TY - GEN
T1 - Towards the Future of AI-Augmented Human Tutoring in Math Learning
AU - Aleven, Vincent
AU - Baraniuk, Richard
AU - Brunskill, Emma
AU - Crossley, Scott
AU - Demszky, Dora
AU - Fancsali, Stephen
AU - Gupta, Shivang
AU - Koedinger, Kenneth
AU - Piech, Chris
AU - Ritter, Steve
AU - Thomas, Danielle R.
AU - Woodhead, Simon
AU - Xing, Wanli
N1 - Funding Information:
Emma is an Associate Professor in the Computer Science Department at Stanford University where she aims to create AI systems that learn from a few samples to robustly make good decisions. Her work is inspired by the positive impact AI may have in education and healthcare, with interests in large language models to advance AI-assisted human tutoring. Emma is part of the Stanford AI Lab, the Stanford Statistical ML group, and AI Safety @Stanford. She has received an NSF CAREER award, Office of Naval Research Young Investigator Award, and many other awards. Emma and her lab have received multiple best paper nominations for their AI and machine learning work.
Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023
Y1 - 2023
N2 - One of the primary obstacles to improving middle school math achievement is lack of equitable access to high-quality learning opportunities. Human delivery of high-dosage tutoring can bring significant learning gains, but students, particularly economically disadvantaged students, have limited access to well-trained tutors. Augmenting human tutor abilities through the use of artificial intelligence (AI) technology is one way to scale up access to tutors without compromising learning quality. This workshop aims to highlight the challenges and opportunities of AI-in-the-loop math tutoring and encourage discourse in the AIED community to develop human-AI hybrid tutoring and teaching systems. We invite papers that provide clearer understanding and support the progress of human and AI-assisted personalized learning technologies. The structure of this full-day hybrid workshop will include presentations of accepted papers, small or whole group discussion, and a panel discussion focusing on common themes related to research and application, key takeaways, and findings imperative to increasing middle school math learning.
AB - One of the primary obstacles to improving middle school math achievement is lack of equitable access to high-quality learning opportunities. Human delivery of high-dosage tutoring can bring significant learning gains, but students, particularly economically disadvantaged students, have limited access to well-trained tutors. Augmenting human tutor abilities through the use of artificial intelligence (AI) technology is one way to scale up access to tutors without compromising learning quality. This workshop aims to highlight the challenges and opportunities of AI-in-the-loop math tutoring and encourage discourse in the AIED community to develop human-AI hybrid tutoring and teaching systems. We invite papers that provide clearer understanding and support the progress of human and AI-assisted personalized learning technologies. The structure of this full-day hybrid workshop will include presentations of accepted papers, small or whole group discussion, and a panel discussion focusing on common themes related to research and application, key takeaways, and findings imperative to increasing middle school math learning.
KW - AI-assisted tutoring
KW - Personalized learning
KW - Tutoring
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U2 - 10.1007/978-3-031-36336-8_3
DO - 10.1007/978-3-031-36336-8_3
M3 - Conference contribution
AN - SCOPUS:85164926207
SN - 9783031363351
T3 - Communications in Computer and Information Science
SP - 26
EP - 31
BT - Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky - 24th International Conference, AIED 2023, Proceedings
A2 - Wang, Ning
A2 - Rebolledo-Mendez, Genaro
A2 - Dimitrova, Vania
A2 - Matsuda, Noboru
A2 - Santos, Olga C.
PB - Springer Science and Business Media Deutschland GmbH
T2 - 24th International Conference on Artificial Intelligence in Education , AIED 2023
Y2 - 3 July 2023 through 7 July 2023
ER -