IGE: Leveraging Data Science Master Programs to Enhance Professional Readiness in STEM PhD Students

IGE：利用数据科学硕士课程增强 STEM 博士生的专业准备

• 批准号: 1806593
• 负责人: Jana Schaich Borg
• 金额: $ 47.84万
• 依托单位: Duke University
• 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: 2018-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1806593&HistoricalAwards=false
• 关键词: IGE; Leveraging; Data; Science; Master

Traditional STEM graduate education is primarily dedicated to training students on how to succeed in academic jobs, despite the fact that most STEM PhD students leave academia after graduation. This traditional approach to graduate education leaves PhD students unprepared to enter the non-academic workforce upon graduation. A lack of adequate preparation not only adversely affects the students themselves, but also leads to missed opportunities for society, since STEM PhD students often have precisely the deep technical background needed to solve the growing number of data-driven problems society faces. This National Science Foundation Innovations in Graduate Education (IGE) award to Duke University will test whether Master-level data science programs, which usually have curricula that emphasize the professional skills and applied data skills missing from most PhD programs, can be leveraged to improve the preparation of PhD students. This project will test the outcomes of combining the applied approach of Master-level data science programs with the depth and experience of PhD STEM students. More specifically, it will determine which aspects of Master-level professional curricula translate to PhD students. The results will provide guidance on approaches to extend the impact of a growing investment in data science Master programs to doctoral-level students and will inform the education community on better preparing the next generation of STEM scientists to work with and improve methods surrounding big data. In so doing, this project will help strengthen the pipeline between universities and non-academic employers. This project will incorporate a select cohort of Duke's STEM PhD students into Duke's Master in Interdisciplinary Data Science (MIDS) Capstone projects with non-academic partners, and include the selected PhD students in the professional development activities of the MIDS program. Duke's MIDS program emphasizes comprehensive training in professional and communication skills in its coursework. The program culminates in a capstone project that requires students to solve a data-driven problem for a partner outside of the university. Students must apply the technical skills, theoretical knowledge, and professional skills they learned in the classroom to a real-life situation that requires interacting with a diversity of both technical and non-technical collaborators. The goal of this research is to determine which of these enhanced experiences can mitigate - and ultimately, overcome - the shortage of doctoral graduates with industry-relevant training, developed professional competencies, and deep domain knowledge. The principles guiding this IGE project stem from research on the use of vertically-integrated, topically-focused research teams as mechanisms to motivate effective, meaningful learning. The MIDS Capstone curriculum is based on evidence-backed practices from the team-based learning and service learning literature. The effectiveness of the project for STEM PhD students will be evaluated using survey, interview, and structured assessment data collected from students, faculty, and Capstone partners, as well as data from potential future employers and students' supervisors after they move to new positions. Outcomes measured will include students' professional skills, students' data science competencies, students' research accomplishments, and reported benefits to non-academic partners. The results will be used to develop scalable mechanisms for universities to extend the impact of their investment in data science Master programs to doctoral-level students. Doing so will strengthen the potential for PhD students to deploy their expertise to solve society's most pressing problems both inside and outside of academia and will provide richer opportunities for organizations to find data scientists with the specialized knowledge needed to solve problems within their area. The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community.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.

传统的STEM研究生教育主要致力于培训学生如何在学术工作中取得成功，尽管大多数STEM博士生在毕业后离开学术界。这种传统的研究生教育方法使博士生在毕业后没有准备好进入非学术劳动力市场。缺乏充分的准备不仅会对学生本身产生不利影响，还会导致社会失去机会，因为STEM博士生往往恰恰拥有解决社会面临的越来越多的数据驱动问题所需的深厚技术背景。授予杜克大学的美国国家科学基金会研究生教育创新奖（IGE）将测试硕士级数据科学课程是否可以用来提高博士生的准备水平，这些课程通常强调大多数博士课程所缺少的专业技能和应用数据技能。该项目将测试将硕士级数据科学课程的应用方法与STEM博士生的深度和经验相结合的结果。更具体地说，它将确定硕士水平的专业课程的哪些方面转化为博士生。研究结果将为如何将对数据科学硕士项目日益增长的投资的影响扩展到博士生提供指导，并将为教育界提供信息，帮助他们更好地准备下一代STEM科学家，以使用和改进围绕大数据的方法。通过这样做，该项目将有助于加强大学和非学术雇主之间的渠道。该项目将把杜克的STEM博士生的一个选择队列纳入杜克的跨学科数据科学硕士（MIDS）与非学术合作伙伴的顶点项目，并包括在MIDS计划的专业发展活动选定的博士生。杜克大学的MIDS课程强调在其课程中进行专业和沟通技能的全面培训。该计划的高潮是一个顶点项目，要求学生为大学以外的合作伙伴解决数据驱动的问题。学生必须将他们在课堂上学到的技术技能，理论知识和专业技能应用到现实生活中，需要与技术和非技术合作者的多样性进行互动。这项研究的目标是确定这些增强的经验可以减轻-并最终克服-博士毕业生与行业相关的培训，开发的专业能力和深厚的领域知识的短缺。指导IGE项目的原则来自于对使用纵向一体化、以主题为重点的研究团队作为激励有效、有意义学习的机制的研究。MIDS Capstone课程是基于团队学习和服务学习文献的证据支持的实践。STEM博士生项目的有效性将使用从学生，教师和Capstone合作伙伴收集的调查，访谈和结构化评估数据进行评估，以及从潜在的未来雇主和学生主管转移到新职位后的数据。衡量的结果将包括学生的专业技能，学生的数据科学能力，学生的研究成果，以及报告的非学术合作伙伴的利益。研究结果将用于为大学开发可扩展的机制，以将其对数据科学硕士课程的投资影响扩展到博士生。这样做将加强博士生利用他们的专业知识解决学术界内外最紧迫的社会问题的潜力，并为组织提供更丰富的机会，找到具有解决其领域内问题所需专业知识的数据科学家。研究生教育创新（IGE）计划的重点是研究生教育的研究。IGE的目标是试验、测试和验证研究生教育的创新方法，并产生将这些方法推广到更广泛的社区所需的知识。该奖项反映了NSF的法定使命，并被认为值得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来支持。