Introducing Data Science Topics to Non-Computing Majors
Introducing Data Science Topics to Non-Computing Majors
复制标题
向非计算机专业介绍数据科学主题
DOI：
10.1145/3478432.3499156
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Raj, Rajendra K.
中科院分区：
文献类型：
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作者：
Liu, Xumin;Golen, Erik;Raj, Rajendra K.
数据科学知识和技能已经成为STEM和非STEM学科不可或缺的。因此，对于非计算专业的学生来说，学习数据科学技术变得至关重要，特别是在他们自己的学科背景下。然而，目前大多数大学数据科学课程都需要足够深入的编程和统计技能，这些技能与管理、操作和分析数据有关，这降低了它们对入门级非计算专业学生的有用性。本研讨会提供了一套实践练习，向入门级的非计算专业介绍数据科学。这些练习涵盖了数据科学的生命周期，包括数据采集、准备、模型开发和部署、可视化和讲故事。一个免费提供的基于Web的数据科学学习平台（DSLP）将展示如何在很少或没有编码背景的情况下进行实际操作的数据科学练习。演讲者还将分享他们在RIT的非计算专业的入门级数据科学课程中使用DSLP工具的经验。工具和课程材料都将与讲习班学员分享。典型的研讨会参与者是对入门级数据科学教学感兴趣的高中教师或大学讲师。不需要事先编程或数据科学经验，从而使研讨会材料可供广泛受众使用。参加者需要有一台可上网的笔记本电脑，才能参加动手练习讲习班。笔记本电脑应该有一个当前的网络浏览器（例如，Safari或Chrome）访问基于Web的学习平台。这项工作得到了国家科学基金会2021287奖的支持。
Data science knowledge and skills have become indispensable to STEM and non-STEM disciplines alike. As a result, it has become crucial for students in non-computing majors to learn data science techniques, particularly in the context of their own disciplines. A majority of current university data science coursework, however, requires sufficient depth in programming and statistical skills related to managing, manipulating, and analyzing data, which reduces their usefulness for entry-level non-computing majors. This workshop presents a set of hands-on exercises to introduce data science to entry-level non-computing majors. The exercises cover the data science lifecycle, including data acquisition, preparation, model development and deployment, visualization, and storytelling. A freely-available web-based Data Science Learning Platform (DSLP) will be presented to show how to perform hands-on data science exercises with little or no coding background. The presenters will also share their experiences in using the DSLP tool in an entry-level data science course to non-computing majors at RIT. Both the tool and course materials will be shared with workshop participants. The typical workshop participant is a high school teacher or a college instructor interested in teaching data science at the introductory level. No prior programming or data science experience is needed, thus making the workshop materials usable by a wide audience. Participants need to have a laptop with access to the Internet to attend the hands-on exercises workshop. The laptop should have a current web browser (e.g., Safari or Chrome) installed to access the web-based learning platform. This work was supported by the National Science Foundation under Award 2021287.