Research: Predicting Achievement and Improving Equity in Engineering Using Contextualized High School Performance

研究：利用具体的高中表现来预测工程成绩并提高工程公平性

• 批准号: 1947114
• 负责人: Michael Bastedo
• 金额: $ 25.44万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-15 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1947114&HistoricalAwards=false
• 关键词: Research; Predicting; Achievement; Improving; Equity

This project seeks to improve the number of well-qualified women, low-income students, and students of color who pursue and obtain postsecondary engineering degrees. Previous NSF-funded research showed that the use of contextualized high school performance in engineering admissions has the potential to increase the number of women, low-income students, and students of color in engineering. Yet surprisingly little is known about how contextualized high school performance relates to student success in engineering. The research that exists, however, suggests that doing well in high school compared to your peers has predictive validity above and beyond the student’s raw credentials. This project will solve significant data, design, and methodological challenges to investigate this question. This project will create a unique dataset drawn from state unit-record data and data from institutional inventories of ABET-accredited engineering programs within that state. The project directly addresses research on the transition from high school to four-year college/university. This project is expected to increase the admittance of underrepresented students into engineering degree programs. Prior research has shown that both admissions offices and national actors are open to changes that support equity and fairness. The research will inform future efforts to improve equity in college admissions, such as the College Board’s Landscape, which has been implemented in over 150 colleges in 2019-2020. This project has the potential to inform not only practices in engineering admissions offices, but also the activities of important national actors such as the College Board, the Coalition for College Access, and Common Application.In this project, this team will investigate the following research questions: Are contextualized high school GPAs and test scores more predictive of engineering outcomes than raw GPAs? Is there a relationship between taking a rigorous high school curriculum and successful engineering outcomes? Are there heterogenous effects for low-income students, underrepresented minority students, and women in engineering? The hypothesis is that students with higher contextualized achievement, either through either contextualized GPAs, SATs, or curriculum selection, will be more likely to succeed in engineering programs, even after conditioning on raw achievement, and that effects will be stronger for women, low-income students, and students of color. This project will utilize unique student unit-record data from the Michigan Department of Education and the Michigan Education Data Center, allowing examination of outcomes for state residents at 15 public ABET-accredited institutions. This study will use quantile regression techniques, which will enable researchers to test the relationship between an independent variable and the entire distribution of a dependent variable, usually divided into quantiles. This technique will be very helpful for this project, where there may be substantial differences in causes and effects across outcomes like first-year GPA and college graduation, rather than simply focusing on the means for those variables. The results will be disseminated through policy briefs, research publications, and work with national leaders on college admissions and engineering.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.

该项目旨在增加合格妇女、低收入学生和有色人种学生攻读和获得中学后工程学位的人数。 以前NSF资助的研究表明，在工程招生中使用情境化的高中表现有可能增加女性，低收入学生和有色人种学生的数量。 然而，令人惊讶的是，人们对情境化的高中表现与学生在工程方面的成功有何关系知之甚少。 然而，现有的研究表明，与同龄人相比，在高中表现良好的预测有效性高于学生的原始证书。 该项目将解决重要的数据，设计和方法的挑战，以调查这个问题。 该项目将创建一个独特的数据集，该数据集来自该州单位记录数据和ABET认证工程项目的机构库存数据。 该项目直接涉及从高中过渡到四年制学院/大学的研究。 预计该项目将增加代表性不足的学生进入工程学位课程的机会。此前的研究表明，招生办公室和国家行为者都对支持公平和公正的变化持开放态度。 该研究将为未来改善大学入学公平性的努力提供信息，例如2019-2020年在150多所大学实施的大学理事会景观。 该项目不仅有可能为工程招生办公室的实践提供信息，还可能为美国大学理事会、大学入学联盟和通用申请等重要国家行为体的活动提供信息。在该项目中，该团队将调查以下研究问题：与原始GPA相比，情境化的高中GPA和考试成绩是否更能预测工程成果？ 在严格的高中课程和成功的工程成果之间有关系吗？ 对低收入家庭的学生、代表性不足的少数民族学生和工程专业的妇女是否有异质性影响？ 该假设是，具有较高情境化成就的学生，无论是通过情境化GPA，SAT还是课程选择，都更有可能在工程项目中取得成功，即使在原始成就的条件下，这种影响对女性，低收入学生和有色人种的影响也会更大。 该项目将利用密歇根州教育部和密歇根州教育数据中心的独特学生单位记录数据，允许在15个公共ABET认证机构检查州居民的结果。 这项研究将使用分位数回归技术，这将使研究人员能够测试自变量和因变量的整个分布之间的关系，通常分为分位数。 这种方法对这个项目非常有帮助，因为在这个项目中，第一年的GPA和大学毕业等结果之间的因果关系可能存在很大差异，而不是简单地关注这些变量的平均值。 该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。