Scientific and Fantastical: Creating Immersive, Culturally Relevant Learning Experiences with Augmented Reality and Large Language Models

要旨

Motivating children to learn is a major challenge in education. One way to inspire motivation to learn is through immersion. We combine the immersive potential of augmented reality (AR), narrative, and large language models (LLMs) to bridge fantasy with reality in a mobile application, Moon Story, that teaches elementary schoolers astronomy and environmental science. Our system also builds upon learning theories such as culturally-relevant pedagogy. Using our application, a child embarks on a journey inspired by Chinese mythology, engages in real-world AR activities, and converses with a fictional character powered by a LLM. We conducted a controlled experiment (N=50) with two conditions: one using an LLM and one that was hard-coded. Both conditions resulted in learning gains, high engagement levels, and increased science learning motivation. Participants in the LLM condition also wrote more relevant answers. Finally, participants of both Chinese and non-Chinese heritage found the culturally-based narrative compelling.

著者
Alan Y.. Cheng
Stanford University, Stanford, California, United States
Meng Guo
Stanford University, Stanford, California, United States
Melissa Ran
Stanford University, Stanford, California, United States
Arpit Ranasaria
Stanford University, Stanford, California, United States
Arjun Sharma
Stanford University, Stanford, California, United States
Anthony Xie
Stanford University, Stanford, California, United States
Khuyen N.. Le
University of California, San Diego, La Jolla, California, United States
Bala Vinaithirthan
Stanford University, Stanford, California, United States
Shihe (Tracy) Luan
Stanford University, Stanford, California, United States
David Thomas Henry. Wright
Nagoya University, Nagoya, Aichi, Japan
Andrea Cuadra
Stanford University, Stanford, California, United States
Roy Pea
Stanford University, Stanford, California, United States
James A.. Landay
Stanford University, Stanford, California, United States
論文URL

https://doi.org/10.1145/3613904.3642041

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Education and AI B

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5 件の発表
2024-05-15 23:00:00
2024-05-16 00:20:00