Paper Number
ICIS2025-1558
Paper Type
Complete
Abstract
Legal literacy has become a key competency in both professional and everyday contexts. Individuals are increasingly required to understand legal principles, whether managing business contracts, interpreting policies, or ensuring regulatory compliance. As part of this broader competence, the ability to understand and write clear and well-structured legal texts is essential. Many students, however, find legal writing challenging because of its complex reasoning and formal conventions. To address this, we present CaseCoach, an intelligent tutoring system based on large language models (LLMs) that supports students in solving complex legal problems through conversational tutoring. Using a design science research approach, we first derived system requirements through interviews with 14 law students. We then evaluated CaseCoach’s effectiveness in a quantitative study involving 40 business and law students. Our research contributes to the development of interactive intelligent tutoring systems and expands design knowledge for AI-based educational technologies in technology-mediated learning environments.
Recommended Citation
Weber, Florian; Neshaei, Seyed Parsa; Wambsganss, Thiemo; and Soellner, Matthias, "Intelligent Tutoring for Law Courses: Design and Evaluation of an LLM-based System" (2025). ICIS 2025 Proceedings. 6.
https://aisel.aisnet.org/icis2025/isdesign/isdesign/6
Intelligent Tutoring for Law Courses: Design and Evaluation of an LLM-based System
Legal literacy has become a key competency in both professional and everyday contexts. Individuals are increasingly required to understand legal principles, whether managing business contracts, interpreting policies, or ensuring regulatory compliance. As part of this broader competence, the ability to understand and write clear and well-structured legal texts is essential. Many students, however, find legal writing challenging because of its complex reasoning and formal conventions. To address this, we present CaseCoach, an intelligent tutoring system based on large language models (LLMs) that supports students in solving complex legal problems through conversational tutoring. Using a design science research approach, we first derived system requirements through interviews with 14 law students. We then evaluated CaseCoach’s effectiveness in a quantitative study involving 40 business and law students. Our research contributes to the development of interactive intelligent tutoring systems and expands design knowledge for AI-based educational technologies in technology-mediated learning environments.
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