IUSE Collaborative Research: Data Computing for All: Developing an Introductory Data Science Course in Flipped Format

这个名为《全民数据计算：以翻转格式编写数据科学入门课程》的项目解决了两个当前问题：需要更多的学生熟悉数据在各种环境中的使用，以及需要教学材料来支持“翻转课堂”形式的课程作业。翻转的教室颠倒了学生们花费时间的方式。学生不是在课堂上把信息传授给他们，然后通过家庭作业问题自己练习使用新知识，而是在上课前获取信息，然后在课程教师在场的情况下练习使用它，以帮助消除误解和复杂性。这使教师能够解决小组学生遇到的问题，而不是在不知道谁听懂的情况下向一大组学生讲课。数据科学对于从基因组测序到客户数据分析等各种应用都是必不可少的。几乎每个学科都需要大规模的数据处理，需要将计算和统计结合起来。更具体地说，这门课程不仅涉及计算机和统计科学，而且涉及所有科学、商业、医学和工程领域的重要需求。对有效利用海量数据和新兴数据科学领域的依赖正在改变跨部门组织的运作。该项目不仅将在STEM学科的一个重要领域提供新的课程，而且将产生有价值的教育研究。随着翻转课堂学习模式的广泛使用，人们对其普适性提出了质疑。它总是正确的方法吗？用这种方式准备一门课程的教材有多难？这个项目将在为背景最少的学生开设的一门新的数据科学课程的背景下解决这些问题。该项目是在两个不同类型的机构的计算机科学和统计部门开发的。这两家机构都有使用翻转方法的经验，而且共同拥有数据科学方面的专业知识。课程材料以及评估结果将使其他机构能够更好地考虑将数据科学计算入门纳入其方案。

This project, Data Computing for All: Developing an Introductory Data Science Course in Flipped Format, addresses two current issues: the need for more students to be familiar with the use of data in a variety of contexts and the need for instructional materials to support coursework in the "flipped classroom" format. The flipped classroom reverses the way time is spent by students. Instead of having information given to them in the classroom and then going away to practice using the new knowledge by themselves through homework problems, the students get the information before class time and then practice using it while the course instructor is present to help with misunderstandings and complexities. This allows the instructor to address the problems encountered by small groups of students, rather than lecturing to a large group without knowing who understands what. Data science is essential for applications as diverse as genome sequencing and customer data analysis. Nearly every discipline has need of large scale data handling that requires computing and statistics in combination. More specifically, this course addresses an important need not only in computer and statistical sciences, but in all science, business, medical and engineering areas in general. The reliance on the effective use of vast amounts of data and the emergent field of data science is changing the operation of organizations across sectors. This project will not only provide new course in an important area in the STEM disciplines, but will also result in valuable educational research.With the growing use of the flipped classroom model of learning, questions arise about its generalizability. Is it always the right approach? How difficult is it to prepare materials to teach a course in this way? This project will address these questions in the context of a new data science course for students with minimal background. The project is being developed in computer science and statistics departments at two different types of institutions. Both institutions have experience using the flipped approach and together have the expertise for data science. The course materials as well as the evaluation results will better enable other institutions to consider including introductory data science computing in their programs.