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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.

In 1995, back when I was finishing my CS Engineering degree, the Barcelona School of Informatics started to use an intranet application called “Racó” [...]

In 2004, the Universitat Politècnica de Catalunya decided to change one of its critical and strategic information services: the online teaching support platform. An Open Source software, Moodle, was adopted and the previous proprietary software was abandoned. In 2020, the home confinement of the population due to the pandemic caused by COVID-19 has been a stress test for the entire university community, and very specifically by those responsible for providing the support of the online teaching support platform. The increase in activity and the prospect of the generalization of online assessment raised the concerns of possible scalability issues with the quiz functionality during the examination period. The solution applied involved using Moodle’s IMS LTI interoperability features to deploy a high-performance version of the Moodle Quizz Module As A Service (SaaS), to plug-and-play within the university’s LMS without drawing on its internal resources. This solution combined with a systems strategy, private cloud operations, internal communication and teacher training, solved this problem and successfully complete the assessment of the university course in a situation of confinement.

This paper presents a collaborative learning activity for courses in engineering degrees or master’s programs that cover the subject and skills of sustainability, social compromise, and ethics for engineering. The activity consists of performing a multidisciplinary analysis of a case of study, which presents a technology or innovation, to detect and debate possible issues and solutions. This learning activity is based on the PESTLE methodology that is used to analyze the political, economic, social, technological, legal, and environmental aspects of a technology or innovation. The PESTLE analysis is implemented using the jigsaw collaborative learning technique. This learning activity can be completed in two sessions of two hours. To validate its usefulness, the learning activity was applied for two semesters in a study on two courses: one in Informatics Engineering Degree and the other one in the Master Degree of Sustainability at the Universitat Politècnica de Catalunya, with very good results.

La Analítica del Aprendizaje (proveniente del término en inglés Learning Analytics) procesa los datos de los estudiantes, incluso los estudiantes menores de edad. El ciclo analítico consiste en recoger datos, almacenarlos durante largos períodos y utilizarlos para realizar análisis y visualizaciones. A mayor cantidad de datos, mejores resultados en el análisis. Este análisis puede ser descriptivo, predictivo e, incluso, prescriptivo, lo que implica la gestión, el tratamiento y la utilización de datos personales. El contexto educativo es, por lo tanto, muy sensible, a diferencia de los contextos individuales en los que el análisis se utiliza a voluntad. No está claro cómo están utilizando los datos de los estudiantes las empresas de tecnología que dan servicio en educación y a quiénes realmente se les beneficia, cómo esto afectará a los estudiantes en un futuro a corto y largo plazo, o qué nivel de privacidad o seguridad se aplica para proteger los datos de los estudiantes. Por consiguiente, y en relación con lo expuesto, el análisis de datos educativos implica un contexto sensible y de fragilidad en la gestión y análisis de datos personales de los estudiantes, incluidos menores, en el que hay que maximizar las precauciones. En esta revisión sistemática de la literatura se explora la importancia de la protección y seguridad de los datos personales en el campo de la educación mediante las promesas emergentes de los interesados en usar la tecnología blockchain. Los resultados denotan que es importante entender las implicaciones y riesgos derivados de usar tecnologías emergentes en educación, su relación con la sociedad y la legalidad vigente.

A significant number of universities where engineering is taught, acknowledge the importance of the social and environmental impact of the scientific and technological practice, as well as the ethical problems it presents, and the need to provide their students with courses covering this as a subject. This paper presents 29 years of teaching courses with the subject of social, environmental, and ethical issues to students of Informatics Engineering. The table contents and its evolution over the years will be analyzed, plus the different teaching strategies applied, with emphasis on the collaborative learning methodologies to facilitate critical thinking and debate. During the experience, the course incorporated the subject of History of Informatics which proved to fit in the course. While the subject of Ethics and Sustainability is increasingly being regarded as an important matter to learn by future ICT engineers, the courses covering it remain as optional in the curriculums. This should change.

The Covid-19 pandemic led Catalan universities to do all teaching and evaluation online from 11 March 2020 until the end of term on 30 July. Conventional universities made the transition to online teaching in just a few days and suddenly virtual platforms become the centre of interaction between lecturers and students. Data that were obtained from the virtual platforms gave extremely valuable information about what was being done in class. This paper analyses data taken from Atenea, the Moodle virtual platform at the Universitat Politècnica de Catalunya (UPC), during quarantine. The key indicators and a data analysis design for Moodle have been proposed, which reveal teaching developments at various levels (overall and at the centre and subject level). This is applied to study data from the UPC Moodle and the results are discussed. The methodology can be extrapolated to other universities with Moodle platforms because the UPC is a set of small campuses and centres.

Most educational software programs use and gather personal information and metadata from students. Additionally, most of the educational software programs are no longer operated by the learning institutions but are run by third-party agencies. This means that in the decade since 2020, information about students is stored and handled outside premises and control of learning institutions. The personal information about students and their activity while they interact with learning management systems and online learning tools is increasingly in custody of cloud computing platforms, software-as-a-service providers, and learning tool vendors. There is an increasing will to use all the data and metadata from the activity of the students for research, to develop education management strategies, pedagogy approaches, and develop behavior control tools or learning tools informed by behavior analysis from learning analytics. Many times, these studies lack the ethical and moral perspective. In addition, there is an increasing number of cases in which this information has leaked or has been used in a shady way. Additionally, this information will be around for a long time, tied to the future digital profiles of the students whose data has been leaked. This paper hypothesizes that there has been an ongoing process of technological evolution that leads to a loss of control over personal information, which makes it even more difficult to protect user confidentiality and ensuring privacy, that data surveillance has entered the world of education, and that the current legal frameworks are not enough to really protect the student’s personal information. The paper analyzes how this situation came to pass, and why this is wrong. We conclude with some proposals to address it from its different root dimensions: technical, cultural, legal, and organizational.

El artículo analiza la ética de la inteligencia artificial generativa (IAGen) en la educación superior desde un enfoque teórico-práctico. Se enmarca en la creciente relevancia de la enseñanza de la ética en tecnologías de la información y en su impacto en la sociedad. El objetivo principal es desarrollar un modelo formativo que integre la reflexión ética sobre la IAGen en la formación de ingenieros informáticos. Para ello, se emplea un estudio de caso basado en la asignatura Aspectos Sociales y Medioambientales de la Informática de la Universidad Politécnica de Cataluña, en la que se aplican los principios teóricos de la ética de la inteligencia artificial (IA) a partir de un caso de aplicación de IAGen en la propia asignatura. Se introducen varios ejemplos de sistemas de IAGen en el dominio de la IA aplicada a la educación. Uno de los ejemplos, desarrollado por los autores, utiliza un asistente de IA creado con el framework LAMB, que permite a los estudiantes analizar el caso propuesto mediante el método PESTLE (political, economic, social, technological, legal, and environmental) y el uso del asistente como experto. Con posterioridad, los estudiantes deben analizar un caso de estudio análogo en otro dominio. Los resultados sugieren que este enfoque teórico-práctico, en el que los conceptos abstractos de ética y seguridad de la IA se aterrizan en decisiones de aplicación específicas y en artefactos tecnológicos concretos, es efectivo para integrar la reflexión ética en la enseñanza de la ingeniería y subraya la necesidad de implementar enfoques multidisciplinares para abordar los desafíos éticos emergentes de la IA en la educación. This article examines the ethics of generative artificial intelligence (GenAI) in higher education from a theoretical and practical perspective. It reflects the growing importance of teaching ethics in information technology and its impact on society. Its aim is to develop a training model  integrates ethical reflection on GenAI into the education of computer engineering students. To achieve this, a case study is used based on the Social and Environmental Aspects of Computer Science module at the Universidad Politécnica de Cataluña, in which the theoretical principles of artificial intelligence (AI) ethics are applied through a case study of the use of GenAI within the course. Several examples of GenAI systems within AI applied to education are introduced. One of the examples, developed by the authors, involves an AI assistant built using the LAMB framework that enables students to analyse the proposed case using the PESTLE (political, economic, social, technological, legal, and environmental) method with the assistant acting as an expert. Students are then required to analyse a similar case study in another domain. The results suggest that this theoretical-practical approach, where abstract concepts of AI ethics and safety are grounded in specific decisions about application and concrete technological artefacts, effectively integrates ethical reflection into engineering education, highlighting the need for multidisciplinary approaches to address emerging ethical challenges in AI and education.

Este artículo analiza la integración de la inteligencia artificial generativa en educación desde una perspectiva crítica, histórica y ética. Se identifica una creciente preocupación por la opacidad de las herramientas de inteligencia artificial actuales, especialmente en sistemas de aprendizaje. El trabajo utiliza un enfoque basado en metáforas para entender cómo las narrativas tecnológicas influyen en la adopción de innovaciones educativas. Se revisan metáforas históricas en las tecnologías aplicadas a la educación, desde Multivac y Matrix hasta el Bazar del software libre y la App Store, y se proponen nuevas imágenes conceptuales que podrían aplicarse al contexto actual en el que la inteligencia artificial irrumpe en la educación. A partir de este análisis metafórico, se plantean siete principios éticos para una adopción segura de la inteligencia artificial generativa en educación, centrados en la privacidad, la alineación pedagógica, la supervisión humana y la transparencia tecnológica. Estos principios se ejemplifican con el entorno LAMB (Learning Assistant Manager and Builder), un marco de código abierto que permite diseñar asistentes de aprendizaje basados en inteligencia artificial de forma ética y contextualizada. Se presentan casos reales de aplicación de LAMB en educación superior, incluyendo una experiencia controlada con estudiantes que muestran mejoras significativas en autonomía y coherencia pedagógica. Finalmente, se destaca cómo LAMB encarna los principios éticos propuestos y responde a las metáforas críticas identificadas, ofreciendo un modelo de integración tecnológica centrado en la autonomía de los docentes, la alineación con los principios y prácticas de la institución educativa y el aprendizaje significativo de los estudiantes. This article examines the integration of generative artificial intelligence in education from a critical, historical, and ethical perspective. It highlights growing concerns about the opacity of current artificial intelligence tools, particularly in learning systems. The study adopts a metaphor-based approach to explore how technological narratives influence the adoption of educational innovations. It reviews historical metaphors used to describe educational technologies, from Multivac and Matrix to the free software Bazaar and the App Store, and proposes new conceptual frameworks that may better reflect the current context in which artificial intelligence is entering the educational sphere. Based on this metaphorical analysis, the article outlines seven fundamental ethical principles for the safe adoption of generative artificial intelligence in education, focusing on privacy, pedagogical alignment, human oversight, and technological transparency. These principles are illustrated through a practical application: the LAMB (Learning Assistant Manager and Builder) environment, an open-source software framework that enables the ethical and contextualized design of artificial intelligence-based learning assistants. The article presents real-world cases of LAMB implementation in higher education, including a controlled experience with students that demonstrates significant improvements in student autonomy and pedagogical coherence. Finally, it emphasizes how LAMB embodies the proposed ethical principles and responds to the identified critical metaphors, offering a model for technology integration centered on teacher autonomy, alignment with institutional values and practices, and meaningful student learning that prioritizes pedagogical control over technological determinism.