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.

该奖项全部或部分由2021年美国救援计划法案（公法117-2）资助。大学教师通常很少收到有关其教学或教学策略的反馈。此外，STEM教室中明显的性别和种族差异表明了学习经验的不平等和质量参差不齐的问题。该研究项目旨在探索在教室中使用摄像机和麦克风等传感系统来收集有关教师如何教学的数据。然后，这些数据可以形成对教学实践的个性化反馈的基础。这个整体调查计划旨在重新构建个人信息学，使用自我跟踪数据来实现目标，作为专业信息学（Pro-I），可以帮助STEM教师提高他们的技能，并在这样做的过程中创造更公平的学习体验。这些改进特别有希望增加那些在STEM研究领域参与人数不足的学生的STEM参与。这项研究也有可能有助于在课堂上使用传感技术作为教学辅助工具的一般理解，并提供有助于自我反思和改进的材料，这可能使许多教师受益。首席研究员寻求使用Pro-I技术来帮助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。教师对他们的教学反馈的普遍来源，如果收到的话，是基于人类的观察，这并不总是很好的规模。该项目旨在使用教室传感系统收集多模态数据，如运动模式，凝视，面部表情和音频，以提供教学行为的细微差别。由此产生的数据将成为多模态分析的基础，旨在帮助教师反思他们的教学实践，并获得可操作的见解以进行改进。这项研究可以扩展两种现有的技术：EduSense，一种基于计算机视觉的教室传感系统和Edulyze，一种用于处理和可视化多模态教室数据的分析管道。该项目由三项研究组成。首先，教育利益相关者，如教师，学生和管理人员将接受采访，了解他们对隐私，代理和采用Pro-I数据和系统的看法。其次，课堂数据将通过EduSense收集，并通过Edulyze进行检查，特别注意分析如何影响教师的自我效能和动机，以改善他们的教学。分析还将研究多模态课堂数据的数据可视化设计。第三，根据前两项研究的结果，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：增加对隐私，代理和采用Pro-I系统的看法的理解，因为它们与教室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动机的经验证据，以改善他们的教学;而亲，该项目旨在支持教师对课堂数据的反思，作为进一步发展公平教学和学习的专业愿景的一种手段。博士后研究奖学金（干艾德PRF）计划，旨在提高研究知识，技能，并在干，干教育，教育，该奖项反映了NSF的法定使命，并被认为是值得通过使用基金会的学术价值和更广泛的影响审查标准。