Local Technology to Enhance Data Privacy and Security in Educational Technology - Amo, Daniel; Prinsloo, Paul; Alier, Marc; Fonseca, David; Torres Kompen, Ricardo; Canaleta, Xavier; Herrero-Martín, Javier (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 2022)
In educational environments, technological adoption in the last 10 years has enabled a data-driven and decisionmaking paradigm in organizations. The integration of cloud services in schools and universities is a positive shift in the field of learning, but it also presents threats to all academic roles that need to be discussed in terms of protection, privacy, and confidentiality. Cloud storage brings the ubiquity of data to this technical transition and a delusive opportunity for cost savings. In many cases, this suggests that certain actors, beyond the control of schools and colleges, collect, handle and treat educational data on private servers and data centers. This privatization enables the manipulation of stored records, leaks, and unauthorized access. In this article, we expose the possibilities that open from the viewpoint of local technology adoption. We seek to reduce or even totally solve the detrimental effects of using cloud-based instructional and analytical technology, mixing or only using local technology. Technological methods that conform to this alternate viewpoint and new lines of study are also being suggested and created.
Keywords: cloud computing; education; local technology; data privacy; security; IJIMAI