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Contextualize to Learn: Preparing Faculty Toward Math Contextualization for Student Success in Advanced Technological Education

情境化学习：让教师为数学情境化做好准备，以帮助学生在先进技术教育中取得成功

基本信息

批准号：
1700625
负责人：
Xueli Wang
金额：
$ 79.95万
依托单位：
University of Wisconsin-Madison
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-06-01 至 2022-05-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1700625&HistoricalAwards=false
关键词：
Contextualize Learn Preparing Faculty Toward

项目摘要

Competency in mathematics is the cornerstone of educational and career success in the Nation's established and emerging technical fields in Science, Technology, Engineering, and Mathematics (STEM). At the same time, completing courses and mastering mathematics remain major areas of struggle for students who are pursuing degrees and certification in advanced technological programs at community and technical colleges. Building on findings from a pilot study, the research team composed of university researchers and faculty and institutional researchers at 2-year colleges will investigate the adaptation, implementation, and outcomes of contextualized mathematics, a promising instructional approach designed to improve teaching and learning mathematics by connecting mathematics with academic/occupational content and applications in the workplace. Integrating quantitative and qualitative approaches, the mixed methods research study examines faculty professional development, adaptation and implementation of contextualized mathematics in the classroom, and the impact of contextualized mathematics on students' educational and career outcomes in advanced manufacturing, engineering technology, biotechnology, construction technology, and transportation technology. Using a convergent parallel mixed methods design, this targeted research study is designed to investigate faculty engagement with and professional development around contextualized mathematics and its impact on students. Two critical areas are examined: a) the development of faculty expertise through faculty development and communities of practice, and b) the interim and longer-term impact on student outcomes through the lens of momentum theory, a model of community college student success. Qualitative data collected by in-depth interviews will be analyzed using the constant comparative method to assess data saturation and stability of data categories. Quantitative data include administrative records, surveys, and classroom observations. Surveys will be piloted and validated using exploratory and confirmatory factor analyses. Classroom observation data will be analyzed using social network analysis. In order to adjust for pre-treatment characteristics of students for establishing balanced comparison groups, the research study applies propensity score matching to address selection bias (enrollment in contextualized mathematics courses). Path analysis will be used to estimate the treatment effect of contextualized mathematics and the potential causal pathways through which contextualized mathematics works (e.g., increased cognitive, metacognitive, and motivational momentum). Convergent analysis will examine the extent to which and the ways in which results from different data sources converge, diverge, and/or connect within and across faculty and student threads of the research. Accordingly, the study will provide a complex and nuanced understanding of the relationships among faculty development, adaptation and implementation of contextualized mathematics in the classroom, and the impact of contextualized mathematics on teaching, learning, and career success.

数学能力是国家在科学，技术，工程和数学（STEM）的既定和新兴技术领域的教育和职业成功的基石。与此同时，完成课程和掌握数学仍然是在社区和技术学院攻读高级技术课程学位和认证的学生的主要斗争领域。基于试点研究的结果，由大学研究人员和两年制大学的教师和机构研究人员组成的研究小组将调查情境化数学的适应，实施和结果，这是一种有前途的教学方法，旨在通过将数学与学术/职业内容和工作场所的应用联系起来来改善教学和学习数学。结合定量和定性的方法，混合方法研究考察教师的专业发展，适应和实施情境化数学在课堂上，和情境化数学对学生的教育和职业成果的影响，在先进制造业，工程技术，生物技术，建筑技术和运输技术。使用收敛并行混合方法设计，这项有针对性的研究旨在调查教师参与和专业发展周围的情境化数学及其对学生的影响。两个关键领域进行检查：a）通过教师发展和实践社区的教师专业知识的发展，和B）通过势头理论的透镜，社区学院学生成功的模式，对学生的成绩的中期和长期的影响。通过深入访谈收集的定性数据将采用持续比较法进行分析，以评估数据饱和度和数据类别的稳定性。定量数据包括行政记录、调查和课堂观察。将使用探索性和验证性因素分析对调查进行试点和验证。课堂观察数据将使用社交网络分析进行分析。为了调整学生的治疗前特征，以建立平衡的比较组，本研究采用倾向分数匹配来解决选择偏差（在情境化的数学课程入学）。路径分析将用于估计情境化数学的治疗效果以及情境化数学发挥作用的潜在因果路径（例如，增加认知、元认知和动机动力）。收敛分析将检查在何种程度上，以及在何种方式，从不同的数据源的结果收敛，发散，和/或连接内部和跨教师和学生的研究线程。因此，这项研究将提供一个复杂和细致入微的理解教师的发展，适应和实施情境化的数学在课堂上，和情境化的数学对教学，学习和职业成功的影响之间的关系。