About the Project
This study explores how law students in Singapore evaluate AI-generated outputs on tort law, focusing on metacognitive awareness and reflective judgment to strengthen legal reasoning and lifelong learning skills. While AI integration in education offers adaptive and personalized learning, its role in legal education remains underexplored.
The research addresses two key questions: how students assess AI outputs for reasoning, accuracy, and clarity, and what best practices support critical evaluation to enhance metacognitive learning. Using tort law—a core module in common law jurisdictions—the study examines students’ ability to adopt, revise, or reject AI reasoning, contributing to responsible AI use in academic and professional contexts.
Research participants will be asked to review AI-generated responses to legal problems, rate them on multiple dimensions, and provide reflective feedback. Data will be analyzed using validated AI literacy and metacognition scales to identify patterns in evaluative reasoning. Findings will inform best practices for evaluating AI outputs on the law, addressing issues like argument strength, reference accuracy, and risks such as hallucinations and jurisdictional errors. By bridging legal education, metacognitive research, and AI literacy, this project supports ethical AI integration, academic integrity, and professional readiness, offering a foundation for future comparative studies across legal disciplines.
Research Impact : Supporting and enhancing law students’ critical evaluation of and reflective judgement on AI outputs”
Theme: Technologies for Augmenting Adult Learning
Principal Investigator(s)
ResWORK Fellow, Gary CHAN Kok Yew @ YPHSL