| NSF Org: |
IIS Division of Information & Intelligent Systems |
| Recipient: |
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| Initial Amendment Date: | September 2, 2016 |
| Latest Amendment Date: | September 2, 2016 |
| Award Number: | 1650295 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Tatiana Korelsky
IIS Division of Information & Intelligent Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | September 1, 2016 |
| End Date: | August 31, 2018 (Estimated) |
| Total Intended Award Amount: | $22,600.00 |
| Total Awarded Amount to Date: | $22,600.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
2275 E BAYSHORE RD STE 160 East Palo Alto CA US 94303-3224 (650)328-3123 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
CA US 94303-3224 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | Cyberlearn & Future Learn Tech |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
The Cyberlearning and Future Learning Technologies Program funds efforts that will help envision the next generation of learning technologies and advance what we know about how people learn in technology-rich environments. Cyberlearning CAP projects build capacity for research and development in the field of cyberlearning by improving technical infrastructure, human capital, and in other ways. The Symposium on Educational Advances in Artificial Intelligence, affiliated with the AAAI (Association for the Advancement of Artificial Intelligence) conference in San Francisco in February 2017 is a premier venue for sharing knowledge about how to use AI in education and how to teach about AI. This grant helps support participation of US students and teachers in the conference, as well as early career faculty and organizers of REU (Research Experiences for Undergraduates) sites.
The symposium includes a variety of activities that advance the field and train the next generation of AI researchers and investigators. Peer reviewed papers and keynote addresses are complemented by sessions on model classroom assignments in teaching AI, and a competition for undergrads to create innovative tasks for students learning robotics. A discussion group will share best practices among REU site coordinators. Tracks will consider outreach and ethics in teaching AI. Broader impacts beyond the participants at the symposium are supported by the materials produced and shared among the community, such as the database of open educational materials, and the outputs of the student competition.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
This project supported educational activities and the participation of US-based students (including undergraduates through PhD students), early career faculty, secondary school educators, and Research Experiences for Undergraduates (REU) site organizers in the 2017 and 2018 Symposia on Educational Advances in Artificial Intelligence (EAAI-17 and EAAI-18). EAAI was co-located with AAAI, a premier conference in Artificial Intelligence (AI), drawing wide domestic and international participation, including many top AI researchers. The conference includes tutorials, workshops, and demonstrations, in addition to the main technical conference program and numerous co-located events, such as EAAI.
EAAI is the major forum for discussing and presenting current results in AI education and pedagogy at AAAI. EAAI provides a venue for AI researchers and educators to discuss pedagogical issues and share resources related to teaching and using AI in education across a variety of curricular levels (K-12 through postgraduate training), with an emphasis on undergraduate and graduate teaching and learning. The symposium includes contributions showing how to more effectively teach AI, as well as how themes from AI may be used to enhance education more broadly (for example, in introductory computing courses or as a means for teaching computational thinking). EAAI encourages the sharing of innovative educational approaches that convey or leverage AI and its many subfields, including robotics, machine learning, natural language processing, computer vision, and others.
The products resulting from EAAI, including the symposium proceedings and a set of ready-to-go Model AI assignments, are publicly available. The Model AI assignments included in EAAI are available openly for other educators to use in their classes, and are widely used around the world in teaching AI. The EAAI proceedings are published openly as part of the AAAI proceedings.
EAAI targets educators who might be outside of AAAI's usual community: those at smaller institutions, those who teach or use AI in their teaching, but not in their research, those from liberal arts colleges, and educators who serve student groups that are poorly represented in STEM disciplines. In addition, EAAI provides a unique mechanism to encourage undergraduate participation in AAAI.
Last Modified: 01/11/2019
Modified by: Eric Eaton
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