The influence of transparency on self-evaluation as part of the university accreditation process in Peru.

In order to show the choice of transparency as the guiding principle of the accreditation process, the article evaluates its influence on the fundamental subprocess of self-evaluation, thereby confirming that transparency is an essential tool for continuous improvement of academic processes and those of educational quality management. It fosters educational innovation and permits the sustainability of the continuous accreditation process over time, resulting in greater probabilities of university self-regulation through systemization of the process, with the objective of continuous improvement of university degree programs. The article analyzes the influence of transparency on each activity of the self-evaluation process according to the Peruvian accreditation model prepared under the total quality approach, as a reference for other accreditation models, proposing concrete transparency actions and evaluating its influence on the stakeholder groups in the self-evaluation process, as well as on the efficiency and effectiveness of the process. It is concluded that transparency has a positive influence on the training of human capital and the formation of the university?s organizational culture, facilitating dissemination, understanding and involvement of the stakeholder groups in the continuous improvement of accreditation activities and increasing their acceptance of change and commitment to the process. It is confirmed that transparency contributes toward increasing the efficiency index of the self-evaluation process by reducing operating costs through adequate, accessible, timely contribution of information by the stakeholders and through the optimization of the time spent gathering relevant information. In addition, it is concluded that transparency contributes toward increasing the effectiveness index of self-evaluation by facilitating the achievement of its objectives through synthetic, useful, reliable interpretation of the education situation and the formulation of feasible improvement plans based on the adequacy, relevance, visibility, pertinence and truthfulness of the information analyzed.

Security needs: Some considerations about its integration into the Self-Determination-Theory (SDT)

According to Self-determination Theory (SDT), there are only three psychological needs - competence, autonomy and relatedness - truly fundamental and essential for human being?s health and well-being, which can be satisfied by individuals while engaging in a wide variety of behaviors that may differ among individuals and be differentially manifest in different cultures. However, a number of questions have been raised about SDT?s contention that there are only those three basic psychological needs. The present study discusses the possibility that the security need should be considered as a basic need and its relation to the accepted three basic psychological needs. Using the Cultural Theory framework the degree of satisfaction of the basic needs, depending on the type of culture, is also presented.

A language exchange program: sustainability innovation in language and culture engagement

Spanish Educational Laws have been promoting the widespread use of English; as a result, Spanish Uni versities are looking for ways to give students more international training in order to prepare them for a future that will increasingly involve global problems and partnerships. Therefore, the Polytechnic University of Madrid, Spain (UPM), and the University of British Columbia, Okanagan, Canada (UBCO) have come together to offer opportunities for international collaboration and learning, thus facilitating virtual encounters among Spanish and Canadian students. The Language Exchange Program between the UPM and UBCO acts as a model for sustainability innovation in language and culture engagement as the students can interact with native speakers in communication tasks. This interdisciplinary initiative supports the latest methodological principles observed in the Common European Framework for Languages, such as autonomous and life-long learning, self-assessment and peer-assessment as well as the incorporation of new technologies to the learning process. Additionally the ‘virtual’ mobility is provided at no extra cost. This article presents the preliminary results of two virtual exchange programs that have been offering varied forms of study which are venue-independent, and have clearly expanded the range of scenarios for the students on both sides by promoting collaborative work and cultural exchange.

A language exchange program: sustainability innovation in language and culture engagement

The Language Exchange Program between the UPM and UBCO acts as a model for sustainability innovation in language and culture engagement as the students can interact with native speakers in communication tasks. This interdisciplinary initiative supports the latest methodological principles observed in the Common European Framework for Languages [1], such as autonomous and lifelong learning, self-assessment and peer-assessment as well as the incorporation of new technologies to the learning process

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure (versión actualizada)

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.