中文标题#
探索在增强型 LLM 环境中的学习紧张感：一种以学生为中心的 LLM 与搜索的定性视角
英文标题#
Exploring undercurrents of learning tensions in an LLM-enhanced landscape: A student-centered qualitative perspective on LLM vs Search
中文摘要#
大型语言模型（LLMs）正在改变学生的学习方式，通过提供易于获取的工具，这些工具可以快速增强或完成各种学习活动，并表现出非平凡的性能。 过去引入搜索引擎和维基百科时也发生了类似的范式转变，它们取代或补充了传统的信息来源，如图书馆和书籍。 本研究探讨了 LLMs 作为学习领域下一次转变的潜力，重点比较了它们在信息发现和综合方面与现有技术（如搜索引擎）的作用。 采用组内、平衡设计，参与者使用搜索引擎（Google）和大型语言模型（ChatGPT）学习新主题。 任务后的访谈探讨了学生们的反思、偏好、痛点和总体看法。 我们呈现了他们的回答分析，揭示了学生在何时、为什么以及如何更喜欢 LLMs 而非搜索引擎的细致见解，为教育工作者、政策制定者和技术开发者在不断变化的教育环境中提供了启示。
英文摘要#
Large language models (LLMs) are transforming how students learn by providing readily available tools that can quickly augment or complete various learning activities with non-trivial performance. Similar paradigm shifts have occurred in the past with the introduction of search engines and Wikipedia, which replaced or supplemented traditional information sources such as libraries and books. This study investigates the potential for LLMs to represent the next shift in learning, focusing on their role in information discovery and synthesis compared to existing technologies, such as search engines. Using a within-subjects, counterbalanced design, participants learned new topics using a search engine (Google) and an LLM (ChatGPT). Post-task follow-up interviews explored students' reflections, preferences, pain points, and overall perceptions. We present analysis of their responses that show nuanced insights into when, why, and how students prefer LLMs over search engines, offering implications for educators, policymakers, and technology developers navigating the evolving educational landscape.
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