Virtual Interviewers, Real Results: Exploring AI-Driven Mock Technical Interviews on Student Readiness and Confidence

TL;DR

This study investigates the use of a multimodal AI system to simulate technical interviews, aiming to improve student readiness and confidence through realistic practice, despite some challenges with conversational flow.

Contribution

It introduces an AI-driven mock interview tool that provides realistic technical interview simulations and evaluates its impact on student confidence and articulation.

Findings

Participants found the AI interviews realistic and helpful.

Increased confidence and improved problem articulation were observed.

Challenges with conversational flow and timing were identified.

Abstract

Technical interviews are a critical yet stressful step in the hiring process for computer science graduates, often hindered by limited access to practice opportunities. This formative qualitative study (n=20) explores whether a multimodal AI system can realistically simulate technical interviews and support confidence-building among candidates. Participants engaged with an AI-driven mock interview tool featuring whiteboarding tasks and real-time feedback. Many described the experience as realistic and helpful, noting increased confidence and improved articulation of problem-solving decisions. However, challenges with conversational flow and timing were noted. These findings demonstrate the potential of AI-driven technical interviews as scalable and realistic preparation tools, suggesting that future research could explore variations in interviewer behavior and their potential effects on candidate preparation.