AAAI2021
Web-based Platform for K-12 AI Education in China
Chao Wu, Yan Li, Junxiang Li, Qiongdan Zhang, Fei Wu
13 citations
Abstract
As human beings are entering the era in which AI becomes the new engine to drive social, economic, and scientific advancement, education is intensively being required to adapt to this trend, to equip current and next-generation with the necessary knowledge, skills, and thinking. Although AI education has achieved relative success in universities and cultivated a large number of talents and companies in the past decade, it hasn't made significant progress in K-12 education. We identify the key challenges as two gaps, one is about transferring practice from university education to K-12 education, and the other is about the inequal distribution of AI educational resources. To fill these gaps and to efficiently facilitate K-12 AI education, especially in countries like China, we designed and implemented a web-based platform, which as a focal and sharing point of K-12 educational resources to provide essential AI learning and exercising components to both students and instructors. With this platform, we've successfully conducted a series of initial trials and gained positive feedbacks. We believe a wider-range of applications of the platform will achieve promising results for K-12 AI education.