Expanding STEM Talent Through Upward Transfer: Factors Influencing Transfer in STEM Fields of Study from Two-Year to Four-Year Institutions

两年制大学是国家教育体系的重要组成部分，在科学、技术、工程和数学（STEM）的成熟和新兴领域日益被认为至关重要。然而，关于影响学生从两年制大学转入四年制大学STEM领域学习的因素的研究有限。根据社会认知职业理论，该项目将开发和完善一个STEM迁移模型，该模型假设STEM迁移受人口因素、情境因素、STEM学习经历以及与STEM学习和迁移相关的动机信念的影响。这项为期四年的纵向混合方法研究项目将调查STEM的转移，并将推进和测试一个高等教育STEM途径模型，以获得STEM的学士学位和职业生涯，或者在STEM中获得其他教育和职业成就。研究团队将跟踪3000名在威斯康星州两年制社区和技术学院开始学习STEM课程或STEM课程所需课程的学生，并研究在研究期间促进或阻碍他们转入四年制学院和大学STEM专业的因素。本研究采用以定量方法为主、定性方法为辅的解释序贯混合方法设计。定量阶段将包括收集和分析参与院校的学生行政记录，并结合一项新的STEM转学纵向调查的学生数据。为了建立建构效度，研究团队将进行探索性因子分析，以确定因子结构。随后将进行验证性因素分析。随着每一波调查数据的获得，将进行额外的因素分析。将进行三波数据收集。结构方程模型（SEM）将用于分析多变量数据和测试理论框架。扫描电镜定义潜在变量和观察变量，同时测试假设变量之间的直接和间接关系。访谈和焦点小组样本将有目的地从调查参与者中选择。虽然具体的选择标准将取决于对调查数据的分析，但预计强度抽样、最大变化抽样和/或同质抽样的组合将是最可行的策略，可以更深入地了解定量结果确定的影响STEM迁移的因素。演绎引导和归纳基础的数据分析将被用来发现访谈和焦点小组定性数据的共同主题。该项目将推进STEM迁移的知识基础，并有助于这一重要研究领域的理论建设。

Two-year institutions are essential components of the nation's education system and increasingly recognized as critically important in established and emerging areas of science, technology, engineering, and mathematics (STEM). However, there is a limited body of research examining what influences student transfer from two-year colleges into STEM fields of study at four-year institutions. Drawing upon social cognitive career theory, the project will develop and refine a STEM transfer model that hypothesizes that STEM transfer is influenced by demographic factors, contextual factors, learning experiences in STEM, and motivational beliefs related to STEM learning and transfer. The four-year longitudinal mixed methods research project will investigate STEM transfer and will advance and test a model of postsecondary STEM pathways to the baccalaureate and careers in STEM or to alternative educational and occupational attainment in STEM. The research team will follow a cohort of 3,000 students beginning in STEM programs or courses required for STEM programs at two-year community and technical colleges in Wisconsin and study factors that facilitate or hinder their transfer into a STEM major at 4-year colleges and universities during the study period. The research adopts an explanatory sequential mixed methods design in which the quantitative approach is dominant and is followed by a complementary qualitative approach. The quantitative phase will consist of collection and analysis of students' administrative records from participating institutions integrated with students' data from a new longitudinal survey on STEM transfer. To establish construct validity, the research team will perform exploratory factor analysis to identify the factor structure. This will be followed by a confirmatory factor analysis. Additional factor analyses will be ongoing as each wave of the survey data becomes available. Three waves of data collection will be conducted. Structural equation modeling (SEM) will be used to analyze the multivariate data and to test the theoretical framework. SEM defines latent and observed variables while testing the direct and indirect relationships among variables that are hypothesized. The interview and focus group sample will be purposively selected from survey participants. While specific selection criteria will depend on the analysis of the survey data, it is anticipated that a combination of intensity sampling, maximum variation sampling and/or homogenous sampling will be the most viable strategies to provide more depth and insight into the factors influencing STEM transfer as identified by quantitative findings. Deductively guided and inductively grounded data analyses will be utilized to discover common themes across interview and focus group qualitative data. The project will advance the knowledge base on STEM transfer and contribute to theory building in this important area of study.