The Learners' User Classes in the TERENCE Adaptive Learning System

Nowadays, circa 10% of 7-11 olds turn out to be poor comprehenders: they demonstrate text comprehension difficulties, related to inference making, despite proficiency in low-level cognitive skills like word reading. To improve the reading comprehension of these children, TERENCE, a technology enhanced learning project, aims at stimulating inference-making about stories. In order to design and develop the TERENCE system, we use a user centred design approach that requires an in depth study of the system's main end-users, namely, its learners and educators. This paper reports on the specification of the user classes for the TERENCE learners by means of user-centred design field studies, the resulting global system architecture, and an example use case of the system, with few related GUI's snapshots.European Commision (EC). Funding FP7/SP1/ICT. Project Code: 25741

Pedagogy-Driven Smart Games for Primary School Children

TERENCE is an FP7 ICT European project, highly multi-disciplinary, that is developing an adaptive learning system for supporting poor comprehenders and their educators. Their learning materials are stories and games, explicitly designed for classes of primary schools poor comprehenders, where classes were created via an extensive analysis of the context of use and user requirements. The games are specialised into smart games, which stimulate inference-making for story comprehension, and relaxing games, which stimulate visual perception and which train the interaction with devices (e.g., PC and tablet PC). In this paper we focus on how we used the pedagogical underpinnings and the acquired requirements to design the games of the system

The Design of Learning Material for Poor Comprehenders: Lessons Learnt from Experts

TERENCE is an FP7 ICT European project that is developing an adaptive learning system for poor comprehenders and their educators. The learning material is made of stories and smart games for stimulating reading comprehension. The design of stories and smart games is also based on data collected from experts for the analysis of the context of use of the system, and is incrementally revised via evaluations of prototypes of stories and games, with domain experts of text comprehension or education as participants. In particular, since smart games are semi-automatically generated via artificial intelligence technologies, they contain mistakes that have to be fixed by experts of pedagogy before the games are given to learners. In this paper we focus on the design and evaluations of the TERENCE stories and smart games for poor comprehenders via lessons learnt with domain experts

The TERENCE Smart Games: Automatic Generation and Supporting Architecture

TERENCE is an FP7 ICT European project that is developing an adaptive learning system for supporting poor comprehenders and their educators. Its learning material are stories and games. The games are specialised into smart games, which stimulate inference-making for story comprehension, and relaxing games, which stimulate visual perception and not story comprehension. The paper focuses on smart games. It first shows the current prototypes, then it describes the TERENCE system architecture, thus it delves into the generation of smart games instances, by highlighting the role of the constraint-based module therein. Finally, it ends with short conclusions about the planned improvements.

The role of Artificial Intelligence and distributed computing in IoT applications

[EN]The exchange of ideas between scientists and technicians, from both academic and business areas, is essential in order to ease the development of systems which can meet the demands of today’s society. Technology transfer in this field is still a challenge and, for that reason, this type of contributions are notably considered in this compilation. This book brings in discussions and publications concerning the development of innovative techniques of IoT complex problems. The technical program focuses both on high quality and diversity, with contributions in well-established and evolving areas of research. Specifically, 10 chapters were submitted to this book. The editors particularly encouraged and welcomed contributions on AI and distributed computing in IoT applications.Financed by regional government of Castilla y León and FEDER funds

The role of Artificial Intelligence and Distributed computing in IoT applications

[ES] La serie «El rol de la inteligencia artificial y la computación distribuida en las aplicaciones IoT» contiene publicaciones sobre la teoría y aplicaciones de la computación distribuida y la inteligencia artificial en el Internet de las cosas. Prácticamente todas las disciplinas como la ingeniería, las ciencias naturales, la informática y las ciencias de la información, las TIC, la economía, los negocios, el comercio electrónico, el medio ambiente, la salud y las ciencias de la vida están cubiertas. La lista de temas abarca todas las áreas de los sistemas inteligentes modernos y la informática como: inteligencia computacional, soft computing incluyendo redes neuronales, inteligencia social, inteligencia ambiental, sistemas auto-organizados y adaptativos, computación centrada en el ser humano y centrada en el ser humano, sistemas de recomendación, control inteligente, robótica y mecatrónica, incluida la colaboración entre el ser humano y la máquina, paradigmas basados en el conocimiento, paradigmas de aprendizaje, ética de la máquina, análisis inteligente de datos, gestión del conocimiento, agentes inteligentes, toma de decisiones inteligentes y apoyo, seguridad de la red inteligente, gestión de la confianza, entretenimiento interactivo, inteligencia de la Web y multimedia. Las publicaciones en el marco de «El rol de la inteligencia artificial y la computación distribuida en las aplicaciones IoT» son principalmente las actas de seminarios, simposios y conferencias. Abarcan importantes novedades recientes en la materia, tanto de naturaleza fundacional como aplicable. Un importante rasgo característico de la serie es el corto tiempo de publicación. Esto permite una rápida y amplia difusión de los resultados de las investigaciones[EN] The series «The Role of Artificial Intelligence and Distributed Computing in IoT Applications» contains publications on the theory and applications of distributed computing and artificial intelligence in the Internet of Things. Virtually all disciplines such as engineering, natural sciences, computer and information sciences, ICT, economics, business, e-commerce, environment, health and life sciences are covered. The list of topics covers all areas of modern intelligent systems and computer science: computational intelligence, soft computing including neural networks, social intelligence, ambient intelligence, self-organising and adaptive systems, human-centred and people-centred computing, recommendation systems, intelligent control, robotics and mechatronics including human-machine collaboration, knowledge-based paradigms, learning paradigms, machine ethics, intelligent data analysis, knowledge management, intelligent agents, intelligent decision making and support, intelligent network security, trust management, interactive entertainment, web intelligence, and multimedia. The publications in the framework of «The Role of Artificial Intelligence and Distributed Computing in IoT Applications» are mainly the proceedings of seminars, symposia and conferences. They cover important recent developments in the field, whether of a foundational or applicable character. An important feature of the series is the short publication time. This allows for the rapid and wide dissemination of research results

Towards a fuzzy domain ontology extraction method for adaptive e-learning

With the widespread applications of electronic learning (e-Learning) technologies to education at all levels, increasing number of online educational resources and messages are generated from the corresponding e-Learning environments. Nevertheless, it is quite difficult, if not totally impossible, for instructors to read through and analyze the online messages to predict the progress of their students on the fly. The main contribution of this paper is the illustration of a novel concept map generation mechanism which is underpinned by a fuzzy domain ontology extraction algorithm. The proposed mechanism can automatically construct concept maps based on the messages posted to online discussion forums. By browsing the concept maps, instructors can quickly identify the progress of their students and adjust the pedagogical sequence on the fly. Our initial experimental results reveal that the accuracy and the quality of the automatically generated concept maps are promising. Our research work opens the door to the development and application of intelligent software tools to enhance e-Learning

Horizon Report Europe - 2014 Schools Edition

The NMC Horizon Project from the New Media Consortium is a long-term investigation launched in 2002 that identifies and describes emerging technologies likely to have a large impact over the coming five years in education around the globe. The NMC Horizon Report Europe: 2014 Schools Edition, the first of its kind for Europe, examines six key trends, six significant challenges and six important developments in educational technology that are very likely to impact educational change processes in European schools over the next five years (2014-2018). The topics within each section were carefully selected by the Horizon Project Europe Expert Panel, a body of 53 experts in European education, technology, and other fields. They come from 22 European countries, as well as international organisations and European networks. Throughout the report, references and links are made to more than 150 European publications (reports, articles, policy documents, blog posts etc.), projects (both EU-funded and national initiatives) and various policy initiatives from all over Europe. The Creative Classrooms multidimensional framework, developed by European Commission’s JRC-IPTS on behalf of DG EAC, was used for analysing the trends, challenges and technologies impacting European schools over the next five years. The analysis reveals that a systemic approach is needed for integrating new technologies in European schools and impacting educational change over the next five years.JRC.J.3-Information Societ

Recommender systems based on hybrid models

[EN]Recommender Systems (RSs) play a very important role in web navigation, ensuring that the users easily find the information they are looking for. Today’s social networks contain a large amount of information and it is necessary that they employ mechanism that will guide users to the information they are interested in. However, to be able to recommend content according to user preferences, it is necessary to analyse their profiles and determine their preferences. The present study presents the work related to different recommender systems focused on two different hybrid models. Both of them are using a Case-Based Reasoning (CBR) system combined with the training of an Artificial Intelligence (AI) algorithm. First, some information is analyzed and trained with an AI algorithm in order to determine relevant patters hidden on the information. Then, the CBR system extends the system using a series of metrics and similar past cases to decide whether the recommendation is likely to be recommended to a user. Finally, the last step on the CBR is to propose recommendations to the final user, whose job is to validate or reject the proposal feeding the cases database