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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM60769

AI Powered Mock Interview Platform

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM60769

Volume:

10 |

4 |

April 2026

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/ijsrem60769

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

AH

Ankush Hutke

AC

Aishwary Chaurasia

DK

Dheeraj Kamat

VM

Vinit Mule

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Abstract

– Securing employment in the current job market is increasingly challenging, and effective interview preparation remains a significant hurdle for many candidates. Common preparation methods such as online videos, peer mock sessions, and generic question banks often fail to provide meaningful performance insights or actionable feedback. This paper presents a web-based platform designed to address these limitations. The system makes use of the Groq AI Engine API to conduct live mock interviews, dynamically generate role-specific questions, and evaluate candidate responses in real time. In addition, the platform incorporates an aptitude assessment and two coding challenges to strengthen technical proficiency. The frontend is developed using ReactJS, while Firebase Firestore manages backend data, including user records, performance scores, and session history. Overall, the system delivers a reliable, efficient, and user-centered solution for interview preparation, providing candidates with practical insights and measurable performance improvements.

KEYWORDS

Artificial Intelligence Mock Interview Groq API ReactJS Firebase Firestore Natural Language Processing Coding Challenges Aptitude Testing Real-time Feedback Career Preparation Web Application

Cite This Article

Ankush Hutke, Aishwary Chaurasia, Dheeraj Kamat, Vinit Mule, "AI Powered Mock Interview Platform," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 4, April 2026. https://doi.org/10.55041/ijsrem60769

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Publication Date

4/20/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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