Academic course registration processes in higher education institutions often involve complex approval workflows, manual paperwork, and communication delays that can significantly impact student satisfaction and administrative efficiency. This paper presents the design, implementation, and evaluation of a cloud-based Course Add/Drop Management System (CADMS) developed for the universities in higher education. The proposed system implements a three-tier approval workflow involving Academic Advisors, Heads of Department, and Registrars, automating the entire process from student request submission to final approval and PDF certificate generation. Built using modern web technologies and Google Apps Script as the backend infrastructure, the system provides real-time status tracking, automated email notifications, and comprehensive dashboard interfaces for all stakeholders. The system was evaluated over a semester with 250+ student requests, demonstrating significant improvements in processing time (reduced from 7-10 days to 24-48 hours), paper consumption (100% elimination), and user satisfaction (88% satisfaction rate). This research contributes to the body of knowledge in educational technology by presenting a cost-effective, scalable solution that can be adapted by institutions with limited IT infrastructure. The paper details the system architecture, implementation methodology, evaluation metrics, and lessons learned during deployment.
Keywords: Course Registration System, Academic Workflow Automation, Cloud Computing, Google Apps Script, Educational Technology, Multi- Tier Approval System, Web Application Development, Serverless, Digitization, Transformation, System, Software Engineering, University, Workflows, Google, Playbook, System Design, Development.
[1] Ahmad, M., et al. (2025). Learning three-dimensional face recognition from sparse views for robust identity verification. SSRN. https://ssrn.com/abstract=5428214.
[2] Akram, F., et al. (2024). Integrating artificial bee colony algorithms for deep learning model optimization: A comprehensive review. In Solving with Bees: Transformative Applications of Artificial Bee Colony Algorithm, Pages 73–102. https://doi.org/10.1007/978-981-97-7344-2_5.
[3] Al Omari, O.M.A., Khan, N.A., & Mahafdah, R. (2017). Ranking and reputation based resource allocation in P2P system. Mediterranean Journal of Basic and Applied Sciences, 1(1): 293–301.
[4] Alanezi, R., Alanezi, M.A., & Khan, N.A. (2018). Development of web based e-cooperative training system. In 2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE).
[5] Alangari, S., et al. (2022). Developing a blockchain-based digitally secured model for the educational sector in Saudi Arabia toward digital transformation. PeerJ Computer Science, 8: e1120.
[6] Alangari, S., & Khan, N.A. (2021). Artificially intelligent warehouse management system. Asian Journal of Basic Science & Research, 3(3): 16–24. https://doi.org/10.38177/ajbsr.2021.3302.
[7] Khan, N., et al. (2025). Network intrusion management of web form spamming using blockchain. Irish Interdisciplinary Journal of Science & Research, 9(3).
[8] Khan, N.A. (2018). Cloud applications development and deployment: The future of cost-effective programming and a step ahead. Middle East Journal of Applied Science & Technology, 1(1): 30–36.
[9] Khan, N.A. (2019). Security management protocols in cloud computation. Middle East Journal of Applied Science & Technology, 2(1): 16–23.
[10] Khan, N.A., et al. (2019). Intrusion management to avoid web-form spamming in cloud based architectures. In 2019 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE). https://doi.org/ 10.1109/iccike47802.2019.9004302.
[11] Khan, N.A., et al. (2019). Prevention of web-form spamming for cloud based applications: A proposed model. In Amity International Conference on Artificial Intelligence (AICAI).
[12] Khan, N.A. (2019). Wireless requirements and benefits in the academics domain. Middle East Journal of Applied Science & Technology, 2(3): 45–49.
[13] Khan, N.A. (2019). Basics of ethical hacking and computer security.
[14] Aljomaee, W.Y., Alshahrani, S.M., & Khan, N.A. (2025). NAMAQ-Arabic handwriting recognition using deep learning, AI, and ML with sentiment analysis. In 2025 4th International Conference on Computing and Information Technology (ICCIT). https://doi.org/10.1109/iccit63348.2025.10989445.
[15] Khan, N.A., & Ghamdi, A. (2015). Cyber forensics and proposed techniques to overcome cyber threats for cyber security. International Journal of Engineering and Management Research, 5(5): 187–191.
[16] Alshalaan, M., & Khan, N.A. (2025). Complexities and challenges for securing digital assets and infrastructure in academia: A review on digital asset security. In Complexities and Challenges for Securing Digital Assets and Infrastructure, Pages 225–244. https://doi.org/10.4018/979-8-3373-1370-2.ch011.
[17] Almalki, J., et al. (2022). Enabling blockchain with IoMT devices for healthcare. Information, 13(10): 448. https://doi.org/10.3390/info13100448.
[18] Almalki, J., Alshahrani, S.M., & Khan, N.A. (2024). A comprehensive secure system enabling healthcare 5.0 using federated learning, intrusion detection and blockchain. PeerJ Computer Science, 10: e1778.
[19] Khan, N.A. (2019). Measuring academics intentions to use a project management system (PMS): A case study of the College of Computing and Information Technology, Shaqra University. Trends in Future Informatics and Emerging Technologies, Pages 58–69.
[20] Khan, N.A. (2025). Statistical probability prediction model for e-learning and realtime proctoring using IoT devices. Journal of King Saud University – Science, 37: 7002025.
[21] Alshahrani, S.M., et al. (2023). Systematic survey on big data analytics and artificial intelligence for COVID-19 containment. Computer Systems Science & Engineering, 47(2). https://doi.org/10.32604/csse.2023 .039648.
[22] Alshahrani, S.M., & Khan, N.A. (2023). COVID-19 advising application development for Apple devices (iOS). PeerJ Computer Science, 9: e1274. https://doi.org/10.7717/peerj-cs.1274.
[23] Alshahrani, S.M., et al. (2022). URL phishing detection using particle swarm optimization and data mining. Computers, Materials & Continua, 73(3). https://doi.org/10.32604/cmc.2022.030982.
[24] Alshalaan, M., & Khan, N.A. (2025). Blockchain-enabled federated learning framework for secure and collaborative drug discovery: Integrating AI, molecular docking, and distributed ledger technology.
[25] Alsulami, M.H., Alotaibi, S., & Khan, N. (2021). Smart university model for Saudi Arabian universities. Design Engineering: 162–181.
[26] Alsulami, M.H., et al. (2021). Zigbee technology to provide elderly people with well-being at home. International Journal of Sensors Wireless Communications and Control, 11(9): 921–927. https://doi.org/10.217 4/22103279 11666210201105206.
[27] Hassan, M.A.A., Khan, N.A., & Nasim, M.A. (2017). Managing data replication in mobile ad-hoc network databases using content based energy optimization. Mediterranean Journal of Basic and Applied Sciences, 1(1): 142–154.
[28] Khan, N.A. (2024). Development of intelligent pick and drop service manager for small cities. Asian Journal of Basic Science & Research, 6(3): 20–27. https://doi.org/10.38177/ajbsr.2024.6303.
[29] Khan, N.A. (2024). Development of intelligent help system for small cities. Asian Journal of Applied Science and Technology, 8(3): 112–119. https://doi.org/10.38177/ajast.2024.8311.
[30] Khan, N.A. (2025). Development of intelligent student information system. Arabian Journal of Basic Science and Research, 7(1). https://doi.org/10.38177/ajbsr.2025.7101.
[31] Khan, N.A., et al. (2021). Development of Mubadarah system – An intelligent system for proposals at a university. In 2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE). https://doi.org/10.1109/iccike51210.2021.9410773.
[32] Khan, N.A., et al. (2021). Development of Medidrone: A drone based emergency service system for Saudi Arabian healthcare. In 2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE). https://doi.org/10.1109/iccike51210.2021.9410685.
[33] Khan, N.A., Rajeyyagari, S., & Khan, A.R. (2025). Development of intelligent library services for university students. Mediterranean Journal of Basic and Applied Sciences, 9(1): 142–147.
[34] Khan, N.A., Siddiqi, A.M.U., & Ahmad, M. (2021). Development of intelligent alumni management system for universities. Asian Journal of Basic Science & Research, 3(2): 51–60. https://doi.org/10.38177/ajbsr. 2021.3206.
[35] Khan, N.A., & Ahamad, D. (2025). Living smart: AI-based urban assistance systems for sustainable wellbeing in small cities. https://doi.org/10.46431/mejast.2025.8210.
[36] Khan, N.A., et al. (2025). Transformative impact of artificial intelligence on higher education: A comprehensive analysis of pedagogical innovation, institutional transformation, and future learning ecosystems. Asian Journal of Applied Science and Technology, 9(4): 57–76.
[37] Khan, N.A., et al. (2024). An IoMT enabled iterative artificial bee colony approach using federated learning for detection of heart disease. In Solving with Bees: Transformative Applications of Artificial Bee Colony Algorithm, Pages 103–116. https://doi.org/10.1007/978-981-97-7344-2_6.
[38] Khan, N.A., et al. (2021). An empirical analysis on users’ acceptance and usage of BYOD-technology for Saudi universities: A case study of Shaqra University. In 2021 International Conference on Technological Advancements and Innovations (ICTAI). https://doi.org/10.1109/ictai53825.2021.9673287.
[39] Khan, N.A., Al-Omari, O.M., & Alshahrani, S.M. (2023). An empirical study on the future of publication repositories and its adaptability in public universities—A case study of Shaqra University, Saudi Arabia. In Computational Intelligence: Select Proceedings of InCITe, Pages 823–829.
[40] Khan, N.A., & Albatein, J. (2021). COVIBOT – An intelligent WhatsApp based advising bot for COVID-19. In 2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE). https:// doi.org/10.1109/iccike51210.2021.9410801.
[41] Khan, N.A., & Alshalaan, M. (2025). AI-driven blockchain framework for digital transformation of academic accreditation process: A Saudi Arabian perspective. https://doi.org/10.46759/iijsr.2025.9404.
[42] Khan, N.A., Khan, A.R., & Rajeyyagari, S. (2025). Innovation in teaching and learning with the use of modern computational tools: A post COVID experience. Middle East Journal of Applied Science & Technology, 8(2): 74–82. https://doi.org/10.46431/mejast.2025.8208.
[43] Khan, V.N.A., et al. (2020). Internet of things (IoT) based educational data mining (EDM) system. Journal of Mechanical Control & Mathematical Sciences, 15(3): 271–284.
[44] Mahafdah, R.F., Al-Omari, O.M., & Khan, N.A. (2018). Learning modal adaptability to improve reading and writing skills of students.
[45] Khan, N.A., et al. (2024). An IoMT enabled iterative artificial bee colony approach using federated learning for detection of heart disease. In Solving with Bees: Transformative Applications of Artificial Bee Colony Algorithm, Pages 103–116. https://doi.org/10.1007/978-981-97-7344-2_6.
[46] Zamani, A.S., Akhtar, M.M., & Khan, N.A. (2025). An application of machine learning, big data and IoT of enterprise architecture: Challenges, solutions and open issues. https://doi.org/10.5772/intechopen.1010260.
Source of Funding:
This study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.
Competing Interests Statement:
The authors declare that they have no competing interests related to this work.
Consent for publication:
The authors declare that they consented to the publication of this study.
Authors' contributions:
All the authors made an equal contribution in the Conception and design of the work, Data collection, Drafting the article, and Critical revision of the article.
Availability of data and materials:
Authors are willing to share data and material on request.
Ethical Approval:
Not applicable for this study.
Institutional Review Board Statement:
Not applicable for this study.
Informed Consent:
Not applicable for this study.
Acknowledgement:
Authors acknowledge the support and hard work from all those who helped in this study.
A New Issue was published – Volume 8, Issue 4, 2025
10-10-2025 11-07-2025