Mock interviews are structured, simulated interview experiences designed to mirror real-world job or academic interview scenarios. They serve as a critical preparatory tool for candidates aiming to enhance their communication skills, boost confidence, and receive constructive feedback before facing actual interviews. This project/system proposes a comprehensive mock interview framework incorporating both technical and behavioral components tailored to specific career domains such as software engineering, data science, business management, and academic admissions. Leveraging AI-driven question generation and real-time evaluation, the system enables users to engage in realistic, domain-specific interview simulations. The platform also integrates features like resume-based question customization, automated scoring, and performance analytics. By providing repeated practice opportunities and targeted feedback, mock interviews help bridge the gap between theoretical knowledge and practical presentation, ultimately increasing candidates’ chances of success in competitive selection processes.
Tejaswini et al. (Sat,) studied this question.