可访问但未被采纳：超越扩大访问以提升第一代低收入（FGLI）大学生对LLM的采纳
Accessible, but Not Adopted: Increasing LLM Adoption among First-generation, Low-income (FGLI) College Students beyond Expanding Access
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中文总结 AI 辅助
本研究基于61次访谈，揭示FGLI大学生LLM采纳深度不足的障碍，提出四项设计原则，并将采纳重新定义为四种使用模式的深度梯度。
中文摘要 AI 辅助
大型语言模型（LLM）日益被定位为赋能弱势群体的力量，并且正在做出重大努力以扩大其访问范围。然而，仅凭访问并不等同于有意义的采纳。首先，即使一个系统是可访问的，如果用户不愿意采纳，它也不会被采纳。其次，即使一个LLM系统表面上被采纳，LLM工具的异质性意味着LLM采纳可以进一步深化。缩小这种访问-采纳差距对于确保LLM的全部社会潜力不仅可访问而且得到充分实现至关重要。基于61次访谈（15次与第一代低收入（FGLI）大学生进行的长时间半结构化访谈、3次与非FGLI学生的访谈、3次与FGLI项目主任的访谈以及40次拦截式访谈），本文考察了第一代低收入学生群体中的访问-采纳差距。本文a)发现，尽管FGLI学生已采纳LLM系统，但其LLM工具使用深度仅限于聊天机器人（如ChatGPT或Claude）的狭窄用例，并且b)识别出限制他们学习和使用意愿的障碍（感知价值低、自我效能感被低估、起点不明确、同伴接触少以及资源限制）。随后，基于这些发现，本文推导出四项设计原则，用于设计旨在缩小FGLI学生在LLM采纳中访问-采纳差距的系统或干预措施。通过这样做，本文通过a)考察FGLI学生群体中的LLM访问-采纳差距，以及b)将LLM采纳重新定义为跨四种LLM工具使用模式的深度梯度：基本聊天机器人界面、工具增强的预构建界面、智能体开发界面和编程式集成，为该领域做出贡献。
英文摘要
Large language models (LLMs) are increasingly positioned as a force to empower underserved communities, and significant efforts are being made to expand access. Yet, access alone does not equate to meaningful adoption. First, even if a system is accessible, it won't be adopted if users are not willing to adopt it. Second, even if an LLM system is superficially adopted, the heterogeneity of LLM tools means that LLM adoption can be further deepened. Closing this access-adoption gap is critical to ensuring that the full social potential of LLM is not only accessible but fully realised. Drawing on 61 interviews (15 long-form semi-structured interviews with first-generation, low-income college (FGLI) students, 3 non-FGLI students, 3 FGLI program directors, and 40 intercept interviews), this paper examines the access-adoption gap in first-generation, low-income student communities. This paper a) finds that while FGLI students have adopted LLM systems, their depth of LLM tool usage is limited to chatbots (e.g., ChatGPT or Claude) for narrow use cases, and b) identifies barriers limiting their willingness to learn and use (low perceived value, under-estimated self-efficacy, unclear starting point, low peer exposure, and resource constraints). Then, from these findings, the paper derives the four design principles to design a system or an intervention aimed at closing the access-adoption gap in LLM adoption by FGLI students. In doing so, the paper contributes to the field by a) examining the LLM access-adoption gap in the FGLI student community, and b) reframing LLM adoption as a depth gradient across four modes of LLM tool use: basic chatbot interfaces, tool-augmented prebuilt interfaces, agentic development interfaces, and programmatic integration.
发表机构
- Harvard University（哈佛大学）
机构由 AI 辅助整理，请以论文原文为准。
