The increased presence of large language models (LLMs) in educational settings has ignited debates concerning negative repercussions, including overreliance and inadequate task reflection. Our work advocates moderated usage of such models, designed in a way that supports students and encourages critical thinking. We developed two moderated interaction methods with ChatGPT: hint-based assistance and presenting multiple answer choices. In a study with students (N=40) answering physics questions, we compared the effects of our moderated models against two baseline settings: unmoderated ChatGPT access and internet searches. We analyzed the interaction strategies and found that the moderated versions exhibited less unreflected usage (e.g., copy \& paste) compared to the unmoderated condition. However, neither ChatGPT-supported condition could match the ratio of reflected usage present in internet searches. Our research highlights the potential benefits of moderating language models, showing a research direction toward designing effective AI-supported educational strategies.

翻译：大型语言模型在教育领域的日益普及引发了关于其负面影响的讨论，包括过度依赖和任务反思不足等问题。本研究倡导对这些模型进行适度使用，设计旨在支持学生并促进批判性思维的方法。我们开发了与ChatGPT交互的两种适度调节方法：基于提示的辅助和提供多种答案选项。在40名学生回答物理问题的研究中，我们将适度调节模型的效果与两种基线设置（无限制ChatGPT访问和互联网搜索）进行了对比。通过分析交互策略，我们发现与无限制条件相比，适度调节版本表现出更少的非反思性使用行为（例如复制粘贴）。然而，两种ChatGPT支持条件均未能达到互联网搜索中反思性使用比例的水平。本研究强调了调节语言模型的潜在优势，为设计有效的AI辅助教育策略指明了研究方向。