Work

InterviewAI: A Quantitative Evaluation of an AI-Powered Interview Simulation System for Job Applicants

Year: 2026

Type: conference-paper

Abstract: This paper addresses a critical software engineering challenge in applied AI: how to build transparent and auditable systems for high-stakes domains like employability training. The study presents InterviewAI, a voice-based web platform that simulates job interviews. Its core contribution is a novel software architecture that rigorously separates a generative Large Language Model (LLM) for question generation from a deterministic, rule-based engine for evaluation. This design directly counters the "black box" problem prevalent in end-to-end generative AI, ensuring that scoring is fair, traceable, and reproducible [5, 7].

Source: International Conference on Intelligent Information Technology (ICIIT)

DOI: 10.1145/3805862.3805883

Authors: Joemarie Comeros Amparo, Tisha Marie Ongcoy, Sharon Azarcon Bucalon, Marijoy Yaun, Shiela Mae Saga, Rasty Demecillo, Krystel Jane Ajias, Vanessa Malonjao, Angel Trocio Monteras

Institutions: Cebu Institute of Technology University, North Eastern Mindanao State University, University of Cebu-Banilad, University of Cebu-Lapulapu and Mandaue, Cebu Technological University, Department of Education

Language: English

Topic: AI and HR Technologies

Subfield: Organizational Behavior and Human Resource Management

Field: Business, Management and Accounting

Domain: Social Sciences

Open Access status: hybrid

OpenAlex ID: W7203671019

FWCI:

Cites: 16

Cited by:

Related to: 10