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MATH: EAGER Building a mathematical toolkit and motivation for success in the physical and quantitative sciences

MATH: EAGER Building a mathematical toolkit and motivation for success in the physical and quantitative sciences
数学:渴望建立数学工具包以及在物理和定量科学领域取得成功的动力
批准号:
1544225
负责人:
Jill Sible
金额:
$29.7万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-09-01 至 2019-08-31

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This project targets the mathematics preparation gap which often contributes to the low success rate in introductory STEM courses. The Virginia Tech Quantitative Tools Working Group (QTWG) project will bring together teams of faculty and students who will work collaboratively to develop effective learning activities to help students retain and apply critical math skills for their STEM majors. The QTWG project will address the mathematics preparation gap by synthesizing the work of three innovative STEM programs that share the goal of improving success and retention in undergraduate STEM majors: 1) an NSF STEP Summer Bridge Program targeting underrepresented physical and quantitative science majors; 2) an Integrated Science Curriculum (ISC) where undergraduates learn foundational science and mathematics through an interdisciplinary problem-based curriculum, and 3) a Physics First-Year Experience (FYE) that helps freshmen hone problem-solving skills. All three programs target students who enter their majors with significant motivation and mathematics preparation, but nonetheless demonstrate low success in foundational STEM courses, particularly mathematics. The QTWG will: 1) build a quantitative tool kit (QToolkit) filled with effective learning activities mapped to particular mathematical skills, 2) identify and empirically validate pedagogical approaches that promote retention and motivation in the physical and quantitative sciences, and 3) develop strategies that equip STEM faculty to lead curricular reform. The QTWG project will generate a rich data set regarding the effectiveness of teaching mathematical skills through application. Investigators will catalog which math skills are most problematic for physical and quantitative science majors, map the learning of these skills across the three programs, and identify the effectiveness of learning strategies addressing these skills. This work will be grounded in the Concerns-Based Adoption Model (CBAM) theory-of-change and employ a "faculty work as learning" framework to build buy-in by individual faculty members. It holds the potential to identify activities that empower faculty members and students to become agents of curricular change while improving the mathematical skills of STEM undergraduates.
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Increasing STEM Graduates in the Physical and Quantitative Sciences
Preparing Economically Challenged Students for Careers in Biotechnology
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