Studying Undergraduate Curricular Complexity for Engineering Student Success (SUCCESS)

随着对工程专业毕业生需求的增长，人们越来越有兴趣了解是什么阻止了学生完成学位。并非每个人都遵循相同的途径获得工程学位;当前的纵向研究表明，学生亚群采取不同的途径完成或放弃学业。因此，BPE计划旨在支持了解系统性障碍的研究，这些障碍将学生从服务不足的社区中推出来。该项目将研究所有学生在攻读工程学位时必须克服的障碍，即课程本身。一个名为Curriculum Analytics的新兴框架提供了一种思考如何分析工程课程的新方法。该框架量化了课程的特点，使其“复杂”，使他们可以连接到毕业率等成果。该项目将使用一个名为工程纵向发展多机构数据库（中场）的纵向数据集，其中包含1987年至2018年美国21所大学本科生的近200万条记录-其中14.4%是工程专业学生。使用这些数据，学生的课程学习轨迹将被创建，聚类，以找到基于课程复杂性的衡量标准的模式，并与跨工程学科的既定课程进行比较，然后分解为亚群。这个项目有可能使管理人员，课程设计师和顾问了解教师和学生的偏差所定义的课程的复杂性如何影响不同学生群体的成功。该项目将从课程复杂性的角度来研究什么样的课程，如第一年的经验，招生模式和课程顺序，支持不同的学生亚群的保留和毕业。为了探索课程因素对不同学生造成的障碍，课程分析框架的措施将被应用于捕捉课程的顺序和相互联系的定量和研究不同的学生途径-无论是编纂和经验丰富。指导性的研究问题是：什么是在课程复杂性的变化之间的以下阶层-机构，学科，入学模式，人口和途径-在何种程度上课程复杂性与不同的人口亚组的结果？该项目将结合联合收割机课程的复杂性与学生的成绩和课程从多机构数据库调查工程纵向发展（中场）的数据，以了解课程因素，扩大参与工程，包括保留和学位完成。该项目将涉及使用关联分析从学生课程数据创建轨迹。这些轨迹的课程复杂性将被计算和分解在感兴趣的阶层。这些新数据将用于探索生态系统指标（如学科粘性和迁移率）的课程复杂性如何与课程的复杂性相关。中场数据库与课程复杂性框架的结合，可以带来一个新的视角，在扩大参与的背景下，工程专业学生的学位获得和保留的纵向研究的差异。目前，课程复杂性是一个新兴的框架，具有描述性和解释性的潜力，如课程质量与课程复杂性的措施。实证结果可以直接告知未来的课程修订和政策的努力，在研究机构通过独特的报告提供给适当的行政利益相关者。通过将这些结果直接传播给机构利益相关者，该项目将利用中场的潜力进行分解，以影响课程和计划层面上工程学中代表性不足的学生的包容性努力。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。

As the demand for engineering graduates grows, there has been mounting interest in understanding what prevents students from completing their degrees. Not everyone follows the same pathway to an engineering degree; current longitudinal research suggests that subpopulations of students take different routes to either completing or abandoning their studies. Accordingly, the BPE program seeks to support research on understanding systematic barriers that push out students from underserved communities. This project will examine a barrier that all students must overcome when pursuing an engineering degree, the curriculum itself. An emerging framework called Curricular Analytics has provided a new method of thinking about how curricula in engineering can be analyzed. The framework quantifies features of the curriculum that make it “complex” such that they can be connected to outcomes like graduation rates. This project will use a longitudinal dataset called the Multi-Institution Database for Engineering Longitudinal Development (MIDFIELD), which contains nearly two million records from undergraduate students at 21 U.S. universities from 1987 through 2018 – 14.4 % of which are engineering students. Using these data, student course-taking trajectories will be created, clustered to find patterns based on measures of curricular complexity and compared to established curricula across engineering disciplines, then disaggregated into subpopulations. This project has the potential to empower administrators, curriculum designers, and advisors to understand how the complexity of the curriculum as defined by faculty and students’ deviances from it affects the success of different subpopulations of students. The project will use the perspective of curricular complexity to examine what kinds of programs such as first year experiences, enrollment models, and course sequencing that support the retention and graduation of different subpopulations of students.To explore what barriers curricular factors impose on different students, the Curricular Analytics framework’s measures will be applied to capture a curriclum’s sequencing and interconnectedness quantitatively and study diverse student pathways - both as codified and as experienced. The guiding research question is: what is the variation in curricular complexity among the following strata – institutions, disciplines, matriculation models, populations, and pathways – and to what extent does curricular complexity relate to outcomes for diverse population subgroups? This project will combine curricular complexity with student outcomes and course-taking data from the Multiple-Institution Database for Investigating Engineering Longitudinal Development (MIDFIELD) to understand curricular factors in broadening participation in engineering, including retention and degree completion. This project will involve creating trajectories from student course-taking data using association analysis. The curricular complexity for these trajectories will be calculated and disaggregated across the strata of interest. These new data will be used to explore how curricular complexity for ecosystem metrics like discipline stickiness and migration yield are related to the complexity of a curriculum. The combination of the MIDFIELD database with the curricular complexity framework can bring a new perspective on differences in longitudinal studies on engineering student degree attainment and retention in the context of broadening participation. Currently, curricular complexity is a nascent framework with descriptive and explanatory potential, such as correlating program quality with curricular complexity measures. The empirical results can directly inform future curriculum revisions and policy efforts at the studied institutions through unique reports delivered to the appropriate administrative stakeholders. By disseminating these results directly to institutional stakeholders, The project will leverage MIDFIELD’s potential for disaggregation to impact inclusion efforts of underrepresented students in engineering at the curricular and programmatic level.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.