Protected Users: A Moodle Plugin To Improve Confidentiality and Privacy Support through User Aliases

Abstract

The privacy policies, terms, and conditions of use in any Learning Management System (LMS) are one-way contracts. The institution imposes clauses that the student can accept or decline. Students, once they accept conditions, should be able to exercise the rights granted by the General Data Protection Regulation (GDPR). However, students cannot object to data processing and public profiling because it would be conceived as an impediment to teachers to execute their work with normality. Nonetheless, regarding GDPR and consulted legal advisors, a student could claim identity anonymization in the LMS, if adequate personal justifications are provided. Per contra, the current LMSs do not have any functionality that enables identity anonymization. This is a big problem that generates undesired situations which urgently requires a definitive solution. In this work, we surveyed students and teachers to validate the feasibility and acceptance of using aliases to anonymize their identity in LMSs as a sustainable solution to the problem. Considering the positive results, we developed a user-friendly plugin for Moodle that enables students’ identity anonymization by the use of aliases. This plugin, presented in this work and named Protected users, is publicly available online at GitHub and published under GNU General Public License.

Estudio exploratorio en iberoamérica sobre procesos de enseñanza-aprendizaje y propuesta de evaluación en tiempos de pandemia

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Avoiding the Dark Side of Digital Transformation in Teaching. An Institutional Reference Framework for eLearning in Higher Education

“…Fortunately, digital teaching introduces more data management capabilities [22], which might introduce more transparency and better decision-making processes for teaching, and for academic improvement. However, these data-based procedures require the definition of an ethical behaviour, in order to define trusted analytics actions that provide enough guarantees about security and privacy [23,24] for any involved person. Further, this will help avoid any dark side practices derived from the technological ecosystem [25] interfaces.…”

Smart Learning

“…The base for a smart learning system is in data and the needed analytics processes [14]. However, despite the potential advantages associated with automatic analysis of educational data, important questions arise, primarily related to the ethical and privacy [15,16] aspects of the teaching-learning process.…”