Support for Doctoral Students to Attend International Conferences: Artificial Intelligence in Education (AIED 2015) and Educational Data Mining Society (EDM 2015)

支持博士生参加国际会议：人工智能教育（AIED 2015）和教育数据挖掘协会（EDM 2015）

• 批准号: 1539739
• 负责人: Beverly Woolf
• 金额: $ 1.85万
• 依托单位: University of Massachusetts Amherst
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-05-01 至 2016-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1539739&HistoricalAwards=false
• 关键词: Support; Doctoral; Students; Attend; International

The Cyberlearning and Future Learning Technologies Program funds efforts that support envisioning the future of learning technologies and advancing what we know about how people learn in technology-rich environments. Capacity-building (CAP) projects help build the capacity of the field to do high-quality, high-impact research on learning. This project supports the mission of NSF to train more advanced professionals in Science, Technology, Engineering, and Mathematics (STEM) by supporting doctoral students attendance at the International Conference on Artificial Intelligence in Education (AIED) and the 6th International Conference on Educational Data Mining (EDM) to be held in Madrid, Spain in June of 2015. The intellectual merit of the grant rests on the quality of the research being presented at the conferences. Together, the conferences provide cross-fertilization of information and ideas from artificial intelligence, cognitive science, machine learning, education, learning sciences, educational technology, psychology, philosophy, sociology, anthropology, linguistics, and the many domain-specific areas for which cyberlearning systems are designed and built. The broader impact of the work rests in the inculcation of students into this field. Doctoral students will be selected from U.S. institutions. The criteria for selection include either having a paper accepted for one of the conferences and/or or submitting an strong rationale for what the student would learn at the conference. All students receiving support will be assigned a mentor. The selecting committee will strive to ensure that there is diversity of institutions, topics, disciplines, ethnicities, and gender in the cohort of awardees. Selected students will receive up to $1,000 to partially cover expenses.

网络学习和未来学习技术计划资助的努力，支持设想学习技术的未来，并推进我们所知道的人们如何在技术丰富的环境中学习。 能力建设（CAP）项目有助于建设该领域进行高质量、高影响力学习研究的能力。 该项目支持NSF的使命，通过支持博士生参加将于2015年6月在西班牙马德里举行的国际人工智能教育会议（AIED）和第六届国际教育数据挖掘会议（EDM），培养更多科学，技术，工程和数学（STEM）方面的高级专业人员。赠款的智力价值取决于在会议上提出的研究的质量。这些会议共同提供了来自人工智能，认知科学，机器学习，教育，学习科学，教育技术，心理学，哲学，社会学，人类学，语言学以及网络学习系统设计和构建的许多特定领域的信息和想法的交叉施肥。这项工作更广泛的影响在于向学生灌输这一领域的知识。博士生将从美国院校中选拔。选择的标准包括要么有一个会议接受的文件和/或提交一个学生将在会议上学到什么强有力的理由。 所有获得支持的学生将被分配一位导师。 遴选委员会将努力确保获奖者群体中的机构、主题、学科、种族和性别的多样性。 被选中的学生将获得高达1,000美元，以支付部分费用。