presence of biology-associated degrees. States with a highly gender diverse ChE workforce had a significantly higher degree of gender diversity among BS graduates (p = 3x10-5), but a significant association was not observed for EE. State variation in funding of support services for K-12 pupils significantly impacted gender diversity of graduates in both fields (p < 1x10-3), particularly in regards to instructional staff support (p < 5x10-4). Nationwide, gender diversity could not be concluded to be either significantly increasing or significantly decreasing for either field.
Journal Article
Practice-Based Teacher Education Benefits Graduate Trainees and Their Students Through Inclusive and Active Teaching Methods
The next generations of science, technology, engineering, and math (STEM) workers are being trained in college and university classrooms by a workforce of instructors who learn pedagogical practice largely on the job. While inclusive instructional practices and their impacts are increasingly well-studied, this training is difficult to instill within the professional development that most STEM professors receive before teaching their students. The Science Teaching Experience Program for Upcoming PhDs (STEP-UP) at the University of Washington was built to prepare future professors for inclusive excellence by guiding them through the literature in education research and providing them a space to practice active and inclusive teaching techniques. This study of STEP-UP uses a design-based approach to understand graduate trainee and undergraduate perceptions of the most salient aspects and outcomes of the program. Our study found that trainees used opportunities to practice inclusive teaching methods with a cohort of their peers, and crucially that these methods were evident in trainee-taught courses through multiple lines of evidence. STEP-UP-trained instructors used inclusive teaching strategies that helped students to feel socioemotionally supported. This study offers a model program that fosters inclusion and equity in undergraduate STEM classrooms through improving teaching professional development for graduate students.
Journal Article
Teaching Computer Programming Using Mathematics: Examples from Middle-School and Graduate School
Our goal is to provide integrated lessons where computer programming concepts are introduced based on mathematics. We consider the development of lessons that would be interesting to our students. At the middle school level, digital video generation is used to introduce coding. At the graduate level, we look at the convergence of machine learning models during training. We introduce middle-school students to computer programming through the use of variables, linear equations, and basic algebraic expressions. We motivate students to create digital images using NumPy arrays by experimenting with number representations and coordinate systems. The students create digital videos by building their video characters and moving them around from frame to frame. At the graduate level, we describe how Real Analysis can be applied in Optimization Theory. The students saw and appreciated the connections between Mathematics and Computer Programming. In the graduate course, the students appreciated the rigorous results on the convergence of neural network models. The approach also produced conditions for guaranteeing that the neural network models are uniformly continuous. We have found that the students strongly appreciated the integration of mathematical concepts into basic and advanced coding courses.
Journal Article