Design and Implementation of an Ethical AI-Based Teaching Assistant for IoT Security Education - Matilda Isaacs; Anwar Majeed; Karim Moussa; Dolapo Shodipo (African Journal of Inter-Multidisciplinary Studies)
Artificial Intelligence (AI) integration in education has evolved significantly, with today's AI systems surpassing conventional computer-assisted teaching methods by providing more dynamic and interactive learning environments. This study aims to design and implement an Ethical AI-based teaching assistant tailored for IoT security education, marking a new milestone in the advancement of AI in educational settings. The system focused on ethical considerations such as data privacy, transparency, and accountability, fostering a learning environment where students can think critically, explore diverse perspectives, and engage meaningfully with AI technology. Central to the project's success was a robust design phase that included carefully selecting AI algorithms, a modular and scalable architecture, an intuitive user interface, and efficient data flow mechanisms. Thorough testing and continuous improvements ensured seamless integration with existing educational technologies, enhancing learning and teaching experiences. As a result, students improved their engagement levels and ability to identify and mitigate IoT security threats, and educators experienced a notable reduction in grading time thanks to the AI's automated assessment capabilities. Additionally, the project increased student satisfaction, greater utilization of learning resources, and the publication of research papers on IoT security. This study highlights the transformative potential of AI in education and underscores the importance of ethical considerations in its application. With its comprehensive approach to design, scalability, and security, this project serves as a model for the future of Ethical AI-driven education, offering valuable insights into how AI can enhance learning outcomes and teaching effectiveness while maintaining academic integrity and data security.