Application of Data Science and ML in the Educational Context: A Case Study of Cambine Secondary School

This study investigates the potential of Data Science and Machine Learning as strategic areas for transforming the teaching and learning process at Cambine Secondary School. The research adopts a mixed-methods approach, combining qualitative and quantitative methods, including interviews and surveys with teachers, students, and school directors. The findings reveal significant barriers such as technological infrastructure limitations, a lack of specialized training, and insufficient pedagogical resources. On the other hand, relevant opportunities are identified, including personalized learning, academic performance prediction, and improved school management. The analysis highlights the need for a strategic plan to overcome these challenges and effectively integrate Data Science and Machine Learning. This plan should focus on technical training, adaptation to local specificities, and infrastructure investment. This study contributes to the debate on modernizing educational systems in resource-constrained contexts and proposes practical recommendations for the sustainable use of these technologies, emphasizing their relevance in promoting a more inclusive, innovative, and efficient education system.