Conference: Advancing AI in Science Education (AASE): A Comprehensive Approach to Equity, Inclusion, and Three-Dimensional Learning

会议:推进科学教育中的人工智能 (AASE):公平、包容和三维学习的综合方法

基本信息

项目摘要

In the 21st century, the educational landscape is undergoing a seismic shift, with Artificial Intelligence (AI) emerging as a pivotal force reshaping the contours of teaching and learning, especially in the realm of science education. As educators, policymakers, and researchers grapple with the challenges and opportunities presented by this technological juggernaut, this project underscores the imperative to weave AI's transformative potential seamlessly with the foundational principles of Diversity, Equity, and Inclusion (DEI). The vision driving this initiative is twofold: harnessing the unparalleled capabilities of AI to revolutionize educational experiences while ensuring that these innovations are accessible, relevant, and beneficial to every student, irrespective of their background or circumstances. By energizing the cutting-edge advancements of AI with the timeless values of DEI, this project envisions a future where education is not only technologically advanced but also deeply equitable, adaptable, and centered on the holistic development of students. The overarching ambition is to chart a course where the next generation, regardless of socio-economic, racial, or cultural backgrounds, can fully tap into the myriad benefits that AI-infused science education offers.This project is anchored in a comprehensive, multi-pronged strategy designed to delve deep into the multifaceted dimensions of AI's role in science education. Drawing from a rich reservoir of insights, including the visionary perspectives articulated by the U.S. Department of Education and groundbreaking research spearheaded by current luminaries, the initiative is poised to craft a strategic roadmap for the seamless, effective, and equitable integration of AI into science education. Central to this endeavor is the project's unwavering commitment to three-dimensional learning, an avant-garde feature of the Next Generation Science Standards (NGSS). This innovative approach, harmoniously aligned with AI and DEI, promises a comprehensive educational experience that transcends traditional pedagogical boundaries, fostering a learning environment that is both immersive and inclusive. The project's methodology is characterized by its collaborative spirit and iterative nature. Through a series of strategic community-led workshops, participants from diverse backgrounds will converge to share insights, challenges, and strategies, fostering a rich tapestry of perspectives. This collaborative ethos extends to in-depth research initiatives, where participants, ranging from seasoned experts to budding scholars, will embark on exploratory journeys to unravel the nuances of AI in science education. Continuous feedback loops, characterized by rigorous reviews and refinements, will ensure that the project's outputs remain aligned with its DEI-centric vision.This project is funded by the Discovery Research preK-12 program (DRK-12) that seeks to significantly enhance the learning and teaching of science, technology, engineering, and mathematics (STEM) by preK-12 students and teachers, through research and development of innovative resources, models, and tools. Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects.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.
在21世纪的世纪,教育格局正在发生巨大的变化,人工智能(AI)正在成为重塑教学和学习轮廓的关键力量,特别是在科学教育领域。随着教育工作者、政策制定者和研究人员努力应对这一技术巨头带来的挑战和机遇,该项目强调了将人工智能的变革潜力与多样性、公平性和包容性(DEI)的基本原则无缝结合的必要性。推动这一倡议的愿景是双重的:利用人工智能无与伦比的能力来彻底改变教育体验,同时确保这些创新对每个学生都是可访问的,相关的,有益的,无论他们的背景或情况如何。通过用DEI永恒的价值观激励人工智能的前沿进步,该项目设想了一个教育不仅技术先进,而且非常公平,适应性强,以学生的全面发展为中心的未来。总体目标是制定一个课程,让下一代,无论社会经济,种族或文化背景如何,都可以充分利用人工智能注入科学教育所带来的无数好处。该项目立足于一个全面,多管齐下的战略,旨在深入研究人工智能在科学教育中作用的多方面因素。从丰富的见解库中汲取,包括美国教育部阐述的有远见的观点和当前杰出人士领导的开创性研究,该计划准备为人工智能无缝,有效和公平地融入科学教育制定战略路线图。这一奋进的核心是该项目对三维学习的坚定承诺,这是下一代科学标准(NGSS)的前卫特征。这种创新的方法与AI和DEI和谐一致,承诺提供超越传统教学界限的全面教育体验,培养沉浸式和包容性的学习环境。该项目的方法的特点是其协作精神和迭代性质。通过一系列由社区领导的战略研讨会,来自不同背景的参与者将汇聚在一起分享见解,挑战和战略,培养丰富的观点。这种合作精神延伸到深入的研究计划,参与者,从经验丰富的专家到初露头角的学者,将开始探索之旅,以解开人工智能在科学教育中的细微差别。持续的反馈循环,以严格的审查和改进为特征,将确保项目的产出与其以DEI为中心的愿景保持一致。该项目由Discovery Research preK-12计划(DRK-12)资助,旨在显著提高preK-12学生和教师的科学,技术,工程和数学(STEM)的学习和教学,通过研究和开发创新资源、模型和工具。DRK-12项目中的项目建立在STEM教育的基础研究以及为拟议项目提供理论和经验依据的先前研究和开发工作的基础上。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。

项目成果

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Xiaoming Zhai其他文献

Fine-tuning ChatGPT for automatic scoring
  • DOI:
    10.1016/j.caeai.2024.100210
  • 发表时间:
    2024-06-01
  • 期刊:
  • 影响因子:
  • 作者:
    Ehsan Latif;Xiaoming Zhai
  • 通讯作者:
    Xiaoming Zhai
Unveiling Scoring Processes: Dissecting the Differences Between LLMs and Human Graders in Automatic Scoring
  • DOI:
    10.1007/s10758-025-09836-8
  • 发表时间:
    2025-03-21
  • 期刊:
  • 影响因子:
    3.500
  • 作者:
    Xuansheng Wu;Padmaja Pravin Saraf;Gyeonggeon Lee;Ehsan Latif;Ninghao Liu;Xiaoming Zhai
  • 通讯作者:
    Xiaoming Zhai
Can generative AI and ChatGPT outperform humans on cognitive-demanding problem-solving tasks in science?
生成式 AI 和 ChatGPT 能否在需要认知能力的科学问题解决任务上超越人类?
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Xiaoming Zhai;Matthew Nyaaba;Wenchao Ma
  • 通讯作者:
    Wenchao Ma
Elucidating STEM Concepts through Generative AI: A Multi-modal Exploration of Analogical Reasoning
通过生成人工智能阐明 STEM 概念:类比推理的多模态探索
  • DOI:
    10.48550/arxiv.2308.10454
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Chen Cao;Zijian Ding;Gyeong;Jiajun Jiao;Jionghao Lin;Xiaoming Zhai
  • 通讯作者:
    Xiaoming Zhai
AI Gender Bias, Disparities, and Fairness: Does Training Data Matter?
人工智能性别偏见、差异和公平:训练数据重要吗?
  • DOI:
    10.48550/arxiv.2312.10833
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Ehsan Latif;Xiaoming Zhai;Lei Liu
  • 通讯作者:
    Lei Liu

Xiaoming Zhai的其他文献

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{{ truncateString('Xiaoming Zhai', 18)}}的其他基金

Supporting Instructional Decision Making: The Potential of An Automatically Scored Three-dimensional Assessment System
支持教学决策:自动评分三维评估系统的潜力
  • 批准号:
    2101104
  • 财政年份:
    2021
  • 资助金额:
    $ 9.98万
  • 项目类别:
    Continuing Grant
AI-based Assessment in STEM Education Conference
STEM 教育会议中基于人工智能的评估
  • 批准号:
    2138854
  • 财政年份:
    2021
  • 资助金额:
    $ 9.98万
  • 项目类别:
    Standard Grant

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