A Randomized Control Study to Determine the Impact of Learning Communities that Link Three Undergraduate, First-Year Science and Mathematics Courses

该项目服务于国家利益，致力于提高学生在理工科课程中的留存和表现。许多机构将学生分组放在相同的课程部分，从而在学习社区中将学生联系在一起。这样的学习社区是留住科学、技术、工程和数学(STEM)领域学生的许多努力的组成部分。尽管这种方法经常被使用，但到目前为止，很少有严谨的科学研究来探索这些联系在一起的社区的有效性。本项目旨在通过将学生随机分配到有联系的社区或没有联系的控制组来完成这样一项研究。为了为这项研究建立社区，注册了同样三门STEM入门课程的学生小组将被安排参加以当代问题为重点的小型研讨会课程，如生物燃料或获得清洁水。通过调查学生的归属感和他们继续学习STEM课程的动机，将确定作为一个小组进入同一个班级的效果。该项目希望找出为什么身处相互联系的社区可以提高学生成绩和留住学生的可能原因。这项研究还将调查哪些学生群体受到参与联系社区的影响最大。这一分析的结果将为这些社区是否是增加STEM多样性的可行方法提供指导。通过这种方式，这个项目有可能更好地了解这些社区是如何以及为什么运作的，从而提供了一条在其他机构复制的可能途径。我们将采用数学分位分数和分层随机抽样的方法，将全日制STEM专业的一年级学生分成四组：在相关社区的STEM初始课程作业；与社区无关的初始STEM课程作业(即对照)；在关联社区的STEM前专业课程作业(即对照)；以及与社区无关的STEM前专业课程作业(即对照)。这种抽样方法将确保群体代表东道国机构的性别、收入、种族、第一代身份和居住/通勤身份的多样性。队列运行两年，每个试验组至少积累80名学生，每个对照组至少积累120名学生。分层线性模型将被用来衡量学习社区对学生成绩和留存的影响。将使用重复测量ANCOVA来比较前后对调查变量(即归属感、社会资本、STEM动机和公众对科学的看法)的反应。协变量将包括相关的人口统计变量和先前存在的学习能力和表现的标记。将进行中介分析，以确定调查测量的心理变量(即归属感、社会资本、STEM动机和社区对科学的看法)是否在参与学习社区和成绩与保持之间的关系中起中介作用。最后，每一项分析也将作为关键人口变量的群体比较进行，包括种族、性别、通勤者/居住状况和第一代人的状况。通过这种方式，该项目不仅将测试学习社区是否总体上影响了学生的成功，而且还将测试它们是否平等地影响了所有学生群体。NSF IUSE：EHR计划支持研究和开发项目，以提高所有学生的STEM教育的有效性。通过参与的学生学习路径，该计划支持有前景的实践和工具的创建、探索和实施。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。

This project serves the national interest by working to improve the retention and performance of students in science and engineering courses. Many institutions place groups of students into the same course sections, thus linking students together in learning communities. Such learning communities are a component of many efforts to retain students in science, technology, engineering, and mathematics (STEM) fields. Although the approach is often used, thus far there have been very few rigorous scientific studies that probe the effectiveness of these linked communities. This project intends to complete such a study using randomized assignment of students to linked communities or to an unlinked control group. To set up communities for the study, groups of students enrolled in the same three introductory STEM courses, will be placed into small seminar classes focused on contemporary issues such as biofuels or access to clean water. The effects of being linked as a group into the same classes will be determined by investigating the students’ sense of belonging and their motivation to continue their STEM coursework. The project hopes to identify possible reasons why being in linked communities can improve student grades and retention. The study will also examine which groups of students are most impacted by participation in the linked community. Results of this analysis will provide guidance about whether these communities are a viable approach to increase diversity in STEM. In this way, this project has the potential to offer a greater understanding about how and why these communities work, and thus offer a possible path to replication at other institutions. Mathematics placement scores and stratified random sampling will be employed to place first-year, full-time STEM majors into one of four groups: initial STEM coursework in a linked community; initial STEM coursework unaffiliated with a community (i.e., controls); pre-STEM major coursework in a linked community; and pre-STEM major coursework unaffiliated with a community (i.e., controls). This sampling method will ensure that groups represent the gender, income, racial, first-generation status, and residential/commuter status diversity of the host institution. Cohorts will be run for two years, accumulating at least 80 students in each experimental group and at least 120 students in each control group. Hierarchical linear modeling will be used to measure the effect of the learning communities on student grades and retention. A repeated-measures ANCOVA will be used to compare the pre/post responses to survey variables (i.e., sense of belonging, social capital, STEM motivation, and communal perceptions of science). Covariates will include relevant demographic variables and pre-existing markers of academic ability and performance. A mediation analysis will be conducted to see if the psychological variables measured by the survey (i.e., sense of belonging, social capital, STEM motivation, and communal perceptions of science) mediate the relationships between participation in the learning communities and grades and retention. Finally, each of the analyses will also be conducted as group comparisons on key demographic variables, including race, gender, commuter/residential status, and first-generation status. In this way, the project will test not only whether the learning communities affected student success overall, but also whether or not they affected all groups of students equally. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.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.