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

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

Nathalia Gomez, S. Sue Batham, Matias Volonte and Tiffany Do
CSCW Companion '25: Companion Publication of the 2025 Conference on Computer-Supported Cooperative Work and Social Computing, pp 209-213
17 Oct 2025
DOI: https://doi.org/10.1145/3715070.3749227
Featured in Collection :   Research Supported by Drexel Libraries' OA Programs
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https://doi.org/10.1145/3715070.3749227View
Published, Version of Record (VoR)Open Access via Drexel Libraries Read and Publish Program 2025CC BY V4.0,  Restricted

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.

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