Collaborative Research: Building on STEP to Understand Variation in STEM Entry and Persistence

这个为期四年的混合方法研究项目调查了学生选择进入和离开学习领域的过程，以及由STEP资助的项目如何影响这些过程。基于埃克尔斯的预期价值模型，这项研究调查了学生获得STEM学士学位的途径，以及不同类型的干预措施对不同学生和STEM专业的这些途径的影响。本研究关注学生学业准备、对未来学业表现的主观期望、客观学业表现、学生对STEM课程和专业的任务价值，以及学生可以从中获得个人和学业支持的人际关系之间的关系。以参与院校一年级新生的分层概率样本为基础的对照分组设计，得到了具有代表性的新生人群样本。该设计包括两个控制组和一个提高外部效度的处理组：一个队列只包括STEM学生在STEP类型I项目(控制条件1)设计的干预开始前一年进入大学。第二组学生包括参加第一步活动的STEM学生(治疗条件)和不参加第一步活动的学生(对照条件2)。数据包括机构学生记录和学生对为这项研究设计的调查的反应。此外，该项目正在建设一个数据基础设施，供研究人员进一步研究和STEP项目使用。

This four-year mixed methods research project investigates the processes by which students select into and out of fields of study and of how projects funded by STEP impact these processes. Grounded in Eccles' expectancy value-model, the research study examines student pathways to STEM baccalaureate degrees and the impact of different types of interventions on those pathways across diverse students and STEM majors. The research focuses on the relationships among student academic preparation, subjective expectations with respect to future academic performance, objective academic performance, the tasks values students ascribe to STEM courses and majors, and interpersonal relationships from which students may draw personal and academic support. The comparison group design based on stratified probability samples of first-time first-year students from the participating institutions results in representative samples of the population of entering first-time students. The design includes two control groups and one treatment group to increase external validity: One cohort includes only STEM students who enter the university in the year prior to the start of the intervention designed by STEP Type I projects (control condition 1). The second cohort of students includes STEM students who participate in STEP Type 1 activities (treatment condition) and those who do not (control condition 2). Data include institutional student records and student responses to surveys designed for the study. In addition, the project is constructing a data infrastructure for further research by researchers and use by STEP projects.