Data Path: Creating a New STEM Pathway for Undergraduates from Statistics Into Data Science

数据路径：为本科生从统计学到数据科学创建一条新的 STEM 路径

• 批准号: 2021488
• 负责人: Denise Hum
• 金额: $ 30万
• 依托单位: San Mateo County Community College District
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2021488&HistoricalAwards=false
• 关键词: Data; Path; Creating; New; STEM

This project aims to serve the national interest by increasing the number and diversity of STEM students. To do so, it will establish a new path into STEM majors and careers through statistics and data science for students at a Hispanic-serving two-year college. This new path is expected to improve STEM learning and teaching and increase the diversity of students pursuing STEM. The first step in the pathway will be a redesigned Introduction to Statistics course that incorporates project-based learning. This change is expected to engage more students and spark their interest in pursuing a STEM pathway. The next step in the pathway will be a new introduction to Data Science course, which will meet a transfer math requirement The Data Science course is expected to serve as an onramp into STEM for students who do not necessarily see themselves in a STEM career. The project will actively recruit students from the new statistics course into the new Data Science course, thus transforming the statistics course into a STEM talent pipeline instead of a terminal math course. Additional students will be recruited into the Data Science course via a new Data Scholars Program, which will provide a supportive STEM community for students who may not be initially interested in STEM majors. Finally, the project will provide professional development to mathematics faculty on implementing project-based curriculum pedagogy. A quasi-experimental design will be used to measure the overall effectiveness of project-based learning in the introductory statistics course. Students in the new project-based learning statistics course will be compared with students in statistics courses using traditional pedagogy. Analysis of variance will be used to examine differences between the two types of courses on measures of student experience, student attendance, course success, degree completion, and transfer rate to four-year universities. Furthermore, qualitative methods, such as focus groups and open-ended survey questions, will be used to evaluate the fidelity of implementing the project-based learning model. This project project may serve as a model for other community colleges looking to build a data science program and a new pathway into STEM. Lessons learned and insights gained into how changing pedagogy impacts student interest and success in STEM will be shared through conference presentations and publications. Anticipated outcomes during the project period include increased student success rates in the project-based statistics course, increased enrollment in the data science course, and increased participation in the Data Scholars program. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.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.

该项目旨在通过增加STEM学生的数量和多样性来服务于国家利益。 为此，它将通过统计和数据科学为西班牙裔两年制大学的学生建立一条进入STEM专业和职业的新途径。这条新的道路有望改善STEM的学习和教学，并增加追求STEM的学生的多样性。该途径的第一步将是重新设计的统计学入门课程，其中包括基于项目的学习。 这一变化预计将吸引更多的学生，并激发他们追求STEM途径的兴趣。 该途径的下一步将是对数据科学课程的新介绍，这将满足转移数学要求数据科学课程预计将成为那些不一定认为自己从事STEM职业的学生进入STEM的入口。 该项目将积极招收新统计课程的学生进入新的数据科学课程，从而将统计课程转变为STEM人才管道，而不是终端数学课程。 更多的学生将通过新的数据学者计划被招募到数据科学课程中，该计划将为最初可能对STEM专业不感兴趣的学生提供支持性的STEM社区。 最后，本计画将提供数学教师在实施专案式课程教学法方面的专业发展。一个准实验设计将被用来衡量项目为基础的学习在介绍统计课程的整体效果。学生在新的项目为基础的学习统计课程将进行比较，学生在统计课程使用传统的教学法。方差分析将被用来检查两种类型的课程之间的差异，对学生的经验，学生出勤率，课程的成功，学位完成，并转移率四年制大学的措施。此外，本研究亦会采用焦点小组及开放式问卷等质性方法，以评估专题为本学习模式的实施效果。这个项目可以作为其他社区学院的榜样，希望建立一个数据科学计划和一个进入STEM的新途径。吸取的经验教训和见解如何改变教学法影响学生的兴趣和成功干将通过会议演讲和出版物共享。项目期间的预期成果包括提高基于项目的统计课程的学生成功率，增加数据科学课程的入学人数，以及增加数据学者计划的参与。 NSF IUSE：EHR计划支持研究和开发项目，以提高所有学生STEM教育的有效性。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。