<![CDATA[In the current digital era, data science has emerged as a transformative discipline with profound potential for reshaping the educational landscape. This paper explores the multifaceted role of data science—specifically through educational data mining (EDM) and learning analytics—in enhancing teaching and learning processes across various platforms. Through a critical literature review, the study examines the dual nature of data utilization. On one hand, it highlights significant benefits such as personalized learning, early detection of student behavioral patterns, and evidence-based decision-making. On the other hand, it addresses critical risks, including privacy concerns, ethical violations, social stereotyping (labeling), and the potential commodification of education by corporate interests. The analysis further demonstrates that an overreliance on quantitative metrics risks neglecting the psychological dimensions and sociocultural contexts inherent in human learning. To mitigate these imbalances, the paper proposes the application of the DELICATE framework (determination, explain, legitimate, involve, consent, anonymize, technical aspects, and external partners) to ensure transparency and data protection. The study concludes by emphasizing a necessary shift from a purely technocratic perspective to a human-centered design approach. The authors argue that data science should serve as a pedagogical support tool rather than a substitute for teacher intuition. By integrating quantitative methods with qualitative-ethnographic approaches, a more just, innovative, and humane educational environment can be achieved.]]>
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