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

通过向上转移扩大 STEM 人才：影响 STEM 学习领域从两年制到四年制机构转移的因素

• 批准号: 1430642
• 负责人: Xueli Wang
• 金额: $ 140万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1430642&HistoricalAwards=false
• 关键词: Expanding; STEM; Talent; Through; Upward

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.

两年制院校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）的成熟和新兴领域越来越被视为至关重要。 然而，有一个有限的研究机构，研究是什么影响学生从两年制大学转入四年制大学的STEM研究领域。 根据社会认知职业理论，该项目将开发和完善一个STEM转移模型，该模型假设STEM转移受到人口因素，背景因素，STEM学习经验以及与STEM学习和转移相关的动机信念的影响。 为期四年的纵向混合方法研究项目将调查STEM转移，并将推进和测试中学后STEM途径的模式，以获得学士学位和STEM职业或STEM的替代教育和职业成就。 该研究小组将跟踪一组3,000名学生，他们从威斯康星州两年制社区和技术学院的STEM项目或STEM项目所需的课程开始，并研究促进或阻碍他们转入STEM专业的因素。 本研究采用解释性序贯混合方法设计，以定量方法为主，定性方法为辅。 定量阶段将包括收集和分析参与机构的学生行政记录，并结合新的STEM转移纵向调查的学生数据。 为了建立结构效度，研究小组将进行探索性因素分析，以确定因素结构。 随后将进行验证性因素分析。 随着每一波调查数据的获得，将继续进行更多的因素分析。 将进行三次数据收集。 将使用结构方程模型（SEM）分析多变量数据并测试理论框架。 SEM定义潜在变量和观察变量，同时检验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出。 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/或均匀抽样的组合将是最可行的策略，以提供对定量结果确定的影响STEM转移的因素的更深入和更深入的了解。 将利用演绎引导和归纳接地数据分析，以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转移的知识基础，并有助于这一重要研究领域的理论建设。