Support for U.S. Doctoral Students to Participate in the Annual Artificial Intelligence in Education (AIED) and co-located Educational Data Mining (EDM) Conferences

支持美国博士生参加年度教育人工智能 (AIED) 和同期举办的教育数据挖掘 (EDM) 会议

• 批准号: 2225091
• 负责人: Neil Heffernan
• 金额: $ 2.5万
• 依托单位: Worcester Polytechnic Institute
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2225091&HistoricalAwards=false
• 关键词: Support; U.S.; Doctoral; Students; Participate

The United States has historically been the global leader in the field of artificial intelligence in education (AIED), or ways to use computerized artificial intelligence to enhance teaching and learning in contexts ranging from children learning math in school, to soldiers learning highly technical jobs in the US military. The preeminent conference in this field is the AIED conference; at this conference the latest research is presented and practitioners learn the state of the art techniques that allow creation of these important educational technologies. A related conference that is equally significant is the Educational Data Mining (EDM) conference, which focuses on research on big data and analytics for education. This proposal would provide partial travel support for 10 Ph.D. students from the United States, selected through a competitive process, to attend the AIED conference and/or EDM conference, present their work, and receive additional mentoring outside of their dissertation committees as part of a doctoral consortium. The intellectual merit of the work rests on the studies the graduate students submit to be considered for participation in the early career track of the conference; this work is then enhanced by guidance from world-class mentors who meet with the students in a structured format to improve their research. The broader impact includes the career impact on the twenty selected students, especially since promising graduate students whose advisors may not have funding to send them to the conference can still be included, and their work can be showcased and improved. Possible long-term broader impacts include building the field of artificial intelligence in education and data analytics researchers and thus eventually, improving the quality of education.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.

从历史上看，美国一直是人工智能教育（AIED）领域的全球领导者，或使用计算机化人工智能来增强教学和学习的方法，从儿童在学校学习数学到美国军队中学习高技术工作的士兵。这一领域最杰出的会议是AIED会议；在这次会议上，展示了最新的研究成果，从业人员学习了最先进的技术，这些技术可以创造这些重要的教育技术。一个同样重要的相关会议是教育数据挖掘（EDM）会议，该会议侧重于大数据和教育分析的研究。该提案将为通过竞争程序选出的10名美国博士生提供部分旅行支持，以参加AIED会议和/或EDM会议，展示他们的工作，并作为博士联盟的一部分接受论文委员会以外的额外指导。这项工作的智力价值取决于研究生提交的研究，这些研究将被考虑参加会议的早期职业轨迹；然后，世界级的导师以结构化的形式与学生会面，以改进他们的研究，从而加强这项工作。更广泛的影响包括对20名入选学生的职业影响，特别是因为导师可能没有资金送他们参加会议的有前途的研究生仍然可以被包括在内，他们的工作可以被展示和改进。可能的长期更广泛的影响包括在教育和数据分析研究人员中建立人工智能领域，从而最终提高教育质量。该奖项反映了美国国家科学基金会的法定使命，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

Automatic Short Math Answer Grading via In-context Meta-learning

通过上下文元学习自动对简短数学答案进行评分

• 发表时间: 2022
• 期刊: Proceedings of the 15th International Conference on Educational Data Mining
• 作者: Zhang, Mengxue;Baral, Sami;Heffernan, Neil;Lan, Andrew
• 通讯作者: Lan, Andrew

Identifying Explanations Within Student-Tutor Chat Logs

识别学生与导师聊天日志中的解释

• 发表时间: 2022
• 期刊: Educational data Mining Conference
• 作者: Prihar, Ethan;Moore, Alexander;Heffernan, Neil
• 通讯作者: Heffernan, Neil

Improving Automated Assessment and Feedback for Student Open-responses in Mathematics

• 发表时间: 2022
• 期刊: Applied Sciences
• 作者: Sami Baral

Student Perception on the Effectiveness of On-Demand Assistance in Online Learning Platforms

学生对在线学习平台按需援助有效性的看法

• 发表时间: 2022
• 期刊: Educational Data Mining Conference
• 作者: Haim, Aaron;Heffernan, Neil
• 通讯作者: Heffernan, Neil

Process-BERT: A Framework for Representation Learning on Educational Process Data

• DOI: 10.48550/arxiv.2204.13607
• 发表时间: 2022-04
• 期刊: ArXiv
• 作者: Alexander Scarlatos;Christopher G. Brinton;Andrew S. Lan