Educational Recommender Systems (ERSs), intelligent tutoring systems that adapt their pedagogical recommendations to each student, are becoming increasingly common. Context-Sensitive Affective Educational Recommender Systems (CSAERSs) personalize the recommendations according to a learning context with multiple dimensions, including the affective dimension and the personality traits of the user. To date, in the field of educational technology, there is little or no research that focuses on offering context-sensitive, personalized, psycho-pedagogical affective support to distance-learning students in real time. Nor do there seem to be any proposals for approaches to the knowledge engineering (term which encompasses knowledge acquisition and knowledge representation) of these systems, in which the relation between the user and his or her context is crucial. There is little work on a systematic approach to the requirements-elicitation phase and to the use of ontologies in the development and validation of ERSs, in general, and CSAERSs, in particular. In this article, we report on a student-centred requirements-elicitation methodology that uses psycho-pedagogical theatre in combination with student surveys. We then illustrate its application in the design and validation of an ontology, together with a semantic-similarity function, that could serve as the nucleus of a CSAERS.

The United Nations (UN) 2030 Agenda and other movements toward setting global goals such as the Paris Agreement and the European Green Deal/U.S. Green New Deal are laying the groundwork for a transformation beyond purely market-based economics toward sustainability and inclusiveness [1], in which technological innovation and, in particular, artificial intelligence (AI) can play a central role. The European Union (EU) is committed to the 2030 Agenda and the sustainable development goals (SDGs), which the UN itself has recognized cannot be achieved without a people-focused, science-based, digital revolution [2]. This commitment to the 2030 Agenda should entail promoting an inclusive and sustainable AI strategy, rather than a strategy with a narrow focus on competitiveness [3], [4]. In order for AI to contribute to achieving the SDGs, a systemic approach to the development of AI solutions is required [5]-[9]. Conversely, the SDGs provide an ideal framework to test the desirability of AI solutions [10]. Europe's multicultural character and its framework of international collaboration give it a head start toward becoming a global reference in the promotion of an inclusive and sustainable AI. Sharing the experiences and practices of such a European AI could make a significant contribution to achieving the SDGs.

En este artículo presentamos las potenciales contribuciones de la Inteligencia Artificial (IA) a un desarrollo sostenible y equitativo, respetuoso con los derechos humanos, frente a sus potenciales riesgos. Argumentamos cómo un enfoque particular de la I+D, y por ende de la educación de los futuros profesionales, podría conferir a esta tecnología un papel decisivo en la consecución de los Objetivos de Desarrollo Sostenible de Naciones Unidas. En particular, proponemos la metodología del Aprendizaje-Servicio como instrumento pedagógico para la educación de ingenieros de la tecnología inteligente comprometidos con la Agenda 2030. Ilustramos también nuestra experiencia de Aprendizaje-Servicio virtual en el contexto de un proyecto de innovación docente impulsado por el grupo COETIC ("Innovación docente para el desarrollo de competencias éticas y cívicas, y metodologías comunitarias en educación superior") de la Universidad Nacional de Educación a Distancia de España (UNED). En este proyecto, alumnos del máster universitario en investigación en IA de la UNED se implican en un proceso de ingeniería de desarrollo de entornos de aprendizaje virtuales inteligentes sensibles al contexto cultural para las universidades africanas colaboradoras (universidades de Strathmore, Kenia; Porto Novo, Benin; y Dschang, Camerún), al tiempo que proporcionan prácticas de español hablado a estudiantes de estas universidades.

The last few years have seen a large number of initiatives on artificial intelligence (AI) ethics: intergovernmental-institution initiatives such as “Ethics Guidelines for Trustworthy AI” from the high-level expert group on AI of the European Commission [1] or the Organisation for Economic Cooperation and Development (OECD) Council Recommendation on Artificial Intelligence [2], government initiatives such as that of the U.K. Parliament Select Committee on Artificial Intelligence [3], industry initiatives on AI ethical codes such as those of Google, IBM, Microsoft, and Intel, academic initiatives such as the Montreal declaration for the responsible development of AI [4], the Stanford University 100 Year Study on AI [5] or the Alan Turing Institute's “Understanding Artificial Intelligence Ethics and Safety” [6], and finally professional body initiatives such as the IEEE Global Initiative on Ethics of Autonomous/Intelligent Systems (A/IS) [7]. These initiatives, while acknowledging the potential of A/IS technologies to contribute to global socioeconomic solutions, highlight the increasing challenges posed by these technologies in the ethical, moral, legal, humanitarian, and sociopolitical domains.

An unexpected outcome from an open project to develop a ‘chaotic’ compiler for ANSI C is described here: a trace information entropy calculus for stochastically compiled programs. A stochastic compiler produces randomly different object codes every time it is applied to the same source code. This calculus quantifies the entropy introduced into run-time program traces by a compiler that aims for the maximal possible entropy, furnishing a definition and proof of security for encrypted computing (Turing-complete computation in which data remains in encrypted form throughout), where the status was formerly unknown.

We propose a semi-automatic method for the generation of educational-competency maps from repositories of multiple-choice question responses, using Bayesian structural learning and data-mining techniques. We tested our method on a large repository of responses to multiple-choice exam questions from an undergraduate course in Languages and Automata Theory at Spain's national distance-learning university (UNED). We also draw up guidelines and best practices, with a view to defining an educational data-mining methodology and to contributing to the development of educational data-mining tools.

We propose a semi-automatic method for the generation of educational-competency maps from repositories of multiple-choice question responses, using Bayesian structural learning and data-mining techniques. We tested our method on a large repository of responses to multiple-choice exam questions from an undergraduate course in Languages and Automata Theory at Spain’s national distance-learning university (UNED). We also draw up guidelines and best practices, with a view to defining an educational data-mining methodology and to contributing to the development of educational data-mining tools.

Distributed systems programming (DSP) is an important subject in the Computer Engineering undergraduate degree. The use of a version of the SIMCAM simulator adapted to the educational context enabled our DSP students to exercise important facets of DSP that are otherwise difficult or impossible to incorporate in student activities. Analyzing and quantifying the assumed benefits of this educational intervention on student learning enables us to better adapt such interventions to student needs. To investigate the impact on student learning of this novel use of a simulator we analyze both the course-assessment results and the constructors of the technology acceptance model, the latter via an initial survey of student perceptions carried out at the beginning of the course and another carried out after completing the simulator-based assignment. We observe, in particular, an improvement in the overall grades between the target year and those of the year previous to the simulator introduction. Moreover, other statistical findings are also of interest.

El Aprendizaje-Servicio Virtual (ApSV) es el Aprendizaje-Servicio (ApS) mediado por las TIC (Tecnologías de la Información y la Comunicación) –tanto para la prestación del servicio como para el apoyo, monitorización y evaluación del aprendizaje por parte de los docentes− y concebido para situaciones en que la comunicación cara a cara entre estudiantes, profesores y beneficiarios del servicio no es posible. La experiencia ha demostrado que sería de gran interés disponer de una aplicación web para el soporte del ApSV (y, en general, de ApS). Presentamos aquí el desarrollo de dicha aplicación web: Virtu@l-ApS. Hasta la fecha, este proyecto de desarrollo de software se ha llevado a cabo en el marco de dos Proyectos de Fin de Grado colaborativos e interdisciplinares de la Universidad Nacional de Educación a Distancia (UNED), de los grados en Educación Social e Ingeniería Informática, respectivamente. Aunque la versión de la aplicación web actualmente disponible carece de importantes funcionalidades, la experiencia de su desarrollo ha sido extremadamente útil, en particular, para la clarificación de los requisitos de una aplicación real, completamente operativa, que esperamos contribuya al soporte y la expansión del ApS en la Enseñanza Superior en España.

espanolEl grupo de innovacion docente de la para el desarrollo de la Competencia Etica y Civica y las metodologias basadas en la comunidad en la educacion superior (COETIC), incluye entre sus objetivos estrategicos el desarrollo de herramientas no solo metodologicas sino tambien tecnologicas para el soporte del Aprendizaje- Servicio Virtual (ApSV). Este recurso pedagogico requiere la mediacion de las TIC, tanto para la prestacion de los servicios como para el apoyo al aprendizaje, y su seguimiento y evaluacion por parte de los docentes. En este articulo, presentamos los avances de COETIC en este terreno, concretados en una aplicacion web para el soporte del ApSV, Virtu@l-ApS. La aplicacion se ha desarrollado en el contexto de los Trabajos Fin de Grado colaborativos e interdisciplinares de dos alumnos de la UNED, de Educacion Social e Ingenieria Informatica, respectivamente. La especificacion de las funcionalidades se ha realimentado de las experiencias piloto de ApSV que COETIC ha impulsado e implementado en los tres ultimos cursos academicos en diferentes titulaciones de la UNED. En particular, la implantacion del ApSV en el master en Investigacion en Inteligencia Artificial (IA) Avanzada: fundamentos, metodos y aplicaciones; ha permitido entender las necesidades tecnologicas que plantea cuando implica procesos de ingenieria informatica. EnglishCOETIC, UNED Teaching Innovation Group for the Development of Ethical and Civic Competence and Community-Based Methodologies in Higher Education, includes among its strategic objectives the development of not only methodological, but also technological, tools for the support of Virtual Service Learning (VSL). This pedagogical resource requires the mediation of ICT, both for the provision of the services and for the learning support, as well as for the monitoring and evaluation of the learning by the teachers. In this article we present COETIC's advances in this field, embodied in a web application for the support of VSL, Virtu@l-VSL. The application has been developed in the context of two collaborative and interdisciplinary final undergraduate-degree projects, in Social Education and Computer benefitted from Engineering, respectively. The specification of the functionalities feedback from the pilot experiences in VSL that COETIC has promoted and implemented in the last three academic years in different degrees. In particular, the implementation of VSL in the Advanced Artificial Intelligence (AI): fundamentals, fethods and applications; has helped to clarify the technological needs of VSL that involves computer engineering processes.

El objetivo de este proyecto consiste en mitigar los problemas existentes para ejecutar aplicaciones distribuidas en las practicas de la asignatura Programacion de Sistemas Distribuidos. Para ello proponemos el uso del simulador SIMCAN, el cual ha sido validado contra arquitecturas reales. Concretamente, se propone adaptar este simulador, desarrollado en el contexto de la investigacion, para fines docentes. Seguidamente, se utilizara la version adaptada de SIMCAN en las practicas de la asignatura Programacion de Sistemas Distribuidos, del grado de Ingenieria de Computadores de la FDI/UCM.

What happens if a Mars lander takes a cosmic ray through the processor and thereafter 1 + 1=3 ? Coping with the fault is feasible but requires the numbers 2 and 3 to be treated as indistinguishable for the purposes of arithmetic, while as memory addresses they continue to access different memory cells. If a program is to run correctly in this altered environment it must be prepared to see address 2 sporadically access data in memory cell 3, which is known as ‘hardware aliasing’. This paper describes a programming discipline that allows software to run correctly in a hardware aliasing context, provided the aliasing is underpinned by hidden determinism.

A simple semantic model for the NRB logic of program verification is provided here, and the logic is shown to be sound and complete with respect to it. That provides guarantees in support of the logic's use in the automated verification of large imperative code bases, such as the Linux kernel source. 'Soundness' implies that no breaches of safety conditions are missed, and 'completeness' implies that symbolic reasoning is as powerful as model-checking here.

This paper reviews and offers some reflections on the current state and potential of expert systems (ESs) for human and sustainable development (HSD) in the context of developing countries (DCs). We propose a framework for the evaluation of ES development projects, and assess some significant recent applications drawn from three areas of relevance for HSD: health care, agriculture and water resource management. In the light of the foregoing we draw some conclusions and suggest some preliminary methodological guidelines to address the objective of a “barefoot” knowledge engineering for “appropriate” ESs, i.e., ESs that indeed meet HSD objectives in the context of DCs.

An 'open' certification process is characterised here that is not based on any central agency, but rather on the option for any party to confirm any part of the certification process at will. The model for this paradigm has been a distributed, piece-wise, semantic audit carried out on the Linux kernel source code using a lightweight formal method.Our goal is a technology that allows open source developers to receive formally backed certifications for their project, in quid pro quo exchanges of resources and expertise with other developers within an amorphous and anonymous cloud of volunteers. To help ensure the integrity of the results, identifying details such as subroutine and variable names are not included in the data sent for analysis, each part of the computation is repeated many times at different sites, and checkpoint information is generated that enables independent checks to be carried out without starting from scratch each time. (C) 2013 Elsevier B.V. All rights reserved.

An experiment in providing volunteer cloud computing support for automated audits of open source code is described here, along with the supporting theory. Certification and the distributed and piecewise nature of the underlying verification computation are among the areas formalised in the theory part. The eventual aim of this research is to provide a means for open source developers who seek formally backed certification for their project to run fully automated analyses on their own source code. In order to ensure that the results are not tampered with, the computation is anonymized and shared with an ad-hoc network of volunteer CPUs for incremental completion. Each individual computation is repeated many times at different sites, and sufficient accounting data is generated to allow each computation to be refuted.