Intercomprendersi – Una experiencia de formación de docentes

Barbara Gramegna. Dipartimento Istuzione e Formazione Italiana Provincia di Bolzano (Italia)Recepción: 23/07/2018 | Aceptado: 30/04/2019Correspondencia a través de ORCID: Barbara Gramegna - 0000-0002-0237-2954This contribution presents a teacher-training program delivered by the Italian Educational Department in the Autonomous Province of Bolzano (Italy) centred on Intercomprehension theory. It was addressed to teachers in service with the aim of combining both purposes of plurilingual and intercultural education. Considered that linguistic competence is essential for developing knowledge in every school subject, the purpose of this training was to offer practical suggestions to become aware of how interlinguistic, receptive skills and decoding strategies can be applied in combination to facilitate comprehension tout court and to achieve mediation skills and language awareness.The paper offers some considerations about today´s language teaching/learning processes in schools and about the changing role of teachers. The third section introduces the concept of Intercomprehension and its value for teacher training. The paper focuses on a description of the phases of the teacher training program conducted in 2017. It illustrates briefly the context, the needs assessment process, the aims and contents. The fourth section provides a summary and analysis of participants´ feedback, with ideas for future developments and conclusive remarks.Resumen: Esta contribución presenta un programa de Intercomprensión docente impartido por el Departamento de Educación Italiano en la Provincia Autónoma de Bolzano (Italia) centrado en la teoría de la Intercomprensión. Se dirigía a los profesores en servicio con el fin de combinar los dos objetivos de la educación plurilingüe e intercultural. Considerando que la competencia lingüística es esencial para el desarrollo del conocimiento, el objetivo de esta formación era ofrecer sugerencias prácticas para mostrar cómo las habilidades interlingüísticas, receptivas y las estrategias de decodificación pueden ser aplicadas en combinación para facilitar la comprensión y para lograr las habilidades de mediación y la conciencia lingüística. El documento ofrece algunas consideraciones sobre los procesos de enseñanza/aprendizaje de idiomas en las escuelas y sobre el rol cambiante de los profesores. La tercera sección introduce el concepto de Intercomprensión y su valor para la formación del profesorado. El documento se centra en una descripción de las fases del programa llevado a cabo en el año 2017. Ilustra brevemente el contexto, el proceso de evaluación de las necesidades, los objetivos y los contenidos. La cuarta sección ofrece un resumen y un análisis de los comentarios de los participantes, con ideas para futuros desarrollos y las conclusiones

Could AI Democratise Education? Socio-Technical Imaginaries of an EdTech Revolution

Artificial Intelligence (AI) in Education has been said to have the potential for building more personalised curricula, as well as democratising education worldwide and creating a Renaissance of new ways of teaching and learning. Millions of students are already starting to benefit from the use of these technologies, but millions more around the world are not. If this trend continues, the first delivery of AI in Education could be greater educational inequality, along with a global misallocation of educational resources motivated by the current technological determinism narrative. In this paper, we focus on speculating and posing questions around the future of AI in Education, with the aim of starting the pressing conversation that would set the right foundations for the new generation of education that is permeated by technology. This paper starts by synthesising how AI might change how we learn and teach, focusing specifically on the case of personalised learning companions, and then move to discuss some socio-technical features that will be crucial for avoiding the perils of these AI systems worldwide (and perhaps ensuring their success). This paper also discusses the potential of using AI together with free, participatory and democratic resources, such as Wikipedia, Open Educational Resources and open-source tools. We also emphasise the need for collectively designing human-centered, transparent, interactive and collaborative AI-based algorithms that empower and give complete agency to stakeholders, as well as support new emerging pedagogies. Finally, we ask what would it take for this educational revolution to provide egalitarian and empowering access to education, beyond any political, cultural, language, geographical and learning ability barriers

Survey on Evaluation Methods for Dialogue Systems

In this paper we survey the methods and concepts developed for the evaluation of dialogue systems. Evaluation is a crucial part during the development process. Often, dialogue systems are evaluated by means of human evaluations and questionnaires. However, this tends to be very cost and time intensive. Thus, much work has been put into finding methods, which allow to reduce the involvement of human labour. In this survey, we present the main concepts and methods. For this, we differentiate between the various classes of dialogue systems (task-oriented dialogue systems, conversational dialogue systems, and question-answering dialogue systems). We cover each class by introducing the main technologies developed for the dialogue systems and then by presenting the evaluation methods regarding this class

Real-time generation and adaptation of social companion robot behaviors

Social robots will be part of our future homes. They will assist us in everyday tasks, entertain us, and provide helpful advice. However, the technology still faces challenges that must be overcome to equip the machine with social competencies and make it a socially intelligent and accepted housemate. An essential skill of every social robot is verbal and non-verbal communication. In contrast to voice assistants, smartphones, and smart home technology, which are already part of many people's lives today, social robots have an embodiment that raises expectations towards the machine. Their anthropomorphic or zoomorphic appearance suggests they can communicate naturally with speech, gestures, or facial expressions and understand corresponding human behaviors. In addition, robots also need to consider individual users' preferences: everybody is shaped by their culture, social norms, and life experiences, resulting in different expectations towards communication with a robot. However, robots do not have human intuition - they must be equipped with the corresponding algorithmic solutions to these problems. This thesis investigates the use of reinforcement learning to adapt the robot's verbal and non-verbal communication to the user's needs and preferences. Such non-functional adaptation of the robot's behaviors primarily aims to improve the user experience and the robot's perceived social intelligence. The literature has not yet provided a holistic view of the overall challenge: real-time adaptation requires control over the robot's multimodal behavior generation, an understanding of human feedback, and an algorithmic basis for machine learning. Thus, this thesis develops a conceptual framework for designing real-time non-functional social robot behavior adaptation with reinforcement learning. It provides a higher-level view from the system designer's perspective and guidance from the start to the end. It illustrates the process of modeling, simulating, and evaluating such adaptation processes. Specifically, it guides the integration of human feedback and social signals to equip the machine with social awareness. The conceptual framework is put into practice for several use cases, resulting in technical proofs of concept and research prototypes. They are evaluated in the lab and in in-situ studies. These approaches address typical activities in domestic environments, focussing on the robot's expression of personality, persona, politeness, and humor. Within this scope, the robot adapts its spoken utterances, prosody, and animations based on human explicit or implicit feedback.Soziale Roboter werden Teil unseres zukünftigen Zuhauses sein. Sie werden uns bei alltäglichen Aufgaben unterstützen, uns unterhalten und uns mit hilfreichen Ratschlägen versorgen. Noch gibt es allerdings technische Herausforderungen, die zunächst überwunden werden müssen, um die Maschine mit sozialen Kompetenzen auszustatten und zu einem sozial intelligenten und akzeptierten Mitbewohner zu machen. Eine wesentliche Fähigkeit eines jeden sozialen Roboters ist die verbale und nonverbale Kommunikation. Im Gegensatz zu Sprachassistenten, Smartphones und Smart-Home-Technologien, die bereits heute Teil des Lebens vieler Menschen sind, haben soziale Roboter eine Verkörperung, die Erwartungen an die Maschine weckt. Ihr anthropomorphes oder zoomorphes Aussehen legt nahe, dass sie in der Lage sind, auf natürliche Weise mit Sprache, Gestik oder Mimik zu kommunizieren, aber auch entsprechende menschliche Kommunikation zu verstehen. Darüber hinaus müssen Roboter auch die individuellen Vorlieben der Benutzer berücksichtigen. So ist jeder Mensch von seiner Kultur, sozialen Normen und eigenen Lebenserfahrungen geprägt, was zu unterschiedlichen Erwartungen an die Kommunikation mit einem Roboter führt. Roboter haben jedoch keine menschliche Intuition - sie müssen mit entsprechenden Algorithmen für diese Probleme ausgestattet werden. In dieser Arbeit wird der Einsatz von bestärkendem Lernen untersucht, um die verbale und nonverbale Kommunikation des Roboters an die Bedürfnisse und Vorlieben des Benutzers anzupassen. Eine solche nicht-funktionale Anpassung des Roboterverhaltens zielt in erster Linie darauf ab, das Benutzererlebnis und die wahrgenommene soziale Intelligenz des Roboters zu verbessern. Die Literatur bietet bisher keine ganzheitliche Sicht auf diese Herausforderung: Echtzeitanpassung erfordert die Kontrolle über die multimodale Verhaltenserzeugung des Roboters, ein Verständnis des menschlichen Feedbacks und eine algorithmische Basis für maschinelles Lernen. Daher wird in dieser Arbeit ein konzeptioneller Rahmen für die Gestaltung von nicht-funktionaler Anpassung der Kommunikation sozialer Roboter mit bestärkendem Lernen entwickelt. Er bietet eine übergeordnete Sichtweise aus der Perspektive des Systemdesigners und eine Anleitung vom Anfang bis zum Ende. Er veranschaulicht den Prozess der Modellierung, Simulation und Evaluierung solcher Anpassungsprozesse. Insbesondere wird auf die Integration von menschlichem Feedback und sozialen Signalen eingegangen, um die Maschine mit sozialem Bewusstsein auszustatten. Der konzeptionelle Rahmen wird für mehrere Anwendungsfälle in die Praxis umgesetzt, was zu technischen Konzeptnachweisen und Forschungsprototypen führt, die in Labor- und In-situ-Studien evaluiert werden. Diese Ansätze befassen sich mit typischen Aktivitäten in häuslichen Umgebungen, wobei der Schwerpunkt auf dem Ausdruck der Persönlichkeit, dem Persona, der Höflichkeit und dem Humor des Roboters liegt. In diesem Rahmen passt der Roboter seine Sprache, Prosodie, und Animationen auf Basis expliziten oder impliziten menschlichen Feedbacks an

Quality and Access in Lifelong Learning

Learner-directed choice is central to the process of educational achievemen

Practical Christianity: Religion in Jane Austen\u27s Novels

A beloved English novelist of the late eighteenth century, Jane Austen captures the attention and emotion of readers through timeless insights into the inner workings of the human heart as characters navigate society, family life, and love. Her novels’ attention to practical morality but reticence toward explicitly religious subject matter raises conjecture concerning the religion behind her values; however, Austen’s Christian upbringing, Anglican practice, and Christian values suggest a foundation of faith from which the morality in her novels emanates. In Sense and Sensibility, Pride and Prejudice, and Mansfield Park, Austen demonstrates her eighteenth-century Anglican worldview in the lives of her characters as they grow in virtue and good character