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

该项目通过努力提高学生在科学和工程课程中的保留率和表现来服务于国家利益。许多机构将学生分组放在同一个课程部分，从而将学生在学习社区中联系在一起。 这样的学习社区是许多努力的一部分，以留住学生在科学，技术，工程和数学（STEM）领域。 虽然这种方法经常被使用，但迄今为止，很少有严格的科学研究来探索这些相互联系的社区的有效性。 本项目旨在通过将学生随机分配到有联系的社区或无联系的对照组来完成这样一项研究。 为了建立研究社区，参加相同的三门STEM入门课程的学生将被安排到小型研讨班，重点关注生物燃料或清洁水的获取等当代问题。 作为一个群体被链接到同一个班级的影响将通过调查学生的归属感和他们继续他们的STEM课程的动机来确定。 该项目希望找出可能的原因，为什么在联系社区可以提高学生的成绩和保留。 该研究还将研究哪些学生群体最受参与相关社区的影响。 这项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，该项目有可能使人们更好地了解这些社区如何以及为什么工作，从而为其他机构提供复制的可能途径。将采用数学分班分数和分层随机抽样将第一年的全日制STEM专业学生分为四组之一：在一个有联系的社区中的初始STEM课程;与社区无关的初始STEM课程（即，控制）;在一个链接的社区的预STEM主要课程;和预STEM主要课程不隶属于一个社区（即，对照）。这种抽样方法将确保各群体代表收容机构的性别、收入、种族、第一代身份和居住/通勤身份的多样性。研究为期两年，每个实验组至少80名学生，每个控制组至少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保留的影响。将使用重复测量ANCOVA比较调查变量的前/后响应（即，归属感，社会资本，STEM动机和对科学的共同看法）。协变量将包括相关的人口统计学变量和预先存在的学术能力和表现的标志物。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）调解了学习社区参与与成绩和保留之间的关系。最后，每项分析还将作为关键人口统计变量的组比较进行，包括种族、性别、通勤/居住状况和第一代状况。通过这种方式，该项目不仅将测试学习社区是否影响学生的整体成功，而且还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STEM教育的有效性。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。

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.