Orchestration of learning activities through the integration of third-party services in IMS learning design

The range of applicable pedagogical models has increased with the adoption of the Information and Communication Technologies in the educational field. The so called educational modelling languages enable the orchestration of learning activities on distance education scenarios. It is possible, for example, to apply strategies that emphasise the relevance of an active participation of the subject and the interaction among the different actors of the learning process. Computer-mediated orchestration of learning courses can be extended beyong distance education scenarios to face-to-face experiences. The IMS Learning Design specification is the de facto standard educational modelling language. The application of the specification in the support of collaborative learning models or in the creation of adaptive learning material is a frequent topic in current research. However, the model has several limitations that hinder the practical adoption of the IMS Learning Design framework. Among these limitations, the lack of integration with thirdparty tools is an obstacle for the creation and deployment of student-centred learning courses, where the active participation implies the use of Web based tools. Distance and blended learning models are especially affected by this limitation. Another factor that prevents full adoption of the framework is the lack of flexibility of the model: the existing players play a previously created script and leave no room for teachers’ reaction to unexpected events. This dissertation proposes a solution for the previous problems without limiting the intrinsic benefits of the specification, such as interoperability and expressiveness. The adopted research methodology consists of three phases: characterisation of the problem, design and implementation of the solution, and experimental validation of the proposed model. The complete description of the problem has required a revision of the state of the art regarding IMS Learning Design and the design and deployment of several cases of study. The analysis of these cases has been centred in the study of the factors that affect the authoring, deployment and enactment phases of scripted learning courses. The documentation and publication of these experiences is one of the contributions of this dissertation. An extension of the IMS Learning Design framework is proposed as a solution of the described problem. The extension, called Generic Service Integration is platform independent and allows the integration of third-party tools in courses described by IMS Learning Design. The integration is enabled by the automation of administrative tasks such as the instantiation of external tools, and by the information exchange among the platforms that take part in the course. Thus, it is possible to include learning activities whose enactment requires the use of Web based tools without losing the intrinsic characteristics of IMS Learning Design. The framework proposed by Generic Service Integration has been implemented as an extension of GRAIL, the IMS Learning Design player in the .LRN Learning Management System. Such extension has allowed the design and deployment of cases of study in which tool integration played an essential role in the sequence of activities. The analysis of these experiences demonstrates the feasibility of the proposed model. Such feasibility tackles two facts: first, the expresiveness of the combination of IMS LD and GSI; second, the replicability and scalability with a high number of participants. -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------La aplicación de las Tecnologías de la Información y la Comunicación al ámbito del aprendizaje tiene como resultado la ampliación del abanico de posibilidades en lo que a modelos pedagógicos se refiere. La aparición de lenguajes de modelado educativo permite la orquestación de actividades en entornos de educación a distancia. Esto hace posible la ejecución de cursos en los que priman la participación activa del sujeto y la interacción entre los diferentes actores del proceso de aprendizaje. La orquestación de cursos guiada por ordenador no es exclusiva de la educación a distancia. En escenarios presenciales, por ejemplo, puede suponer una importante reducción de las tareas administrativas del profesorado. La especificación IMS Learning Design es el actual estándar de facto en el marco de los lenguajes de modelado educativo. Es frecuente la aparición de la especificación en las investigaciones más recientes, explorando su uso en el ámbito del trabajo colaborativo o en la creación de material adaptativo. Sin embargo, son varias las limitaciones que impiden una adopción práctica del esquema de trabajo propuesto por IMS Learning Design. Entre estas limitaciones, la falta de integración con herramientas de terceros dificulta la creación y el despliegue de cursos en los que el papel activo del alumno se refleje en el uso de herramientas basadas en la Web, especialmente en entornos de aprendizaje a distancia o semipresencial. Otro obstáculo importante es la falta de flexibilidad del modelo, ya que las herramientas de despliegue y ejecución de cursos se limitan a reproducir un guión previamente establecido, dejando escaso margen de actuación al profesorado. Esta tesis caracteriza los problemas mencionados y propone una solución factible que no limite las características propias de la especificación, como son su interoperabilidad y expresividad. Para ello, se ha seguido una metodología de trabajo compuesta de tres fases: caracterización del problema, definición e implementación de la solución, y validación experimental del modelo propuesto. Para la caracterización del problema se ha llevado a cabo un estudio del estado del arte con respecto a IMS Learning Design que se ha visto complementado con el diseño y despliegue de casos prácticos reales. En análisis de dichos casos prácticos se ha centrado en el estudio de los factores que afectan a las fases de autoría, despliegue y ejecución de los cursos. La documentación y posterior publicación de dichas experiencias supone por tanto una de las contribuciones de esta tesis. Tras la caracterización del problema, se propone una arquitectura que extiende la especificacióon IMS Learning Design. La arquitectura propuesta es independiente de la plataforma software que se utilice en el diseño y despliegue de cursos. Dicha arquitectura, que recibe el nombre de Generic Service Integration, permite la integración de herramientas de terceros en cursos guiados por IMS Learning Design. Esta integración se basa en la instanciación automática de herramientas externas y el intercambio de información entre las plataformas que intervienen en el curso. Así, se permite la inclusión de actividades que requieran el uso de herramientas basadas en la Web, sin que ello suponga una pérdida de las características propias de IMS Learning Design. El modelo propuesto, Generic Service Integration, ha sido implementado como una extensión de GRAIL, el reproductor de IMS Learning Design en .LRN. Dicha implementación ha permitido la puesta en marcha de casos de estudio en los que la integración de herramientas ha sido un elemento primordial de la secuencia de actividades de aprendizaje. El análisis de dichas experiencias demuestra la viabilidad del modelo propuesto. Esta viabilidad se refiere tanto a la capacidad expresiva de la combinación de IMS LD con GSI, como a su alta replicabilidad y escalabilidad con un número alto de participantes

Human Mobility and Application Usage Prediction Algorithms for Mobile Devices

Mobile devices such as smartphones and smart watches are ubiquitous companions of humans’ daily life. Since 2014, there are more mobile devices on Earth than humans. Mobile applications utilize sensors and actuators of these devices to support individuals in their daily life. In particular, 24% of the Android applications leverage users’ mobility data. For instance, this data allows applications to understand which places an individual typically visits. This allows providing her with transportation information, location-based advertisements, or to enable smart home heating systems. These and similar scenarios require the possibility to access the Internet from everywhere and at any time. To realize these scenarios 83% of the applications available in the Android Play Store require the Internet to operate properly and therefore access it from everywhere and at any time. Mobile applications such as Google Now or Apple Siri utilize human mobility data to anticipate where a user will go next or which information she is likely to access en route to her destination. However, predicting human mobility is a challenging task. Existing mobility prediction solutions are typically optimized a priori for a particular application scenario and mobility prediction task. There is no approach that allows for automatically composing a mobility prediction solution depending on the underlying prediction task and other parameters. This approach is required to allow mobile devices to support a plethora of mobile applications running on them, while each of the applications support its users by leveraging mobility predictions in a distinct application scenario. Mobile applications rely strongly on the availability of the Internet to work properly. However, mobile cellular network providers are struggling to provide necessary cellular resources. Mobile applications generate a monthly average mobile traffic volume that ranged between 1 GB in Asia and 3.7 GB in North America in 2015. The Ericsson Mobility Report Q1 2016 predicts that by the end of 2021 this mobile traffic volume will experience a 12-fold increase. The consequences are higher costs for both providers and consumers and a reduced quality of service due to congested mobile cellular networks. Several countermeasures can be applied to cope with these problems. For instance, mobile applications apply caching strategies to prefetch application content by predicting which applications will be used next. However, existing solutions suffer from two major shortcomings. They either (1) do not incorporate traffic volume information into their prefetching decisions and thus generate a substantial amount of cellular traffic or (2) require a modification of mobile application code. In this thesis, we present novel human mobility and application usage prediction algorithms for mobile devices. These two major contributions address the aforementioned problems of (1) selecting a human mobility prediction model and (2) prefetching of mobile application content to reduce cellular traffic. First, we address the selection of human mobility prediction models. We report on an extensive analysis of the influence of temporal, spatial, and phone context data on the performance of mobility prediction algorithms. Building upon our analysis results, we present (1) SELECTOR – a novel algorithm for selecting individual human mobility prediction models and (2) MAJOR – an ensemble learning approach for human mobility prediction. Furthermore, we introduce population mobility models and demonstrate their practical applicability. In particular, we analyze techniques that focus on detection of wrong human mobility predictions. Among these techniques, an ensemble learning algorithm, called LOTUS, is designed and evaluated. Second, we present EBC – a novel algorithm for prefetching mobile application content. EBC’s goal is to reduce cellular traffic consumption to improve application content freshness. With respect to existing solutions, EBC presents novel techniques (1) to incorporate different strategies for prefetching mobile applications depending on the available network type and (2) to incorporate application traffic volume predictions into the prefetching decisions. EBC also achieves a reduction in application launch time to the cost of a negligible increase in energy consumption. Developing human mobility and application usage prediction algorithms requires access to human mobility and application usage data. To this end, we leverage in this thesis three publicly available data set. Furthermore, we address the shortcomings of these data sets, namely, (1) the lack of ground-truth mobility data and (2) the lack of human mobility data at short-term events like conferences. We contribute with JK2013 and UbiComp Data Collection Campaign (UbiDCC) two human mobility data sets that address these shortcomings. We also develop and make publicly available a mobile application called LOCATOR, which was used to collect our data sets. In summary, the contributions of this thesis provide a step further towards supporting mobile applications and their users. With SELECTOR, we contribute an algorithm that allows optimizing the quality of human mobility predictions by appropriately selecting parameters. To reduce the cellular traffic footprint of mobile applications, we contribute with EBC a novel approach for prefetching of mobile application content by leveraging application usage predictions. Furthermore, we provide insights about how and to what extent wrong and uncertain human mobility predictions can be detected. Lastly, with our mobile application LOCATOR and two human mobility data sets, we contribute practical tools for researchers in the human mobility prediction domain

XXI Workshop de Investigadores en Ciencias de la Computación - WICC 2019: libro de actas

Trabajos presentados en el XXI Workshop de Investigadores en Ciencias de la Computación (WICC), celebrado en la provincia de San Juan los días 25 y 26 de abril 2019, organizado por la Red de Universidades con Carreras en Informática (RedUNCI) y la Facultad de Ciencias Exactas, Físicas y Naturales de la Universidad Nacional de San Juan.Red de Universidades con Carreras en Informátic

XXI Workshop de Investigadores en Ciencias de la Computación - WICC 2019: libro de actas

Trabajos presentados en el XXI Workshop de Investigadores en Ciencias de la Computación (WICC), celebrado en la provincia de San Juan los días 25 y 26 de abril 2019, organizado por la Red de Universidades con Carreras en Informática (RedUNCI) y la Facultad de Ciencias Exactas, Físicas y Naturales de la Universidad Nacional de San Juan.Red de Universidades con Carreras en Informátic

Knowledge and Management Models for Sustainable Growth

In the last years sustainability has become a topic of global concern and a key issue in the strategic agenda of both business organizations and public authorities and organisations. Significant changes in business landscape, the emergence of new technology, including social media, the pressure of new social concerns, have called into question established conceptualizations of competitiveness, wealth creation and growth. New and unaddressed set of issues regarding how private and public organisations manage and invest their resources to create sustainable value have brought to light. In particular the increasing focus on environmental and social themes has suggested new dimensions to be taken into account in the value creation dynamics, both at organisations and communities level. For companies the need of integrating corporate social and environmental responsibility issues into strategy and daily business operations, pose profound challenges, which, in turn, involve numerous processes and complex decisions influenced by many stakeholders. Facing these challenges calls for the creation, use and exploitation of new knowledge as well as the development of proper management models, approaches and tools aimed to contribute to the development and realization of environmentally and socially sustainable business strategies and practices

GVSU Press Releases, 2012

A compilation of press releases for the year 2012 submitted by University Communications (formerly News & Information Services) to news agencies concerning the people, places, and events related to Grand Valley State University

CIMODE 2016: 3º Congresso Internacional de Moda e Design: proceedings

O CIMODE 2016 é o terceiro Congresso Internacional de Moda e Design, a decorrer de 9 a 12 de maio de 2016 na cidade de Buenos Aires, subordinado ao tema : EM--‐TRAMAS. A presente edição é organizada pela Faculdade de Arquitetura, Desenho e Urbanismo da Universidade de Buenos Aires, em conjunto com o Departamento de Engenharia Têxtil da Universidade do Minho e com a ABEPEM – Associação Brasileira de Estudos e Pesquisa em Moda.info:eu-repo/semantics/publishedVersio