Identifying Assets and Collaborative Activities to Support Student Success in Environmental Data Science at Minority Serving Institutions

确定资产和合作活动，以支持少数族裔服务机构的学生在环境数据科学方面取得成功

• 批准号: 2135830
• 负责人: Micaela Parker
• 金额: $ 9.99万
• 依托单位: Ronin Institute for Independent Scholarship Incorporated
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2023-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2135830&HistoricalAwards=false
• 关键词: Identifying; Assets; Collaborative; Activities; Support

This project aims to serve the national interest by increasing capacity in environmental data science through improved access to training and workforce development resources for diverse student populations. Racial and ethnic minority groups in the United States are under-supported and under-represented in data science programs and careers. Multiple challenges, including the affordability, access to new technologies and the lack of educational opportunities for diverse students, have led to a digital divide that demonstrates inequities in access to data, technology and educational opportunities. Data science education at Minority Serving Institutions (MSIs) can narrow this divide by engaging diverse student and faculty populations who have the knowledge and skills required to address issues of social and cultural relevance. MSIs have proven to be effective at recruiting, retaining, and preparing under-represented students for the STEM workforce. This project seeks to bring together representatives from Historically Black Colleges and Universities (HBCUs), Tribal Colleges and Universities (TCUs), and professional organizations to build resource networks, identify barriers to data science education, and co-create a set of recommendations focusing specifically on environmental sciences, thus empowering and supporting equitable data science education and training opportunities that ameliorate the digital divide.The focus on environmental data science springs from two factors that indicate strong workforce needs nationwide: a significant increase in large ecological datasets and environmental synthesis projects over the last decade and the growing national awareness of critical environmental challenges. The project team includes representatives from the Academic Data Science Alliance, Native BioData Consortium, Atlanta University Center Data Science Initiative, the SCORE-UBE Network, The Carpentries and the National Environmental Observation Network and the project will engage a broad collection of additional academic and community partners. This project will organize monthly HBCU and TCU working group meetings and a series of mini-workshops to meet the following goals: 1) identify the unique assets that HBCUs and TCUs bring to environmental data science education; 2) analyze barriers to adoption of data science in teaching relevant courses; 3) identify and raise awareness of resources available to support equitable data science education; 4) promote relationship-building among faculty and partner organizations, forming the basis of a network for future resource sharing and curriculum development with peer support; and, 5) collaboratively develop a living document with recommendations that will enhance student success in environmental data science. Project activities will allow participants, with support from a Leadership Committee and community partners, to identify institutional assets and challenges, and how to best leverage partnerships to enhance data science capacity at HBCUs and TCUs. The project will build relationships and concentrate activities on identifying shared solutions that can be adopted within a variety of contexts and scales. Information gathered during all workshops and the project evaluation will be incorporated in a living document with recommendations that will be disseminated to all network partners and to the wider data science community. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all 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.

该项目旨在通过改善不同学生群体获得培训和劳动力发展资源的机会，提高环境数据科学的能力，从而为国家利益服务。美国的少数种族和族裔群体在数据科学项目和职业中的支持和代表性不足。多种挑战，包括负担能力、获得新技术的机会以及不同学生缺乏教育机会，导致了数字鸿沟，显示了在获得数据、技术和教育机会方面的不平等。少数民族服务机构（MSIs）的数据科学教育可以通过吸引具有解决社会和文化相关性问题所需知识和技能的多样化学生和教师群体来缩小这一鸿沟。MSIs已被证明在招聘，保留和准备代表性不足的学生为STEM劳动力方面是有效的。该项目旨在汇集来自历史黑人学院和大学（HBCU），部落学院和大学（TCU）以及专业组织的代表，以建立资源网络，确定数据科学教育的障碍，并共同创建一套专门针对环境科学的建议。从而赋予和支持公平的数据科学教育和培训机会，改善数字鸿沟。对环境数据科学的关注源于两个因素，表明全国范围内对劳动力的需求很大：过去十年来，大型生态数据集和环境综合项目显著增加，国家对重大环境挑战的认识不断提高。 该项目团队包括学术数据科学联盟，原生生物数据联盟，亚特兰大大学中心数据科学计划，SCORE-UBE网络，Carpentries和国家环境观测网络的代表，该项目将吸引更多的学术和社区合作伙伴。该项目将组织每月一次的HBCU和TCU工作组会议以及一系列小型研讨会，以实现以下目标：1）确定HBCU和TCU为环境数据科学教育带来的独特资产; 2）分析在相关课程教学中采用数据科学的障碍; 3）确定并提高对可用于支持公平数据科学教育的资源的认识; 4）促进教师和合作伙伴组织之间的关系建设，形成网络的基础，为未来的资源共享和课程开发与同行的支持;和，5）合作开发一个活的文件与建议，将提高学生在环境数据科学的成功。项目活动将使参与者在领导委员会和社区合作伙伴的支持下，确定机构资产和挑战，以及如何最好地利用伙伴关系来提高HBCU和TCU的数据科学能力。该项目将建立关系，并将活动集中在确定可在各种背景和规模下采用的共同解决方案上。在所有研讨会和项目评估期间收集的信息将被纳入一份动态文件，并附有建议，分发给所有网络合作伙伴和更广泛的数据科学界。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。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。