Identifying Motivating Factors of Undergraduate Women Pursuing Physics Degrees

该奖项支持基金分析攻读本科物理学位的女性确定的动机因素。该项目将开发定性方法和自然语言处理(NLP)，以在现有数据集中识别积极和消极的动机因素，这些数据集由书面叙述组成，描述了鼓励或阻碍女性攻读物理学位的因素。该项目还将开发一个NLP文本分类器和一种将性别和族裔分类的方法，从而使横向分析成为可能。NLP算法的初步定性分析和开发将利用作为美国物理学会会议为本科生女性物理评估调查的一部分收集的数据。通过使用NLP算法来分析美国物理研究所统计研究中心的物理学士后续调查收集的数据，该分析将得到扩展。该项目将通过深入了解促使妇女攻读物理学学位的因素，促进妇女在物理学领域的代表性。这一知识允许扩大有针对性的干预措施和外联努力，以鼓励妇女从事物理职业。此外，按性别、种族和族裔分类数据将增加吸引有色人种女性或性别非二元人士参与的途径。作为该项目的一部分，开发的资源将与美国物理研究所统计研究中心和美国物理学会的教育和多样性部门共享。这两个大型物理专业组织将支持这些方法的进一步使用和发展，从而潜在地影响许多未来的物理学家。这一奖项反映了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。

This award supports the funding to analyze the motivational factors identified by women pursuing undergraduate physics degrees. This project will develop qualitative methods and natural language processing (NLP) to identify positive and negative motivating factors in existing datasets consisting of written narratives that describe the factors that encouraged or discouraged women from pursuing physics degrees. This project will also develop an NLP text classifier and a methodology for disaggregation of gender and ethnicity, making intersectional analyses feasible. The initial qualitative analysis and development of the NLP algorithm will utilize data collected as part of the American Physical Society Conferences for Undergraduate Women in Physics evaluation survey. The analysis will be extended by using the NLP algorithm to analyze data collected by the American Institute of Physics Statistical Research Center's Follow-up Survey of Physics Bachelors. This project will promote the representation of women in physics by developing an in-depth understanding of the factors motivating women to pursue physics degrees. This knowledge allows for the expansion of targeted interventions and outreach efforts to encourage women into physics careers. Furthermore, disaggregating data by gender, race, and ethnicity will increase the avenues for engaging women of color or gender non-binary persons. The resources developed as part of this project will be shared with the American Institute of Physics Statistical Research Center, and the American Physical Society's Education and Diversity department. These two large professional organizations in physics will support further use and development of these methods, thereby potentially impacting many future physicists.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.