Keynote Speakers (TBD)
Title of the Talk
Abstract: xxx.
Short Bio:
XXX is a Professor at XX .
Recent advanced AI technologies, especially the large language models (LLMs) like GPTs, have significantly advanced the field of natural language processing (NLP) and led to the development of various LLM-based applications. One potential application is as communication interfaces in human-in-the-loop education systems, where the model serves as a mediator among the teacher, students and the machine capabilities including its own. This approach has several benefits, including the ability to personalize interactions, allow unprecedented flexibility and adaptivity for human-AI collaboration and improve the user experience. However, several challenges still exist in implementing this approach, including the need for more robust models, designing effective user interfaces, and ensuring ethical considerations are addressed.
This workshop aims to bring together researchers and practitioners from academia and industry to explore the cutting-edge AI technologies for personalized education, especially the potential of LLMs and adaptive learning technologies. The objectives of the workshop are to: 1. Review the current state-of-the-art in LLM-based systems and their applications in education. 2. Identify challenges and opportunities in using LLMs as both communication and collaboration interfaces in adaptive learning systems, educational games and intelligent educational assistant. 3. Discuss the potential of LLMs in improving human-computer interaction (HCI) and user experience in educational settings. 4. Discuss the state-of-the-art technologies of adaptive learning that tailor education to the individual needs, learning styles, proficiency levels, and problem areas of each student, for personalized learning experience. 5. Explore ethical considerations and standardization issues in the use of LLMs, especially with IEEE AI Standards Committee and IEEE Learning Technology Standards Committee. 6. Introduce and design new implementation approaches such as prompt engineering, local fine tuning, integrated reasoning, and delegation framework for dialog-based systems that use natural language to not only to generate content but also shape the behavior of the system.
This workshop encourages submissions of innovative solutions for a broad range of AI for Education problems. Topics of interest include but are not limited to the following:
We invite high-quality paper submissions of theoretical and experimental nature on the broad AI4EDU topics. The workshop solicits 5-7 pages double-blind paper submissions following CAI 2024 template from participants. All submissions will be peer-reviewed. Submissions of the following flavors will be sought: (1) research ideas, (2) case studies (or deployed projects), (3) review papers, (4) best practice papers, and (5) lessons learned. An optional appendix of arbitrary length is allowed and should be put at the end of the paper (after references).
Accepted papers will be presented as posters during the workshop and list on the website (non-archival/without proceedings). Besides, a small number of accepted papers will be selected to be presented as contributed talks.
Submission link: https://cmt3.research.microsoft.com/AI4EDUCAI2024
Any questions may be directed to the workshop e-mail address: Contact Us
Workshop Paper Submission Due Date: May 15, 2024(AoE)
Notification of Paper Acceptance: May 22, 2024
Camera-ready Papers Due: May 30, 2024
CAI-24 Workshops: June 25, 2024
| Time(GMT+8) | Title | Speaker |
|---|---|---|
| 8:45 am - 9:00 am | Opening Remarks | |
| 9:00 am - 9:30 am | Coffee Break | |
| 9:30 am - 10:30 am | Keynote Talk | |
| 10:30 am – 12:00 pm | Contributed oral talks | |
| 12:00pm – 1: 30 pm | Lunch Break | |
| 1:30 pm - 2:30 pm | Keynote Talk | |
| 2:30 pm – 3:30 pm | Poster Session | |
| 3:30pm – 4:00pm | Coffee Break | |
| 4:15pm – 5:00pm | Panel Discussion | |
| 5:00pm – 5:10pm | Closing Remark |
Abstract: xxx.
Short Bio:
XXX is a Professor at XX .
Oral Paper Title Author list.
Poster Paper Title Author list.
Head of AI Research & Chief Scientist
Squirrel Ai Learning
Contact: qingsongwen@squirrelai.com
Short Bio: Qingsong Wen is the Head of AI Research & Chief Scientist at Squirrel Ai Learning by Yixue Education Inc., working in EdTech area via AI technologies. Before that, he worked at Alibaba, Futurewei, Qualcomm, and Marvell, and received his M.S. and Ph.D. degrees in Electrical and Computer Engineering from Georgia Institute of Technology, USA. His research interests include machine learning and decision intelligence, especially AI for Time Series (AI4TS) & AI for Education (AI4EDU). He has published around 100 top-ranked AI conference and journal papers, had multiple Oral/Spotlight Papers at NeurIPS/ICLR, had multiple Most Influential Papers at IJCAI, received multiple IAAI Deployed Application Awards at AAAI, and won First Place of SP Grand Challenge at ICASSP. Currently, he serves as Organizer/Co-Chair of Workshop on AI for Time Series (AI4TS @ KDD, ICDM, SDM, AAAI, IJCAI) and Workshop on AI for Education (AI4EDU @ CAI). He also serves as Associate Editor for Neurocomputing, Guest Editor for IEEE Internet of Things Journal, and Guest Editor for Applied Energy. In addition, he has regularly served as Area Chair/(S)PC of the AI conferences including KDD, AAAI, IJCAI, ICDM, ICASSP, etc.
Short Bio: Joleen Liang is the Co-Founder of Squirrel Ai Learning. She is Visiting Professor at the Research Institute for Innovation and Technology in Education (UNIR iTED), the Secretary of the IEEE International K-12 Education Knowledge Graph Standards Working Group, the Vice-Dean of Intelligent Education Committee of China Automation Congress, the Deputy Head of the Technology and Standards Working Group, the Smart Education Working Committee of the Internet Society of China, and the Executive Director of the Artificial Intelligence and Robotics Education Committee of the China Education Development Strategy Society. She received her Ph.D in Intelligent Science and Systems at Macau University of Science and Technology. In 2020, she and Squirrel Ai was honored ‘AI Education Innovation Award’by UNESCO. She is also the founder/director of AI+Adaptive Education International Conference (AIAED) focusing on important trends emerging from AI-tech applied to next-generation education and how these advances can impact adaptive human learning at scale. The 1st-4th AIAED invited more 200 AI and AI education speakers (scientists and companies) internationally, and 10000+audiences, 500+ investors, 1000+ CEOs, 200+ media.
Short Bio: Richard Tong is currently the Chief Architect of Squirrel Ai Learning. Prior that, he was the Principal Architect of Carnegie Learning, the Head of Implementation at Greater China Region for Knewton, and the Director of Solution Architecture for Amplify Education. He also served as the CTO of Phoenix New Media. He serves as the Chair of IEEE Artificial Intelligence Standards Committee. He is an experienced technologist, executive, entrepreneur and one of the leading evangelists for standardization effort for global education technology and AI in education.
Short Bio: Yu LU received the Ph.D. from National University of Singapore in computer engineering. He is currently an Associate Professor with the School of Educational Technology, Faculty of Education, Beijing Normal University (BNU), where he also serves as the director of AI Lab at the advanced innovation center for future education (AICFE). He has published more than 90 academic papers in the prestigious venues, and serves as the associate editor for multiple academic journals, such as IEEE Transactions on Learning Technologies. He also serves as PC member or track chair for multiple international conferences (e.g., AIED, EDM, AAAI, ACL, EMNLP, IJCAI, ICCE, GCCCE). Before joining BNU, he was a research scientist and principle investigator at the Institute for Infocomm Research (I2R), A*STAR, Singapore. His research interests mainly sit at the intersection field of artificial intelligence and education.
Short Bio: Liu Guimei is currently a Principal Scientist and Principal Investigator at Institute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR), Singapore. She received her PhD in Computer Science from Hong Kong University of Science and Technology (HKUST). She has published 40+ papers at data mining/AI/Bioinformatics conferences and journals. Her current research interests are mainly on learning analytics and adaptive learning.
Short Bio: Xiangen Hu is a professor in the Department of Psychology, Department of Electrical and Computer Engineering and Computer Science Department at The University of Memphis (UofM) and senior researcher at the Institute for Intelligent Systems (IIS) at the UofM and is professor and Dean of the School of Psychology at Central China Normal University (CCNU). Dr. Hu received his MS in applied mathematics from Huazhong University of Science and Technology, MA in social sciences and Ph.D. in Cognitive Sciences from the University of California, Irvine. Dr. Hu is the Director of Advanced Distributed Learning (ADL) Partnership Laboratory at the UofM, and is a senior researcher in the Chinese Ministry of Education’s Key Laboratory of Adolescent Cyberpsychology and Behavior.
Chief Science Officer & Co-Founder
Eduworks Corporation
Contact: robby.robson@eduworks.com
Short Bio: Robby Robson is a researcher, entrepreneur, and standards professional known for creative and disruptive innovation in industry and academia. He is a co-founder of Eduworks Corporation where he was CEO for 20 years and where he currently serves as Chief Science Officer and Board Chair. His focus at Eduworks is on developing transformative tools for competency-based talent management and workforce development. As a volunteer, Robby serves on multiple IEEE boards and committees in the areas of Standards, Open Source, and Educational Activities.
