Evaluating Letters of Reference to Engineering Doctoral Programs for Racial and Gender Bias

STEM的高级培训和教育对国家的劳动力和经济地位至关重要。平等获得研究生水平的培训减少了来自小规模群体的个人的障碍。标准化的研究生考试在研究生招生过程中变得越来越不重要，后者在挑选研究生项目时更看重推荐信。这个项目的重点是检查导师在推荐信中描述学生时使用的语言，并试图确定在应用可能延长招生差距的关键词或短语时存在的种族和性别偏见。专业发展计划将通过开发技能、方法和基于文本的数据分析来建设工程教育研究的能力。该项目的目标是确定在基于性别和种族/民族的推荐信中描述申请人在工程领域成功的潜力的方式的差异，并在培养基于文本的数据分析技能的同时加深对纪律实践、价值观和规范的理解。该项目以角色一致性理论和刻板印象内容模型理论为基础，将使用定性方法、内容分析和自然语言处理技术来识别和比较推荐信中使用的语言。该项目旨在创造一个没有种族和性别偏见的工程学研究生招生示范图景，而不是用于其他学科的类似调查。该项目由NSF的STEM教育研究中的EHR核心研究能力建设计划(ECR：BCSER)支持，该计划旨在建设研究人员开展高质量STEM教育研究的能力。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。

Advanced training and education in STEM are of critical importance for the nation’s workforce and economic status. Equitable access to graduate level training reduces barriers for individuals from minoritized groups. Standardized graduate exams are becoming less important in the graduate admissions process, which places a higher weight on letters of recommendation for the selection of graduate students for a program. This project focuses on examining the language used by mentors in describing students in letters of recommendations and seeks to identify racial and gender bias in the application of key words or phrases that may perpetuate enrollment disparities. The professional development plan will build capacity in engineering education research through development of skills, methods, and text-based data analyses.The goals of the project are to identify differences in the way an applicant’s potential for success in engineering is described in letters of recommendation based on their gender and race/ethnicity and develop a deeper understanding of disciplinary practices, values, and norms while building skills in text-based data analysis. Founded on role congruity theory and stereotype content model theory, the project will use qualitative methods, content analysis, and natural language processing techniques to identify and compare language used in letters of recommendation. The project aims to produce a model engineering graduate admissions landscape that is free of race and gender biases than can be used for similar investigations of other disciplines. The project is supported by NSF's EHR Core Research Building Capacity in STEM Education Research (ECR:BCSER) program, which is designed to build investigators’ capacity to carry out high-quality STEM education research.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.