mlsanityData to 7 Oct 2026

Leveraging Large Language Models for Learning Complex Legal Concepts through Storytelling

arXiv 2402.17019 ↗First posted 26 Feb 2024cs.CL cs.HCcited by 23

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Abstract (arXiv)

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.

Key facts. Cited by 23 papers in the map (data through 7 Oct 2026). Builds on 24 of its 90 references that are in the map. First posted on arXiv 26 Feb 2024.

Builds on

24 of 90 references.

References · 24

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2020UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Trainingcited by 204
  3. 2019JEC-QA: A Legal-Domain Question Answering Datasetcited by 115
  4. 2017Neural Question Generation from Text: A Preliminary Studycited by 78
  5. 2018What Makes Reading Comprehension Questions Easier?cited by 59
  6. 2023The Next Chapter: A Study of Large Language Models in Storytellingcited by 58
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  11. 2021Automatic Story Generation: Challenges and Attemptscited by 28
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12 more
  1. 2021Question Generation for Adaptive Educationcited by 22
  2. 2023Prompting Large Language Models with Chain-of-Thought for Few-Shot Knowledge Base Question Generationcited by 21
  3. 2022Question Generation for Reading Comprehension Assessment by Modeling How and What to Askcited by 20
  4. 2019Question-type Driven Question Generationcited by 16
  5. 2020QURIOUS: Question Generation Pretraining for Text Generationcited by 12
  6. 2022Quiz Design Task: Helping Teachers Create Quizzes with Automated Question Generationcited by 12
  7. 2022ACCoRD: A Multi-Document Approach to Generating Diverse Descriptions of Scientific Conceptscited by 10
  8. 2023The Law and NLP: Bridging Disciplinary Disconnectscited by 8
  9. 2021I Do Not Understand What I Cannot Define: Automatic Question Generation With Pedagogically-Driven Content Selectioncited by 7
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  11. 2023On the Automatic Generation and Simplification of Children's Storiescited by 4
  12. 2022Unsupervised Simplification of Legal Textscited by 3

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Citing papers per year: 2024: 8; 2025: 12; 2026: 3.

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  2. 2024CLERC: A Dataset for Legal Case Retrieval and Retrieval-Augmented Analysis Generationcited by 18
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  6. 2025Savaal: Scalable Concept-Driven Question Generation to Enhance Human Learningcited by 7
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  8. 2024Benchmarking Cognitive Domains for LLMs: Insights from Taiwanese Hakka Culturecited by 6
  9. 2025When Style Breaks Safety: Defending LLMs Against Superficial Style Alignmentcited by 6
  10. 2025CoCoLex: Confidence-guided Copy-based Decoding for Grounded Legal Text Generationcited by 6
  11. 2025Automating Legal Interpretation with LLMs: Retrieval, Generation, and Evaluationcited by 5
  12. 2024SS-GEN: A Social Story Generation Framework with Large Language Modelscited by 4
11 more
  1. 2024Exploring Possibilities of AI-Powered Legal Assistance in Bangladesh through Large Language Modelingcited by 3
  2. 2026Narrative Theory-Driven LLM Methods for Automatic Story Generation and Understanding: A Surveycited by 3
  3. 2025Long Story Generation via Knowledge Graph and Literary Theorycited by 1
  4. 2025Can Large Language Models Integrate Spatial Data? Empirical Insights into Reasoning Strengths and Computational Weaknessescited by 1
  5. 2025Human-AI Narrative Synthesis to Foster Shared Understanding in Civic Decision-Makingcited by 1
  6. 2025From Answers to Guidance: A Proactive Dialogue System for Legal Documentscited by 1
  7. 2026Gender Bias in LLMs: Preliminary Evidence from Shared Parenting Scenario in Czech Family Lawcited by 1
  8. 2026CLASE: A Hybrid Method for Chinese Legalese Stylistic Evaluationcited by 1
  9. 2024Bridging Context Gaps: Enhancing Comprehension in Long-Form Social Conversations Through Contextualized Excerptscited by 0
  10. 2025Nyay-Darpan: Enhancing Decision Making Through Summarization and Case Retrieval for Consumer Law in Indiacited by 0
  11. 2025Evaluating Cultural Knowledge Processing in Large Language Models: A Cognitive Benchmarking Framework Integrating Retrieval-Augmented Generationcited by 0