Mentoring a Diverse Cohort of Postdoctoral Scholars in Data Science Education Research

指导数据科学教育研究领域的多元化博士后学者

• 批准号: 2222148
• 负责人: Rachel Levy
• 金额: $ 124.94万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2222148&HistoricalAwards=false
• 关键词: Mentoring; Diverse; Cohort; Postdoctoral; Scholars

Data science is rapidly growing, as a profession, a professional skill and a component of literacy for the general public. With data science research careers moving beyond the university setting and into other sectors, it is imperative to learn what kind of learning environment will support the postdoctoral training and development of diverse, skilled data scientists, educators, and data science education researchers who can help build and communicate with a data-literate public. The ability to consume, question, produce, and use data is critical not only to answer research questions in areas such as health, science, business, and government but also to inform decision-making in many aspects of work and personal life. Through this project, the North Carolina State University Data Science Academy will identify the key success components of a model for the recruitment and mentoring of a diverse cohort of postdoctoral fellows who will enter their professions with expertise in data science education research. This model is intended to train and support scholars who have differing levels of experience and strengths in STEM, STEM education, education research, or data science.While data science and literacy can be embedded across disciplines, they are central to STEM Education. How data-related skills will be infused in courses across the curriculum and taught in stand-alone data science learning environments is an open and evolving area of education research and practice. The cohort of postdoctoral scholars will study the North Carolina State University Data Science Academy's course design model: All-campus Data science through Accessible Project-based Teaching and learning (ADAPT). Fellows will work as part of a diverse education research team to develop, implement, scale and share a long-term, robust research program that assesses the efficacy of the ADAPT model and related courses. The research will add capacity to STEM education research by presenting a model that has been validated through ongoing assessment and continuous improvement and has the potential to be adapted to other institutions and STEM fields. By matching postdoctoral fellows with a diverse team of mentors with varied data science education research interests, the project also aims to build reciprocal relationships between mentees and mentors who learn from each other and their experiences. Postdoctoral scholars will have opportunities to engage with a network of data science and education leaders in industry, government, education, consulting and agriculture.The Discovery Research preK-12 program (DRK-12) seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics (STEM) by preK-12 students and teachers, through research and development of innovative resources, models and tools. Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects.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.

数据科学作为一种职业、一种专业技能和公众素养的组成部分正在迅速发展。随着数据科学研究职业超越大学环境并进入其他领域，必须了解什么样的学习环境将支持博士后培训和发展多样化，熟练的数据科学家，教育工作者和数据科学教育研究人员，他们可以帮助建立并与数据沟通。消费、质疑、生产和使用数据的能力不仅对于回答健康、科学、商业和政府等领域的研究问题至关重要，而且对于为工作和个人生活的许多方面的决策提供信息也至关重要。通过这个项目，北卡罗来纳州州立大学数据科学学院将确定一个模型的关键成功要素，用于招聘和指导一批具有数据科学教育研究专业知识的博士后研究员。该模式旨在培养和支持在STEM、STEM教育、教育研究或数据科学方面具有不同经验和优势的学者。虽然数据科学和素养可以跨学科嵌入，但它们是STEM教育的核心。如何将数据相关技能融入整个课程，并在独立的数据科学学习环境中教授，是教育研究和实践的一个开放和不断发展的领域。博士后学者的队列将研究北卡罗来纳州州立大学数据科学学院的课程设计模型：通过可扩展的基于项目的教学和学习（ADAPT）的所有校园数据科学。研究员将作为一个多元化的教育研究团队的一部分，开发，实施，规模和分享一个长期的，强大的研究计划，评估ADAPT模型和相关课程的有效性。该研究将通过提出一个模型来增加STEM教育研究的能力，该模型已通过持续评估和持续改进得到验证，并有可能适用于其他机构和STEM领域。通过将博士后研究员与具有不同数据科学教育研究兴趣的多元化导师团队相匹配，该项目还旨在建立学员和导师之间的互惠关系，他们相互学习并学习他们的经验。博士后学者将有机会与工业，政府，教育，咨询和农业的数据科学和教育领导者网络进行接触。发现研究preK-12计划（DRK-12）旨在通过研究和开发创新资源，模型和工具。DRK-12项目中的项目建立在STEM教育的基础研究以及为拟议项目提供理论和经验依据的先前研究和开发工作的基础上。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。