Supporting collaborative reflection by K-12 teachers with analytics from intelligent tutoring software

通过智能辅导软件的分析支持 K-12 教师的协作反思

• 批准号: 2119501
• 负责人: Vincent Aleven
• 金额: $ 85万
• 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: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2119501&HistoricalAwards=false
• 关键词: Supporting; collaborative; reflection; 12; teachers

One way K-12 teachers engage in lifelong professional learning is by reflecting on their own practices, for example by reviewing video recordings from their class sessions. Past research shows that reflection has powerful effects on teachers’ classroom practice. A separate line of past research shows that students learn very well with AI-based intelligent tutoring software (ITS), for example, in middle-school and high-school mathematics, and that teachers' support contributes to this effect. It is likely that teachers could help students more effectively if they were to periodically reflect on their classroom practices with regard to this type of software. Yet effective reflection is hampered by the fact that it is nearly impossible for teachers to notice and remember all that happens during any given classroom period. A well-designed tool that presents analytics extracted from class sessions could be a great help. The current research therefore investigates how to design an analytics tool that can support K-12 teachers in reflecting collaboratively with trusted colleagues on their classroom practices around students’ work with intelligent tutoring systems (ITS). The project will build an innovative tool that allows computers to automatically collect and analyze multiple sources of data (i.e., multimodal analytics). The tool will prompt reflection and inform discussion among teachers, for example about their students’ learning progress or challenges, and about their own, possibly implicit, biases towards certain students or groups of students. Through reflection with data, teachers can identify ways to improve their teaching practices, student learning, and equity in their classrooms. The main goal of the project is to design and create such a tool, test whether it supports effective collaborative reflection among teachers, and whether it leads to improved classroom practices. The project will contribute to the broader goal of making analytics useful for teachers. It has the potential to improve a highly effective form of K-12 classroom instruction, namely, learning with ITS, an increasingly common learning environment. The project will design, create, and pilot-test a new analytics tool for supporting teachers in jointly reflecting on their classroom practices around ITS. The tool will leverage multimodal analytics; it will extract and show trends in students’ learning and teachers’ practices and illustrate them with strategically selected examples from its own data store, recorded during ITS sessions. The tool will take advantage of (1) location data, collected with sensors placed in classrooms, to reveal patterns in teachers’ movement in the classroom, (2) physiological data, collected with physiological wristbands worn by teachers, to reveal ways in which their stress level affects students, (3) log data detailing students’ interactions with the tutoring system, analyzed to detect progress, struggles, knowledge growth, and learning behaviors, and (4) video data that capture important detail about classroom interactions. The reflection tool will be designed with middle-school teachers. Teachers will be involved in the research start-to-finish to make sure the tool matches their preferences and needs. The design will be guided by a proven model of teacher reflection, adapted for multimodal analytics from sessions with an ITS. The tool will be implemented within CTAT+Tutorshop, a widely-used platform for ITS research and development. Many of the needed analytics already exist within CTAT+Tutorshop, but new ones will be developed as well. Over time, the tool will be continuously improved and pilot tested. At the end, teachers will test a classroom-ready prototype with their classes.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.

K-12教师参与终身专业学习的一种方式是反思自己的实践，例如通过回顾课堂录像。以往的研究表明，反思对教师的课堂实践有着重要的影响。过去的另一项研究表明，学生在基于人工智能的智能辅导软件（ITS）中学习得非常好，例如在初中和高中数学中，教师的支持有助于实现这一效果。如果教师定期反思有关此类软件的课堂实践，他们可能可以更有效地帮助学生。然而，教师几乎不可能注意到并记住任何一节课上发生的所有事情，这一事实阻碍了有效的反思。一个设计良好的工具，提供从课堂上提取的分析可能是一个很大的帮助。因此，目前的研究调查如何设计一个分析工具，可以支持K-12教师在他们的课堂实践中与值得信赖的同事围绕学生的工作与智能辅导系统（ITS）的协作反映。该项目将建立一个创新的工具，允许计算机自动收集和分析多个数据源（即，多模态分析）。该工具将促进教师进行反思，并为讨论提供信息，例如关于学生的学习进展或挑战，以及关于他们自己对某些学生或学生群体的可能隐含的偏见。通过对数据的反思，教师可以找到改善教学实践、学生学习和课堂公平的方法。该项目的主要目标是设计和创建这样一个工具，测试它是否支持教师之间的有效合作反思，以及它是否会改善课堂实践。该项目将有助于实现更广泛的目标，使分析对教师有用。它有可能提高K-12课堂教学的一种高效形式，即与ITS一起学习，这是一种越来越普遍的学习环境。该项目将设计，创建和试点测试一个新的分析工具，以支持教师共同反思他们围绕ITS的课堂实践。该工具将利用多模态分析;它将提取和显示学生学习和教师实践的趋势，并从ITS会议期间记录的自己的数据存储中战略性地选择示例来说明这些趋势。该工具将利用（1）位置数据，通过放置在教室中的传感器收集，以揭示教师在教室中的运动模式，（2）生理数据，通过教师佩戴的生理腕带收集，以揭示他们的压力水平影响学生的方式，（3）详细记录学生与辅导系统的互动的日志数据，分析以检测进步，斗争，知识增长，和学习行为，以及（4）捕捉课堂互动重要细节的视频数据。反思工具将与中学教师一起设计。教师将全程参与研究，以确保该工具符合他们的偏好和需求。该设计将由教师反思的成熟模型指导，适用于ITS会话的多模态分析。该工具将在CTAT+Tutorshop中实施，CTAT +Tutorshop是一个广泛使用的ITS研究和开发平台。CTAT+Tutorshop中已经存在许多所需的分析，但也将开发新的分析。 随着时间的推移，该工具将不断得到改进和试点测试。最后，教师将在课堂上测试一个准备好的原型。这个奖项反映了NSF的法定使命，并被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

项目成果

Teacher noticing and student learning in human-AI partnered classrooms: A multimodal analysis

人类与人工智能合作课堂中的教师注意和学生学习：多模态分析

• 发表时间: 2023
• 期刊: International Society of the Learning Sciences
• 作者: Karumbaiah, S.;Borchers, C.;Falhs, A.;Holstein, K.;Rummel, N.;Aleven, V.
• 通讯作者: Aleven, V.

Multimodal analytics for collaborative teacher reflection of human-ai hybrid teaching: design opportunities and constraints

人机混合教学的协作教师反思的多模态分析：设计机会和限制

• 发表时间: 2023
• 期刊: Springer
• 作者: Karumbaiah, S.;Liu, P.;Maksimova, A.;De Vylder, L.;Rummel, N.;Aleven, V.
• 通讯作者: Aleven, V.

Optimizing parameters for accurate position data mining in diverse classrooms layouts

优化参数以在不同的教室布局中进行准确的位置数据挖掘

• 发表时间: 2023
• 期刊: International Educational Data Mining Society
• 作者: Shou, T.;Borchers, C.;Karumbaiah, S.;Aleven, V.
• 通讯作者: Aleven, V.

A Spatiotemporal Analysis of Teacher Practices in Supporting Student Learning and Engagement in an AI-Enabled Classroom

• DOI: 10.1007/978-3-031-36272-9_37
• 发表时间: 2023
• 作者: Shamya Karumbaiah;Conrad Borchers;Tianze Shou;Ann-Christin Falhs;Pinyang Liu;Tomohiro Nagashima;N. Rummel;V. Aleven

The function of teacher dashboards depends on the amount of time pressure in the classroom situation: Results from teacher interviews and an experimental study

教师仪表板的功能取决于课堂情况的时间压力：教师访谈和实验研究的结果

• DOI: 10.1007/s42010-022-00156-9
• 发表时间: 2022
• 期刊: Unterrichtswissenschaft
• 作者: van Leeuwen, Anouschka;Rummel, Nikol
• 通讯作者: Rummel, Nikol