论文标题
在介绍性数据科学课程中教授视觉可访问性，该课程具有多模式数据表示
Teaching Visual Accessibility in Introductory Data Science Classes with Multi-Modal Data Representations
论文作者
论文摘要
尽管有多种表示数据模式和模型的方法，但可视化主要是在许多数据科学课程中以其效率进行的。这种依赖视力的产出可能会对那些盲人和视力障碍和学习障碍者的关键障碍。我们认为，讲师需要教多种数据表示方法，以便所有学生都可以生产更容易访问的数据产品。在本文中，我们认为应在入门课程中教授可访问性作为数据科学课程的一部分，以便无论数据科学是否专业，他们都可以基本的可访问性。作为我们在两个不同机构的下级课程的一部分教授可访问性的数据科学教育者，我们分享了其他数据科学讲师可以使用的特定示例。
Although there are various ways to represent data patterns and models, visualization has been primarily taught in many data science courses for its efficiency. Such vision-dependent output may cause critical barriers against those who are blind and visually impaired and people with learning disabilities. We argue that instructors need to teach multiple data representation methods so that all students can produce data products that are more accessible. In this paper, we argue that accessibility should be taught as early as the introductory course as part of the data science curriculum so that regardless of whether learners major in data science or not, they can have foundational exposure to accessibility. As data science educators who teach accessibility as part of our lower-division courses in two different institutions, we share specific examples that can be utilized by other data science instructors.
