Short Course in Data Science for Environmental Public Health

环境公共卫生数据科学短期课程

• 批准号: 10746327
• 负责人: Ava Marie Hoffman
• 金额: $ 19.95万
• 依托单位: FRED HUTCHINSON CANCER CENTER
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-25 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10746327
• 关键词: Address; Applied Skills; Awareness; Big Data; Cancer Center; Code; Collaborations; Communities; Community Health; Companions; Continuing Education; Data; Data Analyses; Data Science; Data Set; Democracy; Development; Discipline; Disparity; Documentation; E-learning; Education; Education Gap; Educational Materials; Educational process of instructing; Environmental Health; Environmental Science; Ethics; Event; Faculty; Feedback; Foundations; Goals; Growth; Hispanic-serving Institution; Historically Black Colleges and Universities; Home; Individual; Institution; Instruction; Lead; Learning; Minority-Serving Institution; Modeling; Participant; Persons; Public Health; Publishing; Reproducibility; Research; Research Personnel; Resources; Science; Scientist; Services; Teacher Professional Development; Technology; Time; Training; Travel; Work; community building; community college; data science education; empowerment; experience; flexibility; health data; health disparity; health equity; improved; instructor; learning materials; lectures; massive open online courses; multimodality; online community; online course; participant retention; peer; peer support; programs; recruit; skills; success; supportive environment; tool; tribal college

Project Summary/Abstract Nearly all science fields have been drastically changed by the big data era, and datasets have the potential to create major breakthroughs in environmental health. However, professional development in data science lags behind for environmental health researchers and practitioners. What training does exist primarily benefits privileged institutions. We propose the Short Course in Data Science for Environmental Public Health to bridge this education gap. Through the Fred Hutchinson Cancer Center Data Science Lab, we will leverage our combined 25-plus year track record of developing educational materials, scalable courses, scalable research experiences, and building communities around data science education to create this multi-modal course. The program, which will empower 30 learners annually, begins with a two-week online course that solidifies R programming foundations. These two weeks will use a combination of didactic lectures on best practices and active hands-on lab activities to practice and engrain programming skills, a model for which the lead instructors have earned recognition for excellence in teaching and successfully used to train over 100 professional learners. Participants will practice new skills one topic at a time to make the content more manageable. This foundation will prepare participants for participating in a three-day in-person intensive “Code-a-thon” where they work on authentic environmental health projects. The Code-a-thon will allow participants to practice data ethics skills in peer code review, reproducibility, and transparency in a supportive environment. Additionally, to ensure that we are responsive to the needs of the diverse participants, we will allow learners a mechanism to provide anonymous feedback throughout and beyond the program. To create scalability, we will adapt a companion Massive Open Online Course (MOOC) so that potentially thousands of participants can benefit. We will also harness the strengths of in-person instruction by creating a yearly training for instructors hoping to reproduce this course in their own institution or community. These efforts will be bolstered by an online data community where participants can support, troubleshoot, and collaborate with peers, as well as monthly reminder newsleęers to help participants retain what they learn. We will work with our existing network of faculty from under-resourced institutions to recruit researchers and faculty specifically from Historically Black Colleges and Universities, Hispanic Serving Institutions, Tribal Colleges and Universities, and Community Colleges to participate in the live course. The course will be offered for free and half of the participants will receive travel stipends to help break down barriers to participation. Throughout, learners will work with relevant health equity datasets with the ultimate goal of understanding and addressing disparities in environmental health equity.

项目概要/摘要 大数据时代几乎所有科学领域都发生了巨大变化，数据集有潜力 在环境健康方面取得重大突破 然而，数据科学的专业发展滞后。 对于环境健康研究人员和从业人员来说，培训确实存在主要好处。 我们向有特权的机构推荐环境公共卫生数据科学短期课程。 通过弗雷德·哈钦森癌症中心数据科学实验室，我们将弥补这一教育差距。 25 多年开发教育材料、可扩展课程、可扩展研究的记录 经验，并围绕数据科学教育建立社区来创建这门多模式课程。 该计划每年将为 30 名学习者提供帮助，从为期两周的在线课程开始，该课程巩固了 R 这两周将结合最佳实践和编程基础的教学讲座。 积极的实验室实践活动，以练习和巩固编程技能，这是领导者的一个模型 讲师因卓越的教学而获得认可，并成功培训了 100 多名 专业学习者将一次一个主题地练习新技能，以使内容更加丰富。 该基金会将为参与者参加为期三天的面对面强化课程做好准备。 他们致力于真正的环境健康项目的“编程马拉松”将允许。 参与者在支持性的环境中练习同行代码审查、可重复性和透明度方面的数据道德技能 此外，为了确保我们能够满足不同参与者的需求，我们将 允许学习者在整个计划中和计划之外提供匿名反馈的机制。 可扩展性，我们将调整配套的大规模开放在线课程（MOOC），以便潜在的数千人 我们还将通过创建年度课程来利用现场指导的优势。 为希望在自己的机构或社区重现本课程的教师提供培训。 将得到在线数据社区的支持，可以在其中提供支持、故障排除和协作 与同行一起，以及每月提醒时事通讯，以帮助参与者记住他们将要学习的内容。 利用我们现有的来自资源不足机构的教师网络来招募研究人员和教师 特别是来自历史悠久的黑人学院和大学、西班牙裔服务机构、部落学院 大学和社区学院免费参加直播课程。 一半的参与者将获得旅行津贴，以帮助打破参与障碍。 在整个过程中，学习者将使用相关的健康公平数据集，最终目标是理解 并解决环境健康公平方面的差异。