SBIR Phase II: Using Intervention and Feedback to Improve Group Function In Online Contexts

SBIR 第二阶段：利用干预和反馈来改善在线环境中的群体功能

• 批准号: 2026003
• 负责人: Elizabeth Porter
• 金额: $ 99.14万
• 依托单位: RIFF LEARNING INC
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-15 至 2023-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2026003&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Using; Intervention

The broader impact of this Small Business Innovation Research (SBIR) Phase II project is to create an online, instantaneous feedback mechanism during online engagements to improve soft skills of people group settings. The explosion of online learning experiences in recent years, in which many courses fail to engage learners or help them achieve their academic and professional goals, has focused on the problem of engagement. Interest in online learning remains high, as it presents an opportunity to broaden the reach of institutions and companies, but success rates in broadly available learning experiences are low. he project applies emerging innovations in artificial intelligence to the problem of delivering high-quality learning at scale. While most applications focus on individual learners and creating new personalized educational pathways, this project highlights the importance of collective learning and the power of peer engagement to help all members of a learning community reach their goals together. This Small Business Innovation Research (SBIR) Phase II project will further develop specialized video and text chat tools to collect data from groups engaged in synchronous online learning, analyze and categorize patterns of communication, and give feedback to students to help them have better, more successful experiences online. This project introduces several innovations in data capture and analytics, as well as feedback to learners while they are collaborating online. While many students use online collaboration tools such as discussion boards, chat, and video, this project focuses on providing interventions to change behavior in real-time. During conversations, such as those happening when people brainstorm to solve a problem or work on shared assignments, certain vocal patterns indicate engagement, reveal unstated agreements and discords, and expose individual biases. Using deep learning and data modeling, real-time feedback about conversational dominance is generated and shown to learners while they are speaking. The project further explores the effect of machine-generated insights about what happened during the collaboration, and makes recommendations about behavior modifications, based on predictive models. For more nuanced insights, these data are paired with facial-gestural data, such as nodding or raising one’s eyebrows. Together, these innovations combine data that has never been collected at scale before with social science data models uniquely applied to online learning. The goal of the project is to prove that insights like these have a net positive effect on learning outcomes and raise the level of satisfaction with online learning experiences that incorporate these tools.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.

这个小企业创新研究（SBIR）第二阶段项目的更广泛的影响是在在线参与期间创建一个在线即时反馈机制，以提高人群设置的软技能。 近年来，在线学习体验的爆炸式增长，其中许多课程未能吸引学习者或帮助他们实现学术和职业目标，重点是参与问题。对在线学习的兴趣仍然很高，因为它提供了扩大机构和公司覆盖面的机会，但广泛提供的学习经验的成功率很低。该项目将人工智能领域的新兴创新应用于大规模提供高质量学习的问题。虽然大多数应用程序侧重于个人学习者和创建新的个性化教育途径，但该项目强调了集体学习的重要性和同伴参与的力量，以帮助学习社区的所有成员共同实现他们的目标。这个小企业创新研究（SBIR）第二阶段项目将进一步开发专门的视频和文本聊天工具，从参与同步在线学习的群体中收集数据，分析和分类交流模式，并向学生提供反馈，帮助他们获得更好，更成功的在线体验。该项目介绍了数据采集和分析方面的几项创新，以及在线协作时向学习者提供的反馈。虽然许多学生使用在线协作工具，如讨论板，聊天和视频，这个项目的重点是提供干预措施，实时改变行为。在谈话中，比如人们为了解决一个问题或共同完成一项任务而进行头脑风暴时，某些声音模式表明了参与，揭示了未言明的一致和不一致，并暴露了个人偏见。使用深度学习和数据建模，生成有关会话主导地位的实时反馈，并在学习者说话时向他们显示。该项目进一步探索了机器生成的关于协作期间发生的事情的见解的影响，并基于预测模型提出了关于行为修改的建议。为了获得更细致的洞察力，这些数据与面部手势数据配对，例如点头或扬起眉毛。总之，这些创新将以前从未大规模收集的联合收割机数据与专门应用于在线学习的社会科学数据模型相结合。该项目的目标是证明这些见解对学习成果有净积极影响，并提高对包含这些工具的在线学习体验的满意度。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。