Artificial Intelligence in Data Visualization: Enhancing Research Through Generative Graphs

Abstract

This research examines how generative artificial intelligence, specifically ChatGPT, can transform the analysis and visualization of educational data in the Community of Madrid. Using university enrollment data processed and normalized in SPSS v27, a methodology was designed to integrate traditional statistical tools with advanced AI capabilities. The data were structured to reveal key trends in enrollment across public and private universities and various fields of knowledge. Iterative prompts created visualizations highlighting sustained growth in private institutions and a preference for Social Sciences and Health Sciences. The methodology addressed challenges of time and complexity in data visualization, though some inconsistencies in generated graphs were observed. Findings demonstrate AI's potential to enhance the understanding of complex data and support evidence- based decision- making in educational management. This hybrid approach highlights how AI tools can complement traditional methods, opening new possibilities for academic planning and educational research.