Paper Number
1612
Paper Type
Completed
Description
Structured and persuasive writing is essential for effective communication, convincing readers of argument validity, and inspiring action. However, studies indicate a decline in students' proficiency in this area. This decline poses challenges in disciplines like law, where success relies on structured and persuasive writing skills. To address these issues, we present the results of our design science research project to develop an AI-based learning system that helps students learn legal writing. Our results from two different experiments with 104 students demonstrate the usefulness of our fully working AI-based learning system to support law students independent of a human instructor, time, and location. In addition to providing our embedded software artifact, we document our evaluated design knowledge as a design theory. Thus, we provide the first step toward a nascent design theory for the development of AI-based learning systems for legal writing.
Recommended Citation
Weber, Florian; Wambsganss, Thiemo; and Soellner, Matthias, "Design and Evaluation of an AI-based Learning System to Foster Students' Structural and Persuasive Writing in Law Courses" (2023). ICIS 2023 Proceedings. 9.
https://aisel.aisnet.org/icis2023/learnandiscurricula/learnandiscurricula/9
Design and Evaluation of an AI-based Learning System to Foster Students' Structural and Persuasive Writing in Law Courses
Structured and persuasive writing is essential for effective communication, convincing readers of argument validity, and inspiring action. However, studies indicate a decline in students' proficiency in this area. This decline poses challenges in disciplines like law, where success relies on structured and persuasive writing skills. To address these issues, we present the results of our design science research project to develop an AI-based learning system that helps students learn legal writing. Our results from two different experiments with 104 students demonstrate the usefulness of our fully working AI-based learning system to support law students independent of a human instructor, time, and location. In addition to providing our embedded software artifact, we document our evaluated design knowledge as a design theory. Thus, we provide the first step toward a nascent design theory for the development of AI-based learning systems for legal writing.
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