Many users struggle with effective online search and critical evaluation, especially in high-stakes domains like health, while often overestimating their digital literacy. Thus, in this demo, we present an interactive search companion that seamlessly integrates expert search strategies into existing search engine result pages. Providing context-aware tips on clarifying information needs, improving query formulation, encouraging result exploration, and mitigating biases, our companion aims to foster reflective search behaviour while minimising cognitive burden. A user study demonstrates the companion's successful encouragement of more active and exploratory search, leading users to submit 75 % more queries and view roughly twice as many results, as well as performance gains in difficult tasks. This demo illustrates how lightweight, contextual guidance can enhance search literacy and empower users through micro-learning opportunities. While the vision involves real-time LLM adaptivity, this study utilises a controlled implementation to test the underlying intervention strategies.

翻译：许多用户在在线搜索与批判性评估方面存在困难，尤其是在健康等高风险领域，同时往往高估自身的数字素养。为此，本演示展示了一款交互式搜索伴侣，其将专家搜索策略无缝整合至现有搜索引擎结果页面。通过提供情境感知提示——包括澄清信息需求、改进查询构建、鼓励结果探索以及减轻认知偏差——我们的伴侣旨在培养反思性搜索行为，同时最大限度地减轻认知负担。一项用户研究表明，该伴侣成功鼓励了更主动和探索性的搜索行为，使用户提交的查询数量增加了75%，浏览的结果数量约为原来的两倍，并在困难任务中实现了性能提升。本演示说明了轻量级、情境化的引导如何通过微学习机会提升搜索素养并赋能用户。尽管长远愿景涉及实时大型语言模型的自适应能力，但本研究采用受控实施方案来测试基础的干预策略。