AI for Social Good Education at Hispanic Serving Institutions

Yu Chen, Gabriel Granco, Yunfei Hou, Heather Macias, Frank A. Gomez
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Abstract

This project aims to broaden AI education by developing and studying the efficacy of innovative learning practices and resources for AI education for social good. We have developed three AI learning modules for students to: 1) identify social issues that align with the SDGs in their community (e.g., poverty, hunger, quality education); 2) learn AI through hands-on labs and business applications; and 3) create AI-powered solutions in teams to address social is-sues they have identified. Student teams are expected to situate AI learning in their communities and contribute to their communities. Students then use the modules to en-gage in an interdisciplinary approach, facilitating AI learn-ing for social good in informational sciences and technology, geography, and computer science at three CSU HSIs (San Jose State University, Cal Poly Pomona and CSU San Bernardino). Finally, we aim to evaluate the efficacy and impact of the proposed AI teaching methods and activities in terms of learning outcomes, student experience, student engagement, and equity.
西语裔服务机构的人工智能社会公益教育
本项目旨在通过开发和研究人工智能教育创新学习实践和资源的功效,扩大人工智能教育的社会公益性。我们为学生开发了三个人工智能学习模块,以便1)确定其所在社区与可持续发展目标相一致的社会问题(如贫困、饥饿、优质教育);2)通过实践实验室和商业应用学习人工智能;3)以团队形式创建人工智能驱动的解决方案,以解决他们所确定的社会问题。学生团队应将人工智能学习融入其所在社区,并为社区做出贡献。然后,学生利用这些模块参与跨学科方法,在三所 CSU HSI(圣何塞州立大学、加州理工波莫纳分校和 CSU 圣贝纳迪诺分校)的信息科学与技术、地理学和计算机科学领域促进人工智能学习,以造福社会。最后,我们将从学习成果、学生体验、学生参与度和公平性等方面评估所提出的人工智能教学方法和活动的效果和影响。
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