Escobar Castillejos, DavidDavidEscobar CastillejosBarrera Ánimas, Ari YairAri YairBarrera ÁnimasLozada Flores, OctavioOctavioLozada FloresNoguez, JulietaJulietaNoguez2024-05-092024-05-092024-01-01Escobar-Castillejos, D., Barrera-Animas, A.Y., Lozada-Flores, O., Noguez, J. (2024). Enhancing STEAM in Education 4.0: A Review of Data-Driven Technological Improvements. In: Ponce, H., Brieva, J., Lozada-Flores, O., Martínez-Villaseñor, L., Moya-Albor, E. (eds) Data-Driven Innovation for Intelligent Technology. Studies in Big Data, vol 148. Springer, Cham. https://doi.org/10.1007/978-3-031-54277-0_297830315427639783031542770https://scripta.up.edu.mx/handle/20.500.12552/1039810.1007/978-3-031-54277-0_22-s2.0-85191728017Universities have fulfilled the role of organizations dedicated to the promotion of intellectual knowledge and the fostering of creative thinking. Educational institutions function as the central place for students to acquire specialized knowledge in their respective disciplines, while also developing competencies and beliefs that contribute to the progress of society. As technology advances, universities are facing a new revolution in the paradigms of education, which is making them adapt their established methodologies. Education 4.0 aims to improve education through cutting-edge technology and automation. Furthermore, the use of data-driven methodologies allows educators to automate the processes of assessment and evaluation, which could enhance the accuracy of comprehending educational outcomes. Universities are currently promoting the integration of analytical reasoning and creative expression using multidisciplinary techniques such as STEAM. This approach ensures that students not only acquire technical expertise, but also develop the essential skills of creativity, adaptability, and humanistic understanding that are necessary in the current job market. The objective of this chapter is to discuss the development and importance of STEAM within Education 4.0, emphasizing the potential of data-driven technologies. ©SpringerenAcceso RestringidoData Science for IndustryArtificial Intelligence for IndustryTechnology TrendsMachine Learning for IndustryMachine Learning ApplicationsData Science in Latin AmericaApplied Artificial IntelligenceData-driven InnovationResource Types::text::book::book part