AI Powered Legal Assessments: Evaluating Advocate Skills Through Scenario Based Simulations

Abstract

This study introduces a brand-new interactive web tool that mimics actual legal situations to improve young advocates' hands-on training. The application creates a thorough and engaging learning environment by integrating multiple cutting-edge technologies. There are fewer practical experiences and more theoretical components to the current system for evaluating law scholars. One of the few methods they may currently demonstrate their legal expertise is through MootCourt. We employ a number of strategies, like incorporating an interactive chatbot, automated file management, and a case scheduling mechanism, to enhance exposure and allow them to hone their legal knowledge in a risk-free setting. The case scheduling system efficiently manages and distributes case time to maximize courtroom operations. Advocates can easily organize and submit legal papers with the help of automated file management. In order to improve the standard of legal education and preparation, the suggested solution seeks to provide a stable, controlled AI-driven chatbot for dynamic client and opposing advocate interactions, a case scheduling system for effective judicial management, and an automated file management system for seamless document handling in a risk-free setting that mimics real-world legal practice. This creative method bridges the crucial gap between academic understanding and real-world experience by giving young advocates a risk-free environment in which to hone their abilities.