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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

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中文摘要
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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)
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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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