Leveraging AI for Enhanced Curriculum Mapping and Informed Design Decision-Making

Text similarity analysis is a powerful tool that can help identify hidden relationships and patterns in learning content that may be useful for curriculum designers. On this poster, an exercise will be presented in which similarity analysis techniques have been applied to compare curricula from different educational programs. In this work, data has been collected from various curricula, and a similarity analysis has been conducted using NPL algorithms. These algorithms have allowed the identification of the most similar areas of study between the different curricula, as well as significant differences in terms of learning contents and outcomes. Additionally, a visualization model has been developed to graphically represent the similarities and differences found in the curricula. This visual representation enables a quick and clear understanding of the analysis results, facilitating comparison and informed decision-making by educational decision-makers. It is believed that this work has great potential for improving curriculum planning and decision-making in education. The results of the similarity analysis can help identify opportunities for collaboration between programs, detect gaps in curriculum content, and guide decisio- making in the updating and design of new educational programs.