The rise of IoT (Internet of Things) and Big Data has brought unprecedented changes to the way industries operate, from healthcare to education, offering improvements in efficiency, accessibility, and decision-making. However, the deployment of these technologies presents serious ethical concerns, especially regarding privacy, data ownership, fairness, and transparency in algorithmic decisions. This paper explores the theoretical foundations of ethics, focusing on deontology, utilitarianism, and virtue ethics, and examines how these frameworks can be applied to IoT and Big Data environments. It further considers how these technologies impact educational performance evaluations, highlighting the ethical issues arising from the collection and use of student data. By analyzing more than 20 empirical studies, this research identifies ongoing ethical debates and practical solutions, proposing that a hybrid ethical governance model is necessary. The study concludes with recommendations for stricter regulations, the responsible deployment of AI, and the importance of transparent, participatory policies to safeguard privacy and fairness in the digital era.
Keywords
IoT Ethics, Big Data Ethics, Digital Privacy, Ethical Frameworks, Algorithmic Bias, Data Governance, AI Regulation, Educational Performance, Data Ownership, Privacy Preservation, Surveillance
