Undergraduate Service Learning Experiences with Data: Mathematics in the Community
Undergraduate Service Learning Experiences with Data: Mathematics in the Community
批准号:
2021512
负责人:
Michelle Friend
金额:
$30.0万
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
项目状态:
已结题
起止时间:
2020-10-01 至 2024-09-30
中文摘要
该项目旨在通过改变本科生在新的一年级普通教育(GEED)课程中接触和学习数学的方式来服务于国家利益。在本课程中,学生将分析并创建数据可视化,以回答非营利性社区合作伙伴提出的真实问题。通过培养在信息密集的社会中至关重要的数据素养和可视化技能,学生将满足量化素养的一般教育要求。研究人员预计,学生对数学和数据科学的信心和兴趣将会增加。与社区合作伙伴的有意义的互动将使学生能够更多地参与社区活动,并增强员工技能,例如:领导力、沟通和批判性思维技能。该课程还希望吸引对数学兴趣和自我效能感较低的学生,从而扩大对数据科学的参与。该项目旨在增加对服务学习作为环境的有效性和可行性的理解,以提高学生在Gened数学课程中的成绩。服务学习是一种参与式的教与学方法,强调批判性思维和通过将课程内容与现实世界的经验联系起来解决问题。通过探究式学习,该项目将吸引学生进行真实的探究,解决现实世界的问题,并通过定期反思记录学习。该项目将调查GEED课程在学生对数学和其他STEM学科的兴趣和参与度方面的教育影响。此外,还将考察学生在大学期间的留校率和未来的选课行为。通过让学生完成课程前的调查和相应的课程后的调查,使用有效的自我效能感、兴趣和STEM态度的测量,学科内设计将被用来衡量课程如何改变学生对STEM的态度。此外,研究团队将与其他GenED数学课程的教师合作,实施学科间设计,以比较课程。比较将着眼于绝对结果(例如,比较每门课程在学期结束时对未来STEM课程的兴趣),以及从学期开始到结束的变化(例如,数学自我效能感的增长)。该小组将采用混合方法方法,使用定量数据来衡量实现参与目标的进展情况,并使用定性数据来提供对研究问题的见解以及对整个项目的成功和挑战的见解。数据收集将包括半结构化访谈和焦点小组、项目文件、反思、课堂观察、调查和大学招生数据。项目成果和交付成果将通过公共网站和出版物与其他机构共享。NSF IUSE:EHR计划支持研究和开发项目,以提高所有学生的STEM教育的有效性。通过参与的学生学习路径,该计划支持有前景的实践和工具的创建、探索和实施。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
This project aims to serve the national interest by transforming how undergraduate students engage with and learn mathematics in a new first-year general education (GenEd) course. In this course students will analyze and create visualizations of data in order to answer authentic questions from non-profit community partners. By developing data literacy and visualization skills critical in an information-dense society, students will meet general education requirements in quantitative literacy. Researchers expect that students will increase in confidence and interest in mathematics and data science. Meaningful interactions with community partners will enable students to develop an increased commitment to community engagement and enhanced workforce skills, such as: leadership, communication, and critical thinking skills. The course is also expected to engage students who may have lower interest and self-efficacy in mathematics, thus broadening participation in data science.The project aims to increase understanding of the effectiveness and feasibility of service learning as a context to improve student outcomes in GenEd mathematics courses. Service learning is a method of engaged teaching and learning that emphasizes critical thinking and problem solving by connecting course content with real-world experiences. Through inquiry-based learning the project will engage students in authentic inquiry, solving real-world problems and documenting learning through regular reflection. The project will investigate the educational impact of the GenEd course in terms of students’ interest and engagement in mathematics and other STEM disciplines. Retention in the university and future course-taking behavior will also be examined. A within-subject design will be used to measure how the course changes student attitudes towards STEM by having students complete a pre-course survey and a corresponding post-course survey using validated measures of self-efficacy, interest, and STEM attitudes. In addition, the research team will work with instructors of other GenEd mathematics courses to implement a between-subject design to compare courses. Comparisons will look both at absolute outcomes (e.g. comparing interest in future STEM-course taking at the end of the semester between each course) and also at changes from the beginning to the end of the semester (e.g. gains in mathematical self-efficacy). The team will apply a mixed-methods approach that uses quantitative data to measure progress towards participation targets and qualitative data that provides insights into the research questions as well as insights into the successes and challenges of the overall project. Data collection will consist of semi-structured interviews and focus groups, project documents, reflections, classroom observations, surveys, and university enrollment data. Project results and deliverables will be shared with other institutions through a public website as well as publications. 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.
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