Research: Characterizing Postdoctoral Education, Mentorship, Gender, and Race in the Formation of Academic Engineers and Computer Scientists

博士后教育可以在未来计算机科学(CS)或工程教员的研究成功中发挥关键作用，但这些经验在工程学和CS教育文献中尚未得到研究。国家科学和工程统计中心(NCSES)对科学和工程专业研究生和博士后的调查显示，每年有近8600名博士后学者在工程学和计算机科学领域获得资助；然而，博士后任命缺乏多样性令人担忧。例如，有色人种女性在各自领域的博士后学者中所占比例远低于0.5%。通过教师指导促进博士后任命，帮助学者培养更深层次的方法和内容能力、研究管理技能以及写作、出版和研究技能，为未来的学术生涯做准备。考虑到完成至少一个博士后研究职位对于工程学和CS专业的学生来说是很常见的，为竞争激烈的学术生涯做准备，这些数字可以帮助解释女性和有色人种在教授职位中代表性持续不足的原因。为此，这项资助的目的是表征工程学和计算机科学学者的知识、技能、属性和能力的发展，收集博士后-导师二元组中两个利益相关者的观点，明确关注同性和跨性别和种族差异。本项目通过交叉性和三个目标的导师制的视角，解决缺乏关于博士后发展的学术工作。目标1试图描述博士后学者应该通过他们的任命发展的知识、技能、能力和属性。目标2将从同、跨性别和种族二元的博士后导师和博士后学者的角度来研究博士后社会化和能力发展的叙事。目标3将使用自然语言处理方法，将研究结果与博士后指导和指导的可用资源进行比较。这项研究是通过两个理论镜头来框架的。领导-成员交换理论关注的是主管工作关系中双方的交易性质。交叉性理论承认与种族相关的内在力量和地位，同时也承认那些处于种族和性别交叉点的人存在着放大的复杂性。使用这两个镜头，现有的学术社会化理论可以扩展到博士后教育。研究的第一阶段是基于调查和访谈，以两种不同的数据收集格式从教师和博士后学者那里收集信息，以满足项目的前两个目标。量化结果将为研究的半结构化面试部分提供背景和参与者池，这将突出不同群体在计算机科学和工程学博士后职位上继续代表不足和被边缘化的潜在原因。定量和定性研究将为第二阶段的研究提供信息，在该阶段中，将使用自然语言处理和其他机器学习工具对互联网上免费提供的博士后指导工具、计划和指南进行评估。第二阶段的数据将表明如何改进和实施博士后指导计划和资源，以支持博士后和导师的专业和个人发展。预期的结果包括，导师计划总体上没有解决多样性、公平性和包容性，也没有提出帮助教师在博士后学者中建立多样性的建议。工程学和计算机科学系的博士后导师资源可能不会强调跨性别和/或跨种族导师关系带来的机会和潜在困难。该项目的成果包括研讨会和资源，以改善博士后及其导师的博士后指导体验。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Postdoctoral education can play a critical role in future research success of computer science (CS) or engineering faculty members, but these experiences are under-studied in engineering and CS education literature. The National Center for Science and Engineering Statistics (NCSES) Survey of Graduate Students and Postdoctorates in Science and Engineering indicates that there are nearly 8600 postdoctoral scholars funded per year across engineering and CS; however, the lack of diversity in postdoctoral appointments is alarming. For example, women of color comprise well below 0.5% of postdoctoral scholars in their fields. Postdoctoral appointments are facilitated through faculty mentorship to help scholars develop deeper methodological and content competency, research management skills, and writing, publishing, and researching skills in preparation for a future academic career. Given that completing at least one postdoctoral research position is common for engineering and CS students preparing for competitive academic careers, these numbers can help explain continued underrepresentation of women and people of color in the professoriate. To this end, the purpose of this grant is to characterize the development of knowledge, skills, attributes, and competencies in engineering and computer science scholars, collecting perspectives of both stakeholders in the postdoc-mentor dyad with an explicit focus on same- and cross- gender and race dyads.This project addresses the lack of scholarly work about postdoctoral development through the lens of intersectionality and mentorship across three aims. Aim 1 seeks to characterize the knowledge, skills, competencies, and attributes that postdoctoral scholars should develop through their appointments. Aim 2 will investigate narratives of postdoctoral socialization and competency development from the points of view of postdoctoral advisors and postdoctoral scholars from same- and cross- gender and race dyads. Aim 3 will use natural language processing methods to compare findings with available resources for postdoctoral mentorship and supervision. This study is framed through two theoretical lenses. Leader-member exchange theory focuses on the transactional nature of dyads in supervisory working relationships. Intersectionality theory recognizes the inherent power and positioning associated with race while also acknowledging the amplified complexity that exists for those that are situated at the intersection of race and gender. Existing theories of academic socialization can be expanded for postdoctoral education using these two lenses. Phase 1 of research is survey- and interview-based to collect information from faculty and postdoctoral scholars in two different data collection formats to meet the first two aims of the project. The quantitative results will provide context and a participant pool for the semi-structured interview portion of the research, which will highlight potential reasons for the continued underrepresentation and marginalization of diverse groups in CS and engineering postdoctoral positions. The quantitative and qualitative research will inform the second phase of research in which with freely available postdoctoral mentoring tools, plans, and guidelines available on the internet will be evaluated using natural language processing and other machine learning tools. The data from Phase 2 will indicate how postdoctoral mentoring plans and resources can be improved and enacted to support professional and personal development of both postdocs and mentors. Expected results include that mentorship plans in general do not address diversity, equity, and inclusion, or suggestions to help faculty build diversity in their postdoctoral scholars. and that postdoctoral mentorship resources for engineering and CS departments may not emphasize the opportunities and potential difficulties that come with cross-gender and/or cross-race mentorship relationships. Deliverables for this project include workshops and resources to improve postdoctoral mentoring experiences for both postdocs and their mentors.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.