Shan Yang, Huixian Liao

Shan Yang

March 31, 2026

AI, Legal writing, Course assessment.

With the rapid adoption of AI in higher education, the assessment model for legal writing courses faces unprecedented dilemmas. Students can now use artificial intelligence tools to quickly generate structurally complete legal texts, while instructors are unable to determine, based solely on the final text of student assignments, whether students have truly acquired the competencies targeted by the legal curriculum. Current assessment mechanisms rely excessively on the final assignment texts submitted by students, and students’ over-reliance on AI to complete assignments undermines their critical thinking and value judgment abilities, which is inconsistent with the training objectives of legal education. This leads to the failure of the competency-screening function of course evaluation mechanisms and raises questions about the fairness of grading. While upholding the people-centered philosophy of education, AI application competency should be organically integrated into the assessment system of writing courses, driving a shift in evaluation criteria from outcome-oriented to process-oriented approaches. Accordingly, the focus of legal writing course assessment should not rest solely on reviewing the final submitted text, but should instead emphasize examining the entire process through which students progressively develop reasoning, form judgments, and complete their expression during writing. By requiring students to disclose their AI usage and supplementing this with necessary in-class process-based assessments, a set of legal writing evaluation criteria adapted to the demands of the AI era can be established.

© 2026, the Authors. Published by ISCCAC

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