Iniobong Okon

Work place: Department of Computer and Robotics Education, University of Uyo, Uyo, Nigeria

E-mail: iniobongokon1@iniuyo.edu.ng

Website: https://orcid.org/0009-0006-8810-9909

Research Interests:

Biography

Iniobong Uwem Okon is an academic and researcher in Computer Science Education, specializing in Artificial Intelligence. She lectures in the Department of Computer and Robotics Education at the University of Uyo, Nigeria, where she also earned her Master of Science (Ed) degree. Her research focuses on applying educational technology and machine learning to enhance learning outcomes.

Author Articles
Delivering the Core Curriculum and Minimum Academic Standards (CCMAS) in a Virtual Platform in Nigeria: A Systematic Review

By Gabriel James Anietie Ekong David O. Egete Martha Orazulume Iniobong Okon Aniekan Effiong

DOI: https://doi.org/10.5815/ijeme.2026.01.01, Pub. Date: 8 Feb. 2026

This research investigates the effectiveness of various virtual learning platforms; Zoom, Class Dojo, Google Classroom, and VICBHE (Virtual Interactive Classroom for Bilingual Higher Education), in delivering Core Curriculum and Minimum Academic Standards (CCMAS)-aligned content. The study evaluates platform features such as multimedia support, interactivity, student engagement, ease of assignment distribution, real-time feedback, CCMAS curriculum alignment, ease of use for teachers, and content delivery. This study reveals the platforms ' strengths and weaknesses in facilitating learning outcomes through a combination of regression analysis and experimental data from multiple educational settings. The findings indicate that student engagement and curriculum alignment have the most significant impact on educational success, with Google Classroom emerging as the most effective platform overall. VICBHE, designed to deliver region-specific content, excels in curriculum alignment but faces challenges in interactivity and real-time feedback, limiting its effectiveness in dynamic learning environments. The research concludes with recommendations for platform improvements and strategies for optimizing virtual learning in diverse educational contexts.

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