Parameter-based mechanism for unifying user interaction, applications and communication protocols

In the smart building control industry, creating a platform to integrate different communication protocols and ease the interaction between users and devices is becoming increasingly important. BATMP is a platform designed to achieve this goal. In this paper, the authors describe a novel mechanism for information exchange, which introduces a new concept, Parameter, and uses it as the common object among all the BATMP components: Gateway Manager, Technology Manager, Application Manager, Model Manager and Data Warehouse. Parameter is an object which represents a physical magnitude and contains the information about its presentation, available actions, access type, etc. Each component of BATMP has a copy of the parameters. In the Technology Manager, three drivers for different communication protocols, KNX, CoAP and Modbus, are implemented to convert devices into parameters. In the Gateway Manager, users can control the parameters directly or by defining a scenario. In the Application Manager, the applications can subscribe to parameters and decide the values of parameters by negotiating. Finally, a Negotiator is implemented in the Model Manager to notify other components about the changes taking place in any component. By applying this mechanism, BATMP ensures the simultaneous and concurrent communication among users, applications and devices.

Una propuesta de modelado del estudiante basada en ontologías y diagnóstico pedagógico-cognitivo no monótono

Los recientes avances tecnológicos han encontrado un potencial campo de explotación en la educación asistida por computador. A finales de los años 90 surgió un nuevo campo de investigación denominado Entornos Virtuales Inteligentes para el Entrenamiento y/o Enseñanza (EVIEs), que combinan dos áreas de gran complejidad: Los Entornos Virtuales (EVs) y los Sistemas de Tutoría Inteligente (STIs). De este modo, los beneficios de los entornos 3D (simulación de entornos de alto riesgo o entornos de difícil uso, etc.) pueden combinarse con aquéllos de un STIs (personalización de materias y presentaciones, adaptación de la estrategia de tutoría a las necesidades del estudiante, etc.) para proporcionar soluciones educativas/de entrenamiento con valores añadidos. El Modelo del Estudiante, núcleo de un SIT, representa el conocimiento y características del estudiante, y refleja el proceso de razonamiento del estudiante. Su complejidad es incluso superior cuando los STIs se aplican a EVs porque las nuevas posibilidades de interacción proporcionadas por estos entornos deben considerarse como nuevos elementos de información clave para el modelado del estudiante, incidiendo en todo el proceso educativo: el camino seguido por el estudiante durante su navegación a través de escenarios 3D; el comportamiento no verbal tal como la dirección de la mirada; nuevos tipos de pistas e instrucciones que el módulo de tutoría puede proporcionar al estudiante; nuevos tipos de preguntas que el estudiante puede formular, etc. Por consiguiente, es necesario que la estructura de los STIs, embebida en el EVIE, se enriquezca con estos aspectos, mientras mantiene una estructura clara, estructurada, y bien definida. La mayoría de las aproximaciones al Modelo del Estudiante en STIs y en IVETs no consideran una taxonomía de posibles conocimientos acerca del estudiante suficientemente completa. Además, la mayoría de ellas sólo tienen validez en ciertos dominios o es difícil su adaptación a diferentes STIs. Para vencer estas limitaciones, hemos propuesto, en el marco de esta tesis doctoral, un nuevo mecanismo de Modelado del Estudiante basado en la Ingeniería Ontológica e inspirado en principios pedagógicos, con un modelo de datos sobre el estudiante amplio y flexible que facilita su adaptación y extensión para diferentes STIs y aplicaciones de aprendizaje, además de un método de diagnóstico con capacidades de razonamiento no monótono. El método de diagnóstico es capaz de inferir el estado de los objetivos de aprendizaje contenidos en el SIT y, a partir de él, el estado de los conocimientos del estudiante durante su proceso de aprendizaje. La aproximación almodelado del estudiante propuesta ha sido implementada e integrada en un agente software (el agente de modelado del estudiante) dentro de una plataforma software existente para el desarrollo de EVIEs denominadaMAEVIF. Esta plataforma ha sido diseñada para ser fácilmente configurable para diferentes aplicaciones de aprendizaje. El modelado del estudiante presentado ha sido implementado e instanciado para dos tipos de entornos de aprendizaje: uno para aprendizaje del uso de interfaces gráficas de usuario en una aplicación software y para un Entorno Virtual para entrenamiento procedimental. Además, se ha desarrollado una metodología para guiar en la aplicación del esta aproximación de modelado del estudiante a cada sistema concreto.---ABSTRACT---Recent technological advances have found a potential field of exploitation in computeraided education. At the end of the 90’s a new research field emerged, the so-called Intelligent Virtual Environments for Training and/or Education (IVETs), which combines two areas of great complexity: Virtual Environments (VE) and Intelligent Tutoring Systems (ITS). In this way, the benefits of 3D environments (simulation of high risk or difficult-to-use environments, etc.) may be combined with those of an ITS (content and presentation customization, adaptation of the tutoring strategy to the student requirements, etc.) in order to provide added value educational/training solutions. The StudentModel, core of an ITS, represents the student’s knowledge and characteristics, and reflects the student’s reasoning process. Its complexity is even higher when the ITSs are applied on VEs because the new interaction possibilities offered by these environments must be considered as new key information pieces for student modelling, impacting all the educational process: the path followed by the student during their navigation through 3D scenarios; non-verbal behavior such as gaze direction; new types of hints or instructions that the tutoring module can provide to the student; new question types that the student can ask, etc. Thus, it is necessary for the ITS structure, which is embedded in the IVET, to be enriched by these aspects, while keeping a clear, structured and well defined architecture. Most approaches to SM on ITSs and IVETs don’t consider a complete enough taxonomy of possible knowledge about the student. In addition, most of them have validity only in certain domains or they are hard to be adapted for different ITSs. In order to overcome these limitations, we have proposed, in the framework of this doctoral research project, a newStudentModeling mechanism that is based onOntological Engineering and inspired on pedagogical principles, with a wide and flexible data model about the student that facilitates its adaptation and extension to different ITSs and learning applications, as well as a rich diagnosis method with non-monotonic reasoning capacities. The diagnosis method is able to infer the state of the learning objectives encompassed by the ITS and, fromit, the student’s knowledge state during the student’s process of learning. The proposed student modelling approach has been implemented and integrated in a software agent (the student modeling agent) within an existing software platform for the development of IVETs called MAEVIF. This platform was designed to be easily configurable for different learning applications. The proposed student modeling has been implemented and it has been instantiated for two types of learning environments: one for learning to use the graphical user interface of a software application and a Virtual Environment for procedural training. In addition, a methodology to guide on the application of this student modeling approach to each specific system has been developed.

Inter-organizational information systems adoption for service innovation in building sector

The building sector has experienced a significant decline in recent years in Spain and Europe as a result of the financial crisis that began in 2007. This drop accompanies a low penetration of information and communication technologies in inter-organizational oriented business processes. The market decrease is causing a slowdown in the building sector, where only flexible small and medium enterprises (SMEs) survive thanks to specialization and innovation in services, which allow them to face new market demands. Inter-organizational information systems (IOISs) support innovation in services, and are thus a strategic tool for SMEs to obtain competitive advantage. Because of the inherent complexity of IOIS adoption, this research extends Kurnia and Johnston's (2000) theoretical model of IOIS adoption with an empirical model of IOIS characterization. The resultant model identifies the factors influencing IOIS adoption in SMEs in the building sector, to promote further service innovation for competitive and collaborative advantages. An empirical longitudinal study over six consecutive years using data from Spanish SMEs in the building sector validates the model, using the partial least squares technique and analyzing temporal stability. The main findings of this research are the four ways an IOIS might contribute to service innovation in the building sector. Namely: a) improving client interfaces and the link between service providers and end users; b) defining a specific market where SMEs can develop new service concepts; c) enhancing the service delivery system in traditional customer?supplier relationships; and d) introducing information and communication technologies and tools to improve information management.