表征学生在批判性思维任务中的LLM使用行为及其与学习的关联
Characterizing Students' LLM Usage Behaviors and Their Association with Learning in Critical Thinking Tasks
AI总结：
通过分析研究型课程中学生在无限制条件下使用LLM完成学术论文阅读与批判任务的行为数据，提出基于学生主动性的LLM使用类型分类，并考察使用频率和类型对期中考试成绩的影响。
摘要：
大型语言模型（LLM）正日益嵌入学生的学习实践中，但目前关于学生如何使用LLM以及这种使用如何影响学习的认知主要来自问题解决领域或受控实验环境。我们分析了在一门研究导向课程的两个学期中收集的LLM使用数据，该课程中学生学习阅读、推理和评论学术论文。在没有限制是否或如何使用LLM的情况下，学生在完成一系列课程作业时报告了他们的LLM使用实践。本文通过提出基于学生主动性程度的LLM使用类型的精细自下而上分类，扩展了先前基于同一课程单个学期数据的工作。此外，我们通过三次期中考试的表现来衡量LLM使用对学生学习的影响，考察了使用频率和类型等因素。
英文摘要：
Large language models (LLMs) are becoming increasingly embedded in students' learning practices, yet much of what is known about how students use LLMs and how this usage impacts learning comes from problem-solving domains or constrained experimental settings. We present an analysis of data on LLM usage collected during two offerings of a research-oriented course where students learn to read, reason about, and critique academic papers. Without restrictions on whether or how to use LLMs, students reported their LLM usage practices when asked to do these activities as a series of homework assignments during the course. This paper extends prior work done on data from a single offering of the same course by presenting a refined bottom-up categorization of LLM usage types, cross-labeled by the extent of student initiative these usages entail. Furthermore, we examine how LLM use impacts student learning, measured by performance on three midterms, looking at factors such as frequency and type of usage.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
