Graduate Statistics Curriculum at a Crossroads

处于十字路口的研究生统计课程

基本信息

批准号：
1844975
负责人：
Deborah Nolan
金额：
$ 6.84万
依托单位：
University of California-Berkeley
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-08-15 至 2020-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1844975&HistoricalAwards=false
关键词：
Graduate Statistics Curriculum Crossroads

项目摘要

Funding from this award will support the workshop "Graduate Statistics Education at a Crossroads", to be held November 2-3, 2018 in Alexandria, VA. The workshop will identify challenges and barriers that limit graduate statisticians from fully participating in the new era of big data. To address these challenges and barriers, workshop attendees will craft realizable recommendations for academic departments and institutions. It is expected that these recommendations will promote model curricula, pedagogical approaches, and innovative approaches that have the potential to foster broader engagement with data science and to promote success of future statisticians in data science research and the workforce more broadly. The workshop aligns with the training aspects of Harnessing the Data Revolution, one of ten big ideas for future NSF investment. More specifically, the workshop aims to identify an array of data-science related training activities that would support the statistics community in order that statisticians fully participate in cutting-edge interdisciplinary data science research. Additional details may be found at https://hub.ki/groups/statisticsgraduateeducation/overviewThis 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.

该奖项的资金将支持将于2018年11月2日至3日在弗吉尼亚州亚历山大市举行的“十字路口的研究生统计教育”。研讨会将确定限制研究生统计学家的挑战和障碍，无法完全参与大数据的新时代。为了应对这些挑战和障碍，研讨会的与会者将为学术部门和机构提出可实现的建议。预计这些建议将促进模型课程，教学方法和创新方法，这些方法有可能促进与数据科学的更广泛参与，并在数据科学研究和劳动力中促进未来统计学家的成功。该研讨会与利用数据革命的培训方面保持一致，这是未来NSF投资的十大思想之一。更具体地说，该研讨会旨在确定一系列与数据科学相关的培训活动，这些活动将支持统计社区，以便统计学家充分参与尖端的跨学科数据科学研究。可以在https://hub.ki/groups/statisticsgraduateeducation/overviewthis Award上找到其他详细信息，这反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响来通过评估来支持的。