Datafication in Education and Digital Sovereignty: Complex Challenges
Édgar Giovanni Rodríguez Cuberos, Fundación Universitaria Minuto de Dios UNIMINUTO (Colombia)
Carlos Beltrán Baquero, Fundación Universitaria Minuto de Dios UNIMINUTO (Colombia)
Ruby Barrios Roldán, Fundación Universitaria Minuto de Dios UNIMINUTO (Colombia)
Sara Barón Mora, Fundación Universitaria Minuto de Dios UNIMINUTO (Colombia)
Leonar Arias Alfaro, Fundación Universitaria Minuto de Dios UNIMINUTO (Colombia)
Abstract
As part of the educational strategies required for the 21st century, the human-machine relationship—forged through connections with artificial intelligence—has emerged as a significant phenomenon. Indeed, the education sector has readily integrated these applications into both daily life and academic practice. However, these technologies rely on underlying processes that are often misunderstood or excluded from the classroom—such as the structure and nature of the data used to train AI systems. Stemming from research aimed at identifying factors associated with technology adoption across the country's diverse educational contexts, this specific analysis focuses on determining what types of data—relevant and secure for AI processes—are generated within or are intrinsic to educational settings. For instance, while assessments produce numerical data in the form of grades, there is often no link between this data and the curricular processes that could facilitate data-driven improvements (Rodríguez Cuberos, 2024). Consequently, there is an urgent need to establish foundational guidelines for reclaiming what we term "educational data"—or what others call the "datafication of education"—while prioritizing a social perspective, autonomy, and technological sovereignty. Furthermore, the study highlights the current lack of awareness regarding the potential of educational data and proposes key elements to address this issue within the country.
Keywords: Educational strategies, Learning Spaces, data and education, datafication
REFERENCES
[1] Haller, S. A., & Siedschlag, I. (2011). “Determinants of ICT adoption: Evidence from firm-level data.” Applied Economics, Vol. 43 No. 26, pp. 3775–3788, doi: 10.1080/00036841003724411
[2] McElheran, K., Li, J. F., Brynjolfsson, E., et al. (2024). “AI adoption in America: Who, what, and where.” Economics Management Strategy 33:375–415. https://doi.org/10.1111/jems.12576
[3] Rodríguez Cuberos, E. G. (2024). Diseño de Ambientes de Aprendizaje (DAA) como Praxis Investigativa Educativa Multidisciplinar. Revista De Divulgación Shimmering Words: Research and Pedagogy E-Journal, 13(1), 9-21. https://revistas.santototunja.edu.co/index.php/shimmering/article/view/3007
[4] WEF (2025). New Economy Skills: Building AI, Data and Digital Capabilities for Growth. https://reports.weforum.org/docs/WEF_New_Economy_Skills_2025.pdf
New Perspectives in Science Education




























