Integration of Qualitative and Quantitative Data Science for Education, Health, and Technological Development (GIERENA Multigroup)

This project addresses the fragmentation and heterogeneity of information in the education, health, and technological development sectors by integrating qualitative and quantitative approaches. Faced with the need to optimize decision-making, the research proposes a unified framework that uses Big Data, artificial intelligence, and machine learning to process large volumes of data efficiently. The methodology is structured in phases that include identifying sources, designing workflows with advanced APIs, and developing functional prototypes. The project aims not only to improve resource management and the personalization of pedagogical strategies but also to strengthen distributed software development through cloud architectures. As a result, the project expects to generate scalable tools, scientific publications, and applicable knowledge that allow for more effective, evidence-based management. This transdisciplinary approach seeks to create intersectoral synergies that benefit society, promoting technological innovation and continuous improvement in educational and health services.<br/><br/><b>Goal</b>: <br/>Develop a comprehensive framework based on data science and artificial intelligence for the collection, analysis, and integration of data in the education, health, and technological development sectors. The goal is to optimize decision-making through the use of advanced technologies such as Big Data and machine learning.<br/><br/><b>Research lines</b>: <br/>Data science and simulation