VIVABOT: An AI-Driven Automated Viva Examination System for Efficient and Adaptive Assessments

VIVABOT: An AI-Driven Automated Viva Examination System for Efficient and Adaptive Assessments

Dr A Sree Lakshmi 1, Professor and  HOD in the Department of 1 Computer Science and Engineering , Geethanjali College of Engineering and Technology, Affiliated by Jawaharlal Nehru Technological University ,Hyderabad, India.

Badugu Jessy 2, Student in the Department of  2 Computer Science and Engineering , Geethanjali College of Engineering and Technology, Affiliated by Jawaharlal Nehru Technological University ,Hyderabad, India.

A Praneeth Kumar Reddy3, Student in the Department of 3 Computer Science and Engineering , Geethanjali College of Engineering and Technology, Affiliated by Jawaharlal Nehru Technological University ,Hyderabad, India.

E-mail: 1sreelakshmi.cse@gcet.edu.in, 221r11a05m0@gcet.edu.in, 321r11a05l6@gcet.edu.in

Abstract

VivaBot is an intelligent and completely computerized viva examination system for enhancing efficiency, accuracy, and flexibility in conducting viva voce examinations. It minimizes cumbersome faculty effort by using face recognition-based verification, machine-based roll marking, AI-based question generation, adaptive questioning, and intelligent answer marking. Professors can schedule viva sessions by selecting the class and week, while students securely log in using their face and roll number for effective authentication and impersonation avoidance. The system implements an adaptive questioning mechanism where questions start at a medium level of difficulty and dynamically adjust based on the response of students to give a customized and impartial test. VivaBot makes use of Ollama Mistral AI to generate questions automatically, where educators can upload a set of pre-designed questions in PDF or type in a subject for AI-auto-generated question creation. The AI model even grades student responses unbiasedly, lightening the workload for teaching staff to a large extent and eliminating grading bias. VivaBot also generates performance reports with confidence levels and quality of answers scores according to students' performance, providing elaborate feedback and explanations to each question so that a better understanding is achieved and there will be improvement in the future. Supplementing text-based and speech-
based viva tests, the system utilizes DeepFace technology to facilitate accurate speech recognition and response analysis, making the viva interactive and effective. With machine learning, AI, and automation integration, VivaBot simplifies viva tests with structured, fair, and effective testing, reducing faculty workload as well as offering students an immersive, adaptive, and informative learning experience.

Keywords: Artificial Intelligence and Machine Learning, DeepFace, Large Language Models, Adaptive Questioning System, Automated Answer Evaluation, Student Performance Analysis, Confidence Scoring.