Unplugged institutions: towards a localization of the cloud for Learning Analytics privacy enhancement

Autor: Amo Filvà, Daniel, Fonseca Escudero, David, Alier Forment, Marc, García Peñalvo, Francisco José, Casany Guerrero, María José
Přispěvatelé: Universitat Politècnica de Catalunya. Departament d'Enginyeria de Serveis i Sistemes d'Informació, Universitat Politècnica de Catalunya. EduSTEAM - STEAM University Learning Research Group
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Popis: The debate on privacy issues in Learning Analytics processes has been going on for a long time. In academic terms, various researchers attempted to identify the origin of the problem, provide solutions, and propose alternatives. However, the problem is complex, not yet solved, and increasingly pressing and serious. We reflect on cloud computing technologies as a generator of privacy issues and new derivatives. We assume that the technology used in the cloud is aggravating the problem, not Learning Analytics itself. Considering data capitalism, we argue that it is hopelessly impossible to solve the privacy problem, nor even mitigate it, when educational institutions use data ubiquity services in the cloud. We point to the paradox of Learning Analytics as the in-compatibility factor with third-party cloud computing services, where the latter is the link to all the associated privacy issues. To mitigate privacy issues, we propose the deconstruction of cloud computing for its localization. The localization is the basis of a new concept related to the disconnection of educational institutions from the cloud. New technological perspectives, legal frameworks, and social, cultural, and political changes are required. © 2022 Copyright for this paper by its authors.
Databáze: OpenAIRE