A Contextual Help Browser Extension to Assist Digital Illiterate Internet Users
AI 摘要
设计并评估了一个浏览器扩展,利用AI为数字素养低的用户提供技术术语的上下文帮助。
主要贡献
- 开发了基于AI的上下文帮助浏览器扩展
- 验证了该扩展能有效提高阅读理解和信息检索效率
- 证明了此方法可以扩展到其他领域
方法论
结合技术词典和LLM,通过双层AI管线进行页面分类,并在用户悬停时提供工具提示。进行了混合方法的用户研究。
原文摘要
This paper describes the design, implementation, and evaluation of a browser extension that provides contextual help to users who hover over technological acronyms and abbreviations on web pages. The extension combines a curated technical dictionary with OpenAI's large language model (LLM) to deliver on-demand definitions through lightweight tooltip overlays. A dual-layer artificial intelligence (AI) pipeline, comprising Google Cloud's Natural Language Processing (NLP) taxonomy API and OpenAI's ChatGPT, classifies each visited page as technology-related before activating the tooltip logic, thereby reducing false-positive detections. A mixed-methods study with 25 participants evaluated the tool's effect on reading comprehension and information-retrieval time among users with low to intermediate digital literacy. Results show that 92% of participants reported improved understanding of technical terms, 96% confirmed time savings over manual web searches, and all participants found the tooltips non-disruptive. Dictionary-based definitions were appended in an average of 2135 ms, compared to 16429 ms for AI-generated definitions and a mean manual search time of 17200 ms per acronym. The work demonstrates a practical, real-time approach to bridging the digital literacy gap and points toward extending contextual help to other domains such as medicine, law, and finance.