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Creators/Authors contains: "Macias, Heather"

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  1. Free, publicly-accessible full text available January 1, 2026
  2. 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. 
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  3. While implementing with caution, Artificial Intelligence (AI) holds potential to help nations address pressing social issues, such as homelessness, climate change, and healthcare accessibility. With the existing and potential economic and social benefits of AI, it is crucial to integrate AI learning in undergraduate education. This paper presents the preliminary findings of a course project that engages students to learn AI by prototyping solutions to address important social issues in their communities among 120 undergraduate MIS students. Students worked in groups and developed chatbots that addressed a variety of community issues during COVID-19. A survey study shows students’ enhanced understanding and mastery of AI concepts and applications, empowerment of contributing to their communities through AI innovation, and an emerging awareness of diversity, equity, and ethical issues in the community and AI technologies. We conclude with implications of learning AI, innovation, and ethics through the lens of AI for social good. 
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