Iris and Voice Signal Model for Remote Invigilation of Computer-Based Examination

Michael Olamide Gbale, Samuel Oluwatayo Ogunlana, Aliyu Ednah Olubunmi, Gabriel Babatunde Iwasokun, Olumide Olayinka Obe and Raphael Olufemi Akinyede
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Michael Olamide Gbale: Department of Computer Science, Federal University of Technology, Akure
Samuel Oluwatayo Ogunlana: Department of Computer Science, Adekunle Ajasin University, Akungba-Akoko
Aliyu Ednah Olubunmi: Department of Computer Science, Adekunle Ajasin University, Akungba-Akoko Department of Software Engineering, Federal University of Technology, Akure
Gabriel Babatunde Iwasokun: Department of Information Systems, Federal University of Technology, Akure
Olumide Olayinka Obe: Department of Computer Science, Federal University of Technology, Akure
Raphael Olufemi Akinyede: Department of Information Systems, Federal University of Technology, Akure

International Journal of Research and Innovation in Social Science, 2024, vol. 8, issue 12, 229-240

Abstract: Computer-Based Examination (CBT) represents a growing trend in the assessment of knowledge and skills, utilizing computer technology to address many of the challenges associated with traditional, human-supervised examinations. These challenges include collusion, impersonation, unauthorized external assistance, and peeking. The research developed a comprehensive system that incorporates iris and voice recognition technologies to significantly reduce these problems, thereby enhancing the security, integrity, and reliability of the computer-based examinations. The system consists of the CBT module and the monitoring module. The CBT module includes a network infrastructure with a central server and several network-controlled workstations. The monitoring module was designed to monitor candidates in real-time and features an iris scanner that intermittently captures and analyzes the candidate’s iris, triggering warnings or punitive actions if the system detects Behaviour such as peeking beyond a permissible range or other iris-related infractions. It also includes a voice processor that intermittently captures the candidate’s audio signals, with similar consequences for violating audio intensity rules. The experimental study on the practical function of the system established its suitability for curtailing iris and voice-related infractions during CBT and the minimization of the costs associated with the screening, control, and management of CBT candidates.

Date: 2024
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