Computers in Science and Math Undergraduate Education

计算机在科学和数学本科教育中的应用

• 批准号: 1834159
• 负责人: Joyce Stamm
• 金额: $ 99.99万
• 依托单位: University of Evansville
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-03-01 至 2025-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1834159&HistoricalAwards=false
• 关键词: Computers; Science; Math; Undergraduate; Education

The ability to extract knowledge and insights from large datasets is increasingly important in science and the workforce. This project intends to address this need by educating scientists and mathematicians with computational skills needed to use large datasets to solve complex problems. Over five years, this project will provide four-year scholarships to fifteen low-income, high-achieving STEM undergraduate students with demonstrated financial need. The selected Scholars will be majors in biochemistry, biology, chemistry, environmental science, mathematics, physics, or statistics and data science. The project will develop four new courses to help students develop strong computational thinking and data visualization skills. Three new courses will introduce students early in their college career to interesting scientific problems that require analysis of complex data. A fourth new course will pair local businesses or non-profit clients with teams of third-year students and their faculty mentors. The teams will work to solve a client problem that requires computational approaches. Although only some students will receive scholarships, all math and science majors will have access to the new courses and support activities, including a career colloquium, undergraduate research, and a new Math and Science Problem Solving Lab. This access broadens the potential impact of this work to all STEM undergraduates at the University of Evansville. The project's research goal is to assess the impact of an interdisciplinary, computation-focused learning community on low-income students. Data will be collected from formative and summative assessments of Scholars' academic performance, retention in STEM, and progression to STEM careers. This assessment will use an embedded, mixed-methods study design to understand participant views throughout their college years. The summative data from Scholars will be compared to that of non-participating STEM majors. This analysis will contribute to understanding how participation in a combination of activities including career events, undergraduate research, and computational problem-solving affect students' career goals and self-efficacy. This project is funded by NSF's Scholarships in Science, Technology, Engineering, and Mathematics program, which seeks to increase the number of low-income, academically high-achieving students with demonstrated financial need who earn degrees in STEM fields. It also aims to improve the education of future scientists, engineers, and technicians, and to generate knowledge about academic success, retention, transfer, graduation, and academic/career pathways of low-income students.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

从大型数据集中提取知识和见解的能力在科学和劳动力中越来越重要。 该项目旨在通过教育科学家和数学家使用大型数据集来解决复杂问题所需的计算技能来满足这一需求。 在五年的时间里，该项目将提供四年奖学金，达到15个低收入，高成就的STEM本科生，具有经济需求。 选定的学者将是生物化学，生物学，化学，环境科学，数学，物理学或统计和数据科学的专业。 该项目将开发四个新课程，以帮助学生发展强大的计算思维和数据可视化技能。三个新课程将在大学职业生涯的早期介绍学生的有趣科学问题，需要对复杂数据进行分析。 第四个新课程将将当地企业或非营利性客户与三年级学生及其教师导师组成。 团队将努力解决需要计算方法的客户问题。尽管只有一些学生将获得奖学金，但所有数学和科学专业的专业都将可以访问新课程和支持活动，包括职业座谈会，本科研究以及新的数学和科学解决问题实验室。 这项工作扩大了这项工作对埃文斯维尔大学所有STEM大学生的潜在影响。该项目的研究目标是评估以计算为中心的学习界对低收入学生的影响。 数据将从对学者的学习成绩，在STEM中的保留以及向STEM职业发展的形成性和总结性评估收集。 该评估将使用嵌入式的混合方法研究设计，以了解他们在大学期间的观点。 来自学者的总结数据将与非参与型茎专业的数据进行比较。 该分析将有助于了解参与包括职业活动，本科研究以及计算问题解决的活动的组合影响学生的职业目标和自我效能。 该项目由NSF在科学，技术，工程和数学计划方面的奖学金提供资金，该计划旨在增加具有在STEM领域获得学位的经济需求的低收入，学术上高成就的学生的数量。它还旨在改善未来科学家，工程师和技术人员的教育，并为低收入学生的学术成功，保留，转移，毕业以及学术/职业途径提供知识。该奖项反映了NSF的法定任务，并认为通过使用该基金会的知识分子和更广泛的影响来评估CRITERIA的评估。