Collaborative Research: Diversifying Human-Centered Data Science through the Research and Design of Ethical Games

协作研究：通过道德博弈的研究和设计使以人为本的数据科学多样化

• 批准号: 2127924
• 负责人: Sarah Evans
• 金额: $ 11.4万
• 依托单位: University of North Texas
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-12-01 至 2024-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2127924&HistoricalAwards=false
• 关键词: Collaborative; Research; Diversifying; Human; Centered

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). Tackling the overwhelming issues in data science and machine learning require new ways of training and combining expertise from social science, human-centered design, information studies, statistics, computer science, and related fields. We invite interested undergraduates across disciplines to collaborate on the research and design of a serious game on data ethics issues. In this context, our project studies collaborative learning in groups of peers with conflicting methodological cultures and diverse backgrounds. Participating students will come from two university campuses in different regions of the United States to form a single team of diverse individuals collaborating in a virtual setting. By studying students’ experiences throughout the project, we will increase our understanding of learning through collaboration over time and in relation to their sociocultural histories. An additional artifact of this two-year, interdisciplinary project will be a prototype of an educational game, targeted towards the underrepresented communities and the greater public, that will bring more people into critical conversations about the roles of AI and data science in our society.The primary aim of our research is the production of novel theories in learning sciences regarding collaborative learning in the face of diverse backgrounds and cultural norms. How do students individually and collectively position themselves within data ethics and do these views change over time with increased exposure to technical concepts and norms? How do students reconcile conflicting norms in the design of a single design project? Does the collaborative design of an ethical simulation game facilitate diverse student learning experiences? Our work will be conducted as an ethnographic case study with analysis heavily informed by sociocultural-historical theory. Multiple streams of data will be collected over the course of the project, including observations in the “field,” i.e. of the team meetings (consisting of both audiovisual recordings and researchers’ field notes), informal conversations with participants, products created by the team (such as papers, images, prototypes, etc), brief surveys, and participant interviews. This work aims to contribute new theories on collaborative learning to the body of research in learning sciences as well as serve as a case study for future educational projects situated between disciplines with conflicting cultural norms.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该奖项的全部或部分资金来自《2021年美国救援计划法案》(公法117-2)。解决数据科学和机器学习中的压倒性问题需要新的培训方式，并将社会科学、以人为中心的设计、信息研究、统计学、计算机科学和相关领域的专业知识结合起来。我们邀请各学科感兴趣的本科生合作研究和设计一款关于数据伦理问题的严肃游戏。在这种背景下，我们的项目研究了具有相互冲突的方法文化和不同背景的同龄人之间的协作学习。参赛学生将来自美国不同地区的两所大学校园，组成一个由不同个人组成的单一团队，在虚拟环境中进行合作。通过研究学生在整个项目中的经历，我们将随着时间的推移，通过合作以及与他们的社会文化历史的关系来增加我们对学习的理解。这个为期两年的跨学科项目的另一个产物将是一个教育游戏的原型，目标是代表不足的社区和更广泛的公众，它将把更多的人带入关于人工智能和数据科学在我们社会中的角色的批判性对话中。我们研究的主要目的是在面对不同背景和文化规范的情况下，在学习科学中产生关于协作学习的新理论。学生如何单独和集体地在数据伦理中定位自己，这些观点是否会随着时间的推移而随着对技术概念和规范的接触而发生变化？在单一设计项目的设计中，学生如何协调相互冲突的规范？伦理模拟游戏的协作设计是否有助于学生获得不同的学习体验？我们的工作将作为一个人种学案例研究进行，分析中大量参考了社会文化-历史理论。在项目过程中将收集多种数据，包括“实地”观察，即团队会议(包括视听录音和研究人员实地笔记)、与参与者的非正式对话、团队创造的产品(如论文、图像、原型等)、简要调查和对参与者的访谈。这项工作旨在为学习科学的研究机构贡献关于协作学习的新理论，并作为未来位于文化规范冲突的学科之间的教育项目的案例研究。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Game Development as Speculative Design: Teaching Data Science Ethics Using Decentralized Research Groups

作为推测性设计的游戏开发：利用分散的研究小组教授数据科学伦理

• DOI: 10.1002/pra2.672
• 发表时间: 2022
• 期刊: Proceedings of the Association for Information Science and Technology
• 作者: Byun, Mimi;Evans, Sarah;Herman, Bernease;Aragon, Cecilia;Rojas‐Ponce, Diana
• 通讯作者: Rojas‐Ponce, Diana