Design and Implementation of an Artificial Intelligence-Augmented Learning Management System (EduSync)
DOI:
https://doi.org/10.70112/ajcst-2026.15.2.4448Keywords:
Artificial Intelligence, Automated Grading, EduSync, Learning Management System, React, SupabaseAbstract
The fragmented platforms in Nigerian universities do not offer personalization, real-time interaction, or Artificial Intelligence features, making it difficult for both students and lecturers. This platform was developed using the Incremental Software Development Model through eight stages. The frontend consists of React 18, TypeScript, and Tailwind CSS, while the backend is based on the Supabase PostgreSQL database. The GROK (Llama) API enables the automated assessment engine to function properly. All performance objectives were achieved, including logging in within 1-2 seconds, loading the dashboard within 1-3 seconds, and submitting assignments within 2 seconds. The role-based access control system effectively restricted any form of unauthorized access, while the AI grading engine provided instant feedback with complete lecturer override functionality. EduSync has made lecturers' workloads less burdensome and students more organized by using AI to automate processes, demonstrating that efficient and intelligent LMS systems can transform the Nigerian university system.
References
[1] P. Adako and S. Ekundayo, "A systematic review of factors influencing digital inclusion in African higher education during periods of crises," Int. J. Educ. Dev., vol. 107, p. 102980, 2025.
[2] O. Ajani et al., "The role of institutional readiness in sustaining LMS use in rural South African universities," J. Comput. High. Educ., vol. 37, no. 1, pp. 121–140, 2025.
[3] M. Almaiah et al., "Exploring the critical challenges and factors influencing the e-learning system usage during COVID-19 pandemic," Educ. Inf. Technol., vol. 25, no. 6, pp. 5261–5280, 2020. doi: 10.1007/s10639-020-10219-y.
[4] S. M. ARITEKIN, "A systematic literature review on factors affecting the adoption of AI-enabled Learning Management Systems (2020–2025)," Interact. Learn. Environ., advance online publication, 2025.
[5] M. Bond, "A meta-systematic review of artificial intelligence in higher education: Ethical, collaborative, and methodological challenges," Int. J. Educ. Technol. High. Educ., vol. 21, no. 1, p. 36, 2024. doi: 10.1186/s41239-023-00436-z.
[6] X. Chen et al., "AI-powered chatbots in learning management systems: Improving engagement through adaptive feedback," Educ. Technol. Res. Dev., vol. 71, no. 5, pp. 2149–2167, 2023. doi: 10.1007/s11423-023-10177-8.
[7] J. Chun et al., "PlanGlow: Personalized study planning with an explainable and controllable LLM-driven system," in Proc. ACM CHI, 2025. doi: 10.1145/3698205.3729541.
[8] Ekuase-Anwansedo and A. Smith, "Effect of cloud-based learning management system on the LMS implementation process: Faculty and student perspectives," arXiv preprint arXiv:2102.10522, 2021. doi: 10.48550/arXiv.2102.10522.
[9] García-Varela et al., "ChatGPT as a stable and fair tool for automated essay scoring," Educ. Sci., vol. 15, no. 8, p. 946, 2025. doi: 10.3390/educsci15080946.
[10] Grévisse et al., "LLM-based automatic short answer grading in undergraduate medical education," BMC Med. Educ., vol. 24, no. 1, p. 1060, 2024. doi: 10.1186/s12909-024-06026-5.
[11] Jamil et al., "Adoption of learning management system for teaching by academic staff in selected faculties of Ahmadu Bello University, Zaria," Lonoja J. Inf. Sci. Res., vol. 2, no. 1, pp. 40–58, 2024.
[12] S. Kumar et al., "Integration of personal management features in learning management systems: Enhancing student engagement," J. Comput. High. Educ., vol. 34, no. 2, pp. 233–249, 2022.
[13] M. Lundgren, "Large language models in student assessment: Opportunities and challenges," Assess. Eval. High. Educ., vol. 49, no. 2, pp. 210–225, 2024.
[14] MDPI, "AI-powered automated essay grading: A comparison of performance metrics between GPT-4 and human graders," J. Educ. Technol., advance online publication, 2025.
[15] J. Mensah and R. Boateng, "Mobile-first learning management systems for bandwidth-constrained environments in sub-Saharan Africa," Afr. J. Inf. Syst., vol. 16, no. 1, pp. 89–104, 2024.
[16] K. Okoye and A. Ikedinachi, "Artificial intelligence-augmented learning management systems: Prospects and challenges," Int. J. Educ. Dev. ICT, vol. 17, no. 3, pp. 45–60, 2021.
[17] P. G. Poličar et al., "Automated assignment grading with large language models: Insights from a bio-informatics course," Bioinformatics, vol. 41, Suppl. 1, pp. i21–i29, 2025. doi: 10.1093/bioinformatics/btae334.
[18] Qeios, "Ethical governance and trust in AI-driven LMS: A bibliometric analysis of the past five years," Qeios J., advance online publication, 2025.
[19] S. H. Raza and A. Farooq, "AI in Pakistani schools: Adoption, usage, and perceived impact among educators," arXiv preprint arXiv:2509.25293, 2025.
[20] R. Safilian et al., "RATAS: A GenAI approach for explainable and scalable automated answer grading," 2025.
[21] Y. Su et al., "Challenges in Moodle adoption: Digital literacy and content overload," Int. J. Emerging Technol. Learn., vol. 17, no. 4, pp. 120–133, 2022.
[22] N. Thakur et al., "Judging the judges: Evaluating alignment and vulnerabilities in LLMs-as-judges," in Proc. ACL GEM Workshop, 2025.
[23] Y. Zhang and N. Patel, "Systematic review of AI-driven learning management systems: Personalization, predictive analytics, and gamification," Int. J. Educ. Technol. High. Educ., vol. 22, no. 1, p. 58, 2025.
[24] Y. Zou et al., "Examining the impact of user interface design on student engagement in mobile learning management systems," Br. J. Educ. Technol., vol. 54, no. 5, pp. 1083–1100, 2023.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Centre for Research and Innovation
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
