Making legal knowledge accessible to non-experts is crucial for enhancing
general legal literacy and encouraging civic participation in democracy.
However, legal documents are often challenging to understand for people without
legal backgrounds. In this paper, we present a novel application of large
language models (LLMs) in legal education to help non-experts learn intricate
legal concepts through storytelling, an effective pedagogical tool in conveying
complex and abstract concepts. We also introduce a new dataset LegalStories,
which consists of 295 complex legal doctrines, each accompanied by a story and
a set of multiple-choice questions generated by LLMs. To construct the dataset,
we experiment with various LLMs to generate legal stories explaining these
concepts. Furthermore, we use an expert-in-the-loop method to iteratively
design multiple-choice questions. Then, we evaluate the effectiveness of
storytelling with LLMs through an RCT experiment with legal novices on 10
samples from the dataset. We find that LLM-generated stories enhance
comprehension of legal concepts and interest in law among non-native speakers
compared to only definitions. Moreover, stories consistently help participants
relate legal concepts to their lives. Finally, we find that learning with
stories shows a higher retention rate for non-native speakers in the follow-up
assessment. Our work has strong implications for using LLMs in promoting
teaching and learning in the legal field and beyond.

将大型语言模型应用于法律教育，通过讲故事的方式帮助非专家了解复杂的法律概念，发现这种方法能够提高对法律概念的理解和对法律的兴趣，并具有较高的保留率，对法律领域以及其他领域的教学和学习具有重要意义。