CLHCFeb 26, 2024

Leveraging Large Language Models for Learning Complex Legal Concepts through Storytelling

AI2
arXiv:2402.17019v442 citationsh-index: 17ACL
Originality Incremental advance
AI Analysis

This work addresses the challenge of legal literacy for non-experts, particularly non-native speakers, by applying LLMs to education, though it is incremental as it adapts existing LLM methods to a new domain.

The paper tackled the problem of making legal knowledge accessible to non-experts by using large language models (LLMs) to generate stories for learning complex legal concepts, finding that LLM-generated stories enhanced comprehension and interest, with higher retention rates for non-native speakers in follow-up assessments.

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 294 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 approach to iteratively design multiple-choice questions. Then, we evaluate the effectiveness of storytelling with LLMs through randomized controlled trials (RCTs) 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.

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