计算法律分析:解决合同法问题的指导方法

IF 0.7 Q3 EDUCATION & EDUCATIONAL RESEARCH
Marton Ribary, Antony Starza-Allen
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引用次数: 0

摘要

本文提出了一种在一年级本科生合同法模块中解决问题的指导方法。我们的方法源于我们的教学实践,受计算建模理论的启发,帮助学生从主要和次要来源中识别和提取法律信息,并将所学知识组织到结构化框架中。这种方法为学习搭建了脚手架,并建立了一个可以识别法律问题的框架。这些框架可用于查找与构建分析和论证相关的法律信息,从而自信地提出法律建议。本文将我们的方法描述为五个不同的阶段:(1) 从法律资料中提取理论内容,(2) 将这些内容组织成一个连贯的框架,(3) 将框架应用于问题情景,(4) 构建和(5) 撰写详细、权威和有说服力的法律建议。我们的方法包含了基本技能,通过概念的 "语义网 "进行推论,并利用计算机启发的可视化构建论据。通过计算思维,学生可以将法律信息的初始分类与有说服力的法律论证的构成要素之间的联系可视化,从而阐明并揭开法律建议制作过程的神秘面纱。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computing Legal Analysis: A Guided Approach to Problem Solving in Contract Law
The paper proposes a guided methodology for problem solving in a first-year undergraduate contract law module. Developed from our teaching practice and inspired by theories of computational modelling, our approach helps students to identify and extract legal information from primary and secondary sources, and to organise what they have learned into structured frameworks. The method creates scaffolding for learning and a framework through which legal issues can be identified. These frameworks can be used to locate legal information relevant to the construction of analysis and argument to the point of producing legal advice with confidence. The paper describes our approach in five distinct stages: (1) extracting doctrinal content from legal sources, (2) organising such content into a coherent framework, (3) applying the framework to problem scenarios, (4) constructing , and (5) writing up detailed, authoritative, and persuasive legal advice.. Our methodology embeds essential skills aided by a “semantic web” of concepts from which one could draw inferences, and uses computer-inspired visualisation for constructing arguments. Computational thinking allows students to visualise connections between the initial categorisation of legal information and the constitutive elements of a persuasive legal argument to articulate and demystify the process of producing legal advice.
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来源期刊
Legal Education Review
Legal Education Review EDUCATION & EDUCATIONAL RESEARCH-
自引率
66.70%
发文量
7
审稿时长
12 weeks
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