SmartEdu: Designing an AI-Ready Learning Management System Using Visual Semantic Ontologies

The digital transformation of education demands intelligent Learning Management Systems (LMS) capable of delivering personalized, context-aware learning experiences. The aim of this work is to examine the SmartEdu, an AI-ready LMS developed through Object-Oriented Analysis and Design Methodology (OOADM) and powered by Visual Semantic Ontologies, addressing critical limitations of conventional e-learning platforms. The system's development incorporated a robust methodological framework combining OOADM for system architecture with Protégé for ontology development, PHP/MySQL for backend implementation, TensorFlow for AI-driven recommendations, D3.js for knowledge visualization, and Moodle API for LMS integration. SmartEdu's PhD-level ontology framework enables sophisticated competency mapping and adaptive learning pathways, achieving a 32% improvement in learning personalization and 41% enhancement in content discoverability compared to traditional platforms. The implementation demonstrates how semantic web technologies integrated with visual ontology modeling can transform static e-learning environments into dynamic, intelligent ecosystems. Case studies across three higher education institutions validate the system's effectiveness in knowledge representation and personalized education delivery. This research makes significant theoretical contributions to intelligent educational systems while providing practical insights for implementing ontology-driven platforms. The results establish OOADM as an effective approach for complex educational system development and showcase how visual semantic technologies can address current challenges in digital education. The study offers higher education institutions a scalable, future-proof solution that bridges cutting-edge technologies with pedagogical requirements.

Artificial Intelligence, Traditional Learning Management Systems

1. Abdulraheem, B. M. (2023). Design and implementation of an online teaching and learning management system. FUDMA Journal of Sciences. 12 [Google Scholar] [Crossref]

2. Aning, A., & Baharum, A. (2020). E-learning design in Malaysian higher educational institutions. Journal of Hunan University Natural Sciences. 11 [Google Scholar] [Crossref]

3. Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The Semantic Web. Scientific American. [Google Scholar] [Crossref]

4. Bradley, V. M. (2021). Learning Management System (LMS) use with online instruction. International Journal of Technology in Education, 4(1), 68–92. 3 [Google Scholar] [Crossref]

5. Brusilovsky, P., & Peylo, C. (2003). Adaptive and intelligent web-based educational systems. International Journal of Artificial Intelligence in Education, 13(2-4), 156-169. [Google Scholar] [Crossref]

6. Chen, X. (2020). Neurosymbolic AI for education: Bridging neural networks and knowledge representation. [Google Scholar] [Crossref]

7. Duval, E. (2011). Attention please! Learning analytics for visualization and recommendation. [Google Scholar] [Crossref]

8. Emmanuel V. N. (2024). Learning management systems for higher education: A brief comparison. SpringerOpen, 3(58). 7 [Google Scholar] [Crossref]

9. Ergen T., and Kozat S.S. (2017). Neural Networks based Online Learning. In: IEEE 25th Signal Processing and Communications Applications Conference. 13(3):578–583 [Google Scholar] [Crossref]

10. Lane A. (2024). The Role of AI in the Semantic Layer. https://enterprise-knowledge.com/the-role-of-ai-in-the-semantic-layer/. 1 [Google Scholar] [Crossref]

11. Lim, C. C., Yu, M. H., Jin, J. S., & Chung, V. (2004). Design and development of an e-learning management system. ICEB 2004 Proceedings. 2 [Google Scholar] [Crossref]

12. Mizoguchi, R., & Bourdeau, J. (2016). Using ontological engineering to overcome AI-ED problems. International Journal of AI in Education, 26(1), 91-106. [Google Scholar] [Crossref]

• The Role of Artificial Intelligence in Revolutionizing Library Services in Nairobi: Ethical Implications and Future Trends in User Interaction
• ESPYREAL: A Mobile Based Multi-Currency Identifier for Visually Impaired Individuals Using Convolutional Neural Network
• Comparative Analysis of AI-Driven IoT-Based Smart Agriculture Platforms with Blockchain-Enabled Marketplaces
• AI-Based Dish Recommender System for Reducing Fruit Waste through Spoilage Detection and Ripeness Assessment
• SEA-TALK: An AI-Powered Voice Translator and Southeast Asian Dialects Recognition