成为信息的优秀管理者：将伦理、公民与职业素养融入统计与数据科学课程的框架
Becoming Good Stewards of Information: A framework for integrating ethical, civic, and professional formation throughout the statistics and data science curriculum
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中文总结 AI 辅助
该研究提出将信息管理作为统一框架，用于在统计与数据科学课程中融入伦理、公民与职业素养，并提供了课程实施示例与学生参与的初步证据。
中文摘要 AI 辅助
近期统计与数据科学教育的相关建议强调，教学目标不应仅局限于知识掌握，还应包括统计素养、循证决策、沟通能力、伦理意识、数据的负责任使用以及公民责任感。我们认为，这些目标均可通过一个共同视角来理解：帮助学生成为更优秀的信息管理者。信息管理为培养学生成为统计学家、数据科学家与公民提供了统一框架，使其成为审慎的数据与证据生产者和消费者，以诚信与透明的方式传达研究结果，批判性地对待数据伦理，认识到数据背后的人，并利用数据做出明智决策、服务社区、推进公共利益。我们提出信息管理作为一种发展性模型，可在课程早期引入，并在入门、高级、应用及理论课程中以逐步深化的方式反复呈现。为说明该方法，我们提供了课程活动与精选每周阅读材料的具体示例，作为低门槛实施策略，并呈现了学生参与该框架的初步证据。本文通过提供概念基础与实用实施策略，为将伦理、职业与公民素养融入统计与数据科学课程提供了连贯的方法。
英文摘要
Recent recommendations in statistics and data science education emphasize goals that extend beyond content mastery, including statistical literacy, evidence-based decision-making, communication, ethics, responsible use of data, and civic responsibility. We argue these goals can all be understood through a common lens: helping students become better stewards of information. Stewardship of information provides a unifying framework for the formation of students as statisticians, data scientists, and citizens who are thoughtful producers and consumers of data and evidence, communicate findings with integrity and transparency, engage critically with data ethics, recognize the human beings behind the data, and harness data to make informed decisions, serve communities, and advance the common good. We present stewardship of information as a developmental model that can be introduced early and revisited with increasing sophistication across a curriculum, including in introductory, advanced, applied, and theoretical courses. To illustrate this approach, we provide concrete examples of course activities and curated weekly readings as a low-barrier implementation strategy and present preliminary evidence of student engagement with the framework. By offering both a conceptual foundation and practical implementation strategies, this paper contributes a coherent approach for integrating ethical, professional, and civic formation across the statistics and data science curriculum.
