统计与数据科学课程无障碍和包容性教学材料框架
Framework for Accessible and Inclusive Teaching Materials for Statistics and Data Science Courses
AI总结：
本文提出一个可访问性和包容性框架，用于编写统计教科书，并分享目标设定、工具使用及教学建议，以促进数据科学教育中的公平与包容。
摘要：
尽管数据科学劳动力快速增长，有色人种、女性、残障人士及其他群体在该领域中的代表性仍然不足，服务不到位，有时甚至被排斥在外。这一模式阻碍了个人获得平等机会，同时也催生了延续不平等的产品和政策。因此，对于培养下一代统计与数据科学教育者而言，可访问性和包容性应成为我们项目和课程中的重中之重。在本文中，我们讨论了如何开发一个可访问性和包容性框架，即一种让我们对这些原则负责的结构，用于编写统计学教科书。我们分享了在设定可访问性和包容性目标方面的经验、实现这些目标所使用的工具，以及给其他教育工作者的建议。我们提供了教师可在自己课程中实施的示例。
英文摘要：
Despite rapid growth in the data science workforce, people of color, women, those with disabilities, and others remain underrepresented in, underserved by, and sometimes excluded from the field. This pattern prevents equal opportunity for individuals, while also creating products and policies that perpetuate inequality. Thus, for statistics and data science educators of the next generation, accessibility and inclusion should be of utmost importance in our programs and courses. In this paper, we discuss how we developed an accessibility and inclusion framework, hence a structure for holding ourselves accountable to these principles, for the writing of a statistics textbook. We share our experiences in setting accessibility and inclusion goals, the tools we used to achieve these goals, and recommendations for other educators. We provide examples for instructors that can be implemented in their own courses.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
