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AI Institute for Inclusive Intelligent Technologies for Education (INVITE)

AI Institute for Inclusive Intelligent Technologies for Education (INVITE)
AI 普惠智能教育技术研究所 (INVITE)
批准号:
2229612
负责人:
H Chad Lane
金额:
$1999.87万
依托单位国家:
美国
项目类别:
Cooperative Agreement
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-06-01 至 2028-05-31

项目摘要

项目成果

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中文摘要
翻译
教育包容性和智能技术研究所(INVITE)试图通过开发人工智能(AI)工具和方法来支持三项重要的非认知技能,以从根本上重新定义教育技术与学习者的互动方式:坚持不懈、学术韧性和协作。这一新一代系统将从根本上更好地响应学习者的需求、行为和发展,并被设计为支持整个学习者,而不仅仅是专注于学科的成就。受使用启发的研究将集中在儿童如何交流STEM内容,他们如何学习在具有挑战性的工作中坚持,以及教师如何支持和促进非认知技能的发展。由此产生的基于人工智能的工具将被整合到课堂中,使教师能够以更适合发展的方式支持学习者。这项工作将产生一组丰富的数据,记录学习者与教育技术、彼此和教师的互动,使研究人员能够研究学习者随时间和不同STEM活动的成长。研究和推广活动将利用邀请K-12合作伙伴网络,覆盖24个学区和8个州的非营利组织,覆盖多达96,000名学习者。该研究所将提供包容性计划,以支持不同的学生参与研究经验、教育中的人工智能本科课程以及教师的专业发展计划。研究所的研究将在稳健和公平的机器学习、学习者建模和自然语言理解方面追求基础的人工智能进步,以实现对随时间和跨领域的非认知技能发展的评估和建模。它将围绕三个相互关联的方面:(1)收集、分析和共享新的数据集,以实现公平和稳健的机器学习和自然语言理解;(2)建立理解学习者行为的新的、稳健的方法和持久的、集成的学习者模型,其中包括对非认知技能的评估;(3)发展新的包容性STEM学习环境,提供与具有社会意识的教学主体的自然和适应性互动。符合真实数据和模拟学习者的可解释生成模型将使关于人类学习的新发现和假设成为可能。受使用启发的研究将推进STEM学习过程中非认知技能获得的科学,并揭示历史上被人工智能系统忽视的学习的相关背景方面。该研究所将成为建设研究、教育能力的纽带,并扩大人工智能与全民教育交叉领域的参与,为广泛的利益攸关方提供服务。具体地说,该研究所将(1)建立一个多模式数据集数据库,供其他研究人员使用,(2)提供开源工具和机会,以开发关于创新的人工智能教育系统的使用、控制和影响的知识,以及(3)积极建设一支多元化的未来科学家和工程师队伍,以设计、实施和部署下一代人工智能教育全民教育系统。美国教育部教育科学研究所的国家教育研究中心正在与NSF合作,为该研究所提供资金。这一奖项反映了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。
英文摘要
The Institute for Inclusive and Intelligent Technologies for Education (INVITE) seeks to fundamentally reframe how educational technologies interact with learners by developing artificial intelligence (AI) tools and approaches to support three crucial noncognitive skills known to underlie effective learning: persistence, academic resilience, and collaboration. This new generation of systems will be radically more responsive to learner needs, behaviors, and development and be designed to support the whole learner, beyond discipline-focused achievement. Use-inspired research will focus on how children communicate STEM content, how they learn to persist through challenging work, and how teachers support and promote noncognitive skill development. The resultant AI-based tools will be integrated into classrooms to empower teachers to support learners in more developmentally appropriate ways. This work will generate a rich set of data documenting learners’ interactions with educational technologies, each other, and teachers, allowing researchers to study learner growth over time and across different STEM activities. Research and outreach activities will draw from the INVITE K-12 partner network reaching up to 96,000 learners across 24 school districts and nonprofits spanning 8 states. The Institute will offer inclusive programs to support diverse students’ participation in research experiences, undergraduate courses in AI in education, and professional development programs for teachers.Institute research will pursue foundational AI advances in robust and fair machine learning, learner modeling, and natural language understanding to enable assessment and modeling of noncognitive skill development over time and across domains. It will revolve around three interconnected strands: (1) Collect, analyze, and share novel datasets for fair and robust machine learning and natural language understanding; (2) Build novel, robust methods for understanding learner behaviors and persistent, integrated learner models that incorporate assessments of noncognitive skills; (3) Develop new inclusive STEM learning environments that provide natural and adaptive interaction with socially-aware pedagogical agents. Interpretable generative models fit to real data and simulated learners will enable new discoveries and hypotheses about human learning. Use-inspired research will advance the science of noncognitive skill acquisition during STEM learning and uncover relevant contextual aspects of learning historically overlooked by AI systems. The institute will serve as a nexus for building capacity for research, education, and broadening participation in the intersection of AI and Education for All, serving a wide array of stakeholders. Specifically, the Institute will (1) produce a database of multimodal datasets for use by other researchers, (2) provide open source tools and opportunities to develop knowledge about the use, control, and impact of innovative AI-enabled education systems, and (3) actively build a diverse workforce of future scientists and engineers to design, implement, and deploy the next generation of AI-enabled Education for All systems. The National Center for Education Research at the Institute of Education Sciences of the US Department of Education is partnering with NSF to provide funding for the Institute.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.
期刊论文(7)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1145/3577190.3614127
发表时间: 2023-10
期刊: Proceedings of the 25th International Conference on Multimodal Interaction
影响因子: --
作者: [Yingbo Ma;Mehmet Celepkolu;K. Boyer;Collin Lynch;E. Wiebe;Maya Israel]
通讯作者: Yingbo Ma;Mehmet Celepkolu;K. Boyer;Collin Lynch;E. Wiebe;Maya Israel
DOI: 10.1016/j.jecp.2023.105775
发表时间: 2024
期刊: Journal of Experimental Child Psychology
影响因子: 2.6
作者: [Gladstone, Jessica R., Tallberg, Molly, Jaxon, Jilana, Cimpian, Andrei]
通讯作者: Cimpian, Andrei
DOI: 10.1145/3626252.3630811
发表时间: 2024
期刊: Proceedings of the 55th ACM Technical Symposium on Computer Science Education V.1
影响因子: --
作者: [Ojha, Vidushi, West, Leah, Lewis, Colleen M.]
通讯作者: Lewis, Colleen M.
DOI: 10.18653/v1/2023.emnlp-main.881
发表时间: 2023-12
期刊: ArXiv
影响因子: --
作者: [Ziheng Zeng;Kellen Tan Cheng;Srihari Venkat Nanniyur;Jianing Zhou;Suma Bhat]
通讯作者: Ziheng Zeng;Kellen Tan Cheng;Srihari Venkat Nanniyur;Jianing Zhou;Suma Bhat
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