Professional Informatics in Support of Inclusive and Equitable Teaching Practices

支持包容和公平教学实践的专业信息学

• 批准号: 2222530
• 负责人: Tricia Ngoon
• 金额: $ 30万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2222530&HistoricalAwards=false
• 关键词: Professional; Informatics; Support; Inclusive; Equitable

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).College instructors often receive little to no feedback about their teaching or teaching strategies. Moreover, stark gender and racial disparities in STEM classrooms point to issues of inequality and uneven quality of learning experiences. This research project is designed to explore the use of sensing systems such as cameras and microphones in classrooms to collect data about how instructors teach. That data can then form the basis for personalized feedback on teaching practices. This overall program of investigation aims to reframe personal informatics, the use of self-tracked data to achieve one’s goals, as professional informatics (Pro-I) that can help STEM instructors improve their craft and, in so doing, create more equitable learning experiences. Such improvements hold promise especially, to increase STEM participation among students who are underrepresented in their participation in STEM fields of study. This research also has the potential to contribute to a general understanding of the use of sensing technologies in classrooms as a teaching aid and provide materials that aid self-reflection and improvement that could benefit many faculty. The principal investigator seeks to use Pro-I technologies to help STEM instructors further develop their professional practice with a view towards creating more equitable learning experiences in their undergraduate courses. Prevalent sources of feedback to faculty about their teaching, if received at all, are based on human observations, which do not always scale well. This project is designed to use classroom sensing systems to collect multimodal data such as movement patterns, gaze, facial expressions, and audio to provide a nuanced picture of teaching behaviors. The resulting data will be the basis for multimodal analytics designed to help instructors reflect on their teaching practices and derive actionable insights for improvement. This research could extend two existing technologies: EduSense a computer-vision based classroom sensing system and Edulyze an analytics pipeline for processing and visualizing multimodal classroom data. This project is comprised of three studies. First, educational stakeholders such as instructors, students, and administrators will be interviewed about their perceptions of privacy, agency, and adoption of Pro-I data and systems. Second, classroom data will be collected through EduSense and examined through Edulyze with particular attention to how analyses influence instructors’ self-efficacy and motivation to improve their teaching. Analyses will also examine the design of data visualizations for multimodal classroom data. Third, based on the results of the first two studies, a prototype Pro-I system will be developed and deployed for a semester to examine the effects of reflecting on the resulting analyses. This research has the potential for important contributions: increased understanding of the perceptions of privacy, agency, and adoption of Pro-I systems as they relate to the ethical design of classroom sensing systems; empirical evidence of how Pro-I data can impact instructors’ self-efficacy and motivation to improve their teaching; and the Pro-I technology that is intended to scaffold instructor reflections about classroom data as a means to further develop professional vision for equitable teaching and learning.The project responds to the STEM Education Postdoctoral Research Fellowship (STEM Ed PRF) program that aims to enhance the research knowledge, skills, and practices of recent doctorates in STEM, STEM education, education, and related disciplines to advance their preparation to engage in fundamental and applied research that advances knowledge within the field.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源于《2021 年美国救援计划法案》（公法 117-2）。大学教师通常很少甚至没有收到有关其教学或教学策略的反馈。此外，STEM 课堂上存在明显的性别和种族差异。该研究项目旨在探索在教室中使用摄像头和麦克风等传感系统来收集有关教师教学方式的数据，这些数据可以为个性化教学奠定基础。这项总体调查计划旨在重新构建个人信息学，即使用自我跟踪数据来实现个人目标，作为专业信息学 (Pro-I)，可以帮助 STEM 教师提高他们的技能，并在此过程中，创造更公平的学习体验尤其有望提高参与 STEM 学习领域的学生的 STEM 参与度。这项研究还有可能有助于人们普遍了解传感技术在课堂上的使用。作为首席研究员寻求使用 Pro-I 技术帮助 STEM 教师进一步发展他们的专业实践，以期在本科课程中创造更公平的学习体验。教师关于其教学的反馈的普遍来源（如果有的话）都是基于人类观察，而这些反馈并不总是能够很好地扩展。该项目旨在使用课堂传感系统来收集多模态数据，例如运动模式、凝视、面部表情。和音频来提供细致入微的画面由此产生的数据将成为多模式分析的基础，旨在帮助教师反思他们的教学实践并得出可操作的改进见解。这项研究可以扩展两种现有技术：EduSense（基于计算机视觉的课堂传感系统）和 Edulyze 。该项目由三项研究组成，首先，将采访教师、学生和管理人员等教育利益相关者，了解他们对隐私、代理以及 Pro-I 数据和系统采用的看法。二、课堂数据将通过 EduSense 收集并通过 Edulyze 进行检查，特别关注分析如何影响教师的自我效能和改进教学的动机。第三，基于结果的分析还将检查多模式课堂数据的数据可视化设计。在前两项研究中，将开发一个原型 Pro-I 系统并部署一个学期，以检查反思对结果分析的影响。这项研究具有重要贡献的潜力：增进对隐私、代理和采用的看法的理解。 Pro-I的系统，因为它们与课堂传感系统的道德设计有关；Pro-I 数据如何影响教师的自我效能和改进教学的动机的经验证据；以及旨在支持教师对课堂反思的 Pro-I 技术；该项目响应 STEM 教育博士后研究奖学金 (STEM Ed PRF) 计划，旨在增强近期博士在 STEM、STEM、STEM 领域的研究知识、技能和实践教育，教育，以及该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值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

"An Instructor is [already] able to keep track of 30 students": Students’ Perceptions of Smart Classrooms for Improving Teaching & Their Emergent Understandings of Teaching and Learning

“一名教师[已经]能够跟踪 30 名学生”：学生对智能教室改善教学的看法

• DOI: 10.1145/3563657.3596079
• 发表时间: 2023-07
• 期刊: ACM Designing Interactive Systems Conference (DIS '23
• 作者: Ngoon, Tricia J.;Kovalev, David;Patidar, Prasoon;Harrison, Chris;Agarwal, Yuvraj;Zimmerman, John;Ogan, Amy
• 通讯作者: Ogan, Amy