International Journal of
Information and Education Technology

Editor-In-Chief: Prof. Jon-Chao Hong
Frequency: Monthly
ISSN: 2010-3689 (Online)
E-mali: editor@ijiet.org
Publisher: IACSIT Press
 

OPEN ACCESS
3.9
CiteScore

IJIET 2026 Vol.16(8): 2048-2058
doi: 10.18178/ijiet.2026.16.8.2665

Development and Usability Evaluation of an Intelligent Quiz Repository with AI-based Duplication and Similarity Detection for Instructional Support

Jayson A. Batoon *, Menirissa D. De Belen, Reylan M. Evale, and Digna S. Evale
College of Information and Communications Technology, Bulacan State University, Bulacan, Philippines
Email: jayson.batoon@bulsu.edu.ph (J.A.B.); menirissa.debelen@bulsu.edu.ph (M.D.D.B.); reylan.evale@bulsu.edu.ph (R.M.E.); digna.evale@bulsu.edu.ph (D.S.E.)
*Corresponding author

Manuscript received December 14, 2025; revised January 23, 2026; accepted February 18, 2026; published August 12, 2026

Abstract—This study presents the development and usability evaluation of an intelligent quiz repository system enhanced with an Artificial Intelligence (AI)-based duplication and similarity detection mechanism to support quiz creation and management in higher education. The administration of quizzes and the management of item banks will be positively affected by the system in higher education. The whole idea is to create an integrated platform for the instructors to keep their quiz items in an easy way: store, classify and generate. The system’s major constituents are a quiz repository, a quiz generator, a dashboard that contains analytics, and an AI that has a cosine similarity method for tracking duplications and discovering repeating or almost identical questions. The study followed a developmental-descriptive path, concentrating on system architecture, user-interface design, and iterative refinements based on faculty input. The usability principles derived from Nielsen’s heuristics and Software Usability Measurement Inventory (SUMI) were incorporated into the design to ensure clarity, uniformity, and user-friendliness. The findings reveal that the system’s design has effectively addressed the issues of redundancy, disorganization, and manual workload, thus paving the way for new and expanded usability testing of the system in the near future.

Keywords—quiz repository, Artificial Intelligence (AI) duplication tracking, system design, quiz generation, usability evaluation


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Cite: Jayson A. Batoon, Menirissa D. De Belen, Reylan M. Evale, and Digna S. Evale, "Development and Usability Evaluation of an Intelligent Quiz Repository with AI-based Duplication and Similarity Detection for Instructional Support," International Journal of Information and Education Technology, vol. 16, no. 8, pp. 2048-2058, 2026.


Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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