AI 中文总结
该研究通过194人参与的众包实验，对比传统搜索与LLM聊天界面对学习有争议话题的影响，发现工具无显著差异，用户特征对学习结果影响更大。
AI 中文摘要
随着大型语言模型（LLMs）越来越多地融入日常信息平台，基于聊天的系统正成为传统网络搜索的热门替代方案，尤其适用于信息搜索和非正式学习任务。尽管出现了这种转变，但人们对不同工具如何影响学习结果知之甚少。本研究旨在加深对基于聊天的信息访问在非正式学习场景中如何支持和影响学习表现的理解。本文呈现了一项众包用户研究（N=194）的结果，该研究对比了使用传统搜索界面与基于LLM的聊天界面了解有争议话题的效果。通过对学习结果、用户特征和交互模式的分析，我们发现用户的学习增益或对研究任务的批判性反思方面不存在显著差异。我们对进一步探索变量的分析观察表明，在长期存在的有争议话题的背景下，用户特征（如态度强度和智力谦逊程度）可能比信息访问工具对即时学习结果的影响更大。
英文摘要
As large language models (LLMs) become more integrated into everyday information platforms, chat-based systems are emerging as a popular alternative to traditional web searches, especially for informational search and informal learning tasks. Despite this shift, little is known about how different tools affect learning outcomes. Our work aims to improve the understanding of how chat-based information access supports and impacts learning performance in informal learning settings. In this paper, we present the results of a crowdsourcing user study (N = 194) that compares learning about debated topics using a traditional search interface versus an LLM-powered chat interface. Through our analysis of learning outcomes, user characteristics, and interaction patterns, we found no significant differences in user learning gain or critical reflection on our study tasks. Our observations from the analysis of further exploratory variables suggest that, in the context of longstanding debated topics, user characteristics such as their attitude strength and level of intellectual humility might be more important in shaping immediate learning outcomes than the information access tool.
