AI Literacy for Underserved Students: Leveraging Cultural Capital from Underserved Communities for AI Education Research

要旨

As Artificial Intelligence (AI) continues to influence various aspects of society, the need for AI literacy education for K-12 students has grown. An increasing number of AI literacy studies aim to enhance students' competencies in understanding, using, and critically evaluating AI systems. However, despite the vulnerabilities faced by students from underserved communities—due to factors such as socioeconomic status, gender, and race—these students remain underrepresented in existing research. To address this gap, this study focuses on leveraging the cultural capital that students acquire from their communities’ unique history and culture for AI literacy education. Education researchers have demonstrated that identifying and mobilizing cultural capital is an effective strategy for educating these populations. Through collaboration with 26 students from underserved communities—including those who are socioeconomically disadvantaged, female, or people of color—this paper identifies three types of cultural capital relevant to AI literacy education: 1) resistant capital, 2) communal capital, and 3) creative capital. The study also emphasizes that collaborative relationships between researchers and students are crucial for mobilizing cultural capital in AI literacy education research.

著者
Huajie Cao
Michigan State University, East Lansing, Michigan, United States
Kahyun Choi
University of Illinois at Urbana-Champaign, Champaign, Illinois, United States
Claire Park
Chippewa Middle School, Okemos, Michigan, United States
Hee Rin Lee
Michigan State University, East Lansing, Michigan, United States
DOI

10.1145/3706598.3713173

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713173

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Tech and AI Literacy

G416+G417
7 件の発表
2025-04-29 18:00:00
2025-04-29 19:30:00
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