Módulo VII.2. Intervención temprana y aplicación de recursos inteligentes. Intelligent personal assistants.

Este módulo plantea los elementos básicos para entender en qué consisten y cómo funcionan a un nivel abstracto los bots, entendidos como asistentes personales inteligentes. Mostrando además a su posible uso y utilidad en la rama de salud, y apuntando a sus futuras aplicaciones en la atención temprana.“Specialized and updated training on supporting advance technologies for early childhood education and care professionals and graduates”, eEarlyCare-T, reference 2021-1-ES01-KA220-SCH-000032661, is co-financed by the European Union's Erasmus+ programme, line KA220 Strategic Partnerships Scholar associations

Refactorización sobre Programación Genérica en Lenguajes Orientados a Objetos

En el desarrollo del software, éste se degrada produciéndose la entropía software. Una de las labores fundamentales para su eliminación, es el mantenimiento perfectivo, y en particular, la refactorización. La independencia del lenguaje en la definición e implementación de refactorizaciones, así como la programación genérica en refactorización son dos importantes líneas abiertas de investigación en este campo. Con el objetivo de lograr cierta independencia en su definición e implementación se propone un metamodelo para la definición de los conceptos básicos y una plantilla para su definición, junto con un modelo de caracterización y proceso. Posteriormente se describe un nuevo catálogo de refactorizaciones en genericidad y se propone una arquitectura basada en frameworks. Finalmente se valida la solución sobre el lenguaje Java, construyendo un prototipo. En resumen, se aporta un nuevo enfoque a la hora de abordar las refactorizaciones, mejorando algunas de las deficiencias detectadasDepartamento de Informátic

Herramienta de simulación para la realización de pruebas en la gestión de red basada en SNMP

En este artículo se expone una experiencia realizada en la asignatura Trabajo Fin de Carrera en la que se plantea como objetivo la utilización de dispositivos simulados de testeo en la gestión de red basada en el modelo Simple Network Management Protocol (SNMP) para que el alumno pruebe los prototipos implementados. La herramienta de simulación suministrada al alumno será configurada en función de los requisitos del prototipo a desarrollar y generará los necesarios informes para que éste los utilice como guía a la hora de decidir qué soluciones tomar en cada momento. Como resultado obtendrá una mayor capacidad de resolución de problemas y un mayor rendimiento en la evolución de su implementación.Peer Reviewe

Using Advanced Learning Technologies with University Students: An Analysis with Machine Learning Techniques

The use of advanced learning technologies (ALT) techniques in learning management systems (LMS) allows teachers to enhance self-regulated learning and to carry out the personalized monitoring of their students throughout the teaching–learning process. However, the application of educational data mining (EDM) techniques, such as supervised and unsupervised machine learning, is required to interpret the results of the tracking logs in LMS. The objectives of this work were (1) to determine which of the ALT resources would be the best predictor and the best classifier of learning outcomes, behaviours in LMS, and student satisfaction with teaching; (2) to determine whether the groupings found in the clusters coincide with the students’ group of origin. We worked with a sample of third-year students completing Health Sciences degrees. The results indicate that the combination of ALT resources used predict 31% of learning outcomes, behaviours in the LMS, and student satisfaction. In addition, student access to automatic feedback was the best classifier. Finally, the degree of relationship between the source group and the found cluster was medium (C = 0.61). It is necessary to include ALT resources and the greater automation of EDM techniques in the LMS to facilitate their use by teachers.This research was funded by the MINISTERIO DE CIENCIA E INNOVACIÓN, grant number PID2020-117111RB-I00

Evaluation of Functional Abilities in 0–6 Year Olds: An Analysis with the eEarlyCare Computer Application

The application of Industry 4.0 to the field of Health Sciences facilitates precise diagnosis and therapy determination. In particular, its effectiveness has been proven in the development of personalized therapeutic intervention programs. The objectives of this study were (1) to develop a computer application that allows the recording of the observational assessment of users aged 0–6 years old with impairment in functional areas and (2) to assess the effectiveness of computer application. We worked with a sample of 22 users with different degrees of cognitive disability at ages 0–6. The eEarlyCare computer application was developed with the aim of allowing the recording of the results of an evaluation of functional abilities and the interpretation of the results by a comparison with "normal development". In addition, the Machine Learning techniques of supervised and unsupervised learning were applied. The most relevant functional areas were predicted. Furthermore, three clusters of functional development were found. These did not always correspond to the disability degree. These data were visualized with distance map techniques. The use of computer applications together with Machine Learning techniques was shown to facilitate accurate diagnosis and therapeutic intervention. Future studies will address research in other user cohorts and expand the functionality of their application to personalized therapeutic programs.Vice-rectorate for Research and Knowledge Transfer of the University of Burgos for making the development of the software possible through the VI Edition of the Call for Proofs of Concept: Impulse for the valorization and marketing of research results (2018–2019) and VII Edition of the Call for Proofs of Concept: Impulse for the valorization and marketing of research results (2019–2020)

Monitoring Students at the University: Design and Application of a Moodle Plugin

Early detection of at-risk students is essential, especially in the university environment. Moreover, personalized learning has been shown to increase motivation and lower student dropout rates. At present, the average dropout rates among students following courses leading to the award of Spanish university degrees are around 18% and 42.8% for presential teaching and online courses, respectively. The objectives of this study are: (1) to design and to implement a Modular Object-Oriented Dynamic Learning Environment (Moodle) plugin, “eOrientation”, for the early detection of at-risk students; (2) to test the effectiveness of the “eOrientation” plugin on university students. We worked with 279 third-year students following health sciences degrees. A process for extracting information records was also implemented. In addition, a learning analytics module was developed, through which both supervised and unsupervised Machine Learning techniques can be applied. All these measures facilitated the personalized monitoring of the students and the easier detection of students at academic risk. The use of this tool could be of great importance to teachers and university governing teams, as it can assist the early detection of students at academic risk. Future studies will be aimed at testing the plugin using the Moodle environment on degree courses at other universities.Consejería de Educación de la Junta de Castilla y León (Spain) (Department of Education of the Junta de Castilla y León), grant number BU032G19, and grants from the University of Burgos for the dissemination and the improvement of teaching innovation experiences of the Vice-Rectorate of Teaching and Research Staff, the Vice-Rectorate for Research and Knowledge Transfer, 2020, and the Departamento de Ciencias de la Salud the University of Burgos (Spain)

Uso de herramientas para la adquisición de competencias transversales asociadas al desarrollo y mantenimiento de software

Las herramientas de control de versiones y planificación de tareas permiten monitorizar y recoger información sobre el proceso de desarrollo software. En este trabajo se presenta la utilización de este tipo de herramientas en asignaturas relacionadas con este campo. La idea no es tanto utilizar las herramientas como contenido per se de las asignaturas, sino servirse de ellas para fomentar y evaluar la adquisición de ciertas competencias transversales relacionadas con esas asignaturas. El presente trabajo selecciona esas competencias, estudia las posibles herramientas, su ámbito de utilización y conveniencia, y finaliza con el análisis del impacto de las herramientas en las competencias transversales seleccionadas a través de encuestas a los alumnos.Peer Reviewe

Proceso de gestión de trabajos fin de carrera

El desarrollo de trabajos final de carrera en las actuales titulaciones de informática es una de las materias fundamentales a la conclusión de los estudios. En las propuestas de grado y máster este punto sigue siendo fundamental, no existiendo apenas discusión en la necesidad de realizar un proyecto donde se aglutinen todos los conocimientos y competencias, que han sido adquiridos a lo largo de los estudios realizados. En este trabajo, se propone un modelo de gestión de la asignatura dentro de un contexto universitario, aplicando buenas prácticas de ingeniería del software: monitorización, control de proceso, revisiones, evaluación y medición. A partir de dicho modelo se describe una herramienta que lo automatiza, y se muestran dos casos de estudio resultado de su aplicación. El primero muestra los productos obtenidos de la aplicación del proceso. El segundo compara los resultados al utilizar la herramienta de evaluación entre trabajos de dos asignaturas distintas de proyectos: la de ingeniería y la de ingeniería técnica en informática.Peer Reviewe

A Systematic Review of the Use of T-Pattern and T-String Analysis (TPA) With Theme: An Analysis Using Mixed Methods and Data Mining Techniques

In recent years, research interest in human and non-human behavioral analysis has increased significantly. One key element in the resulting studies is the use of software that facilitates comparative analysis of behavioral patterns, such as using T-Pattern and T-String analysis -TPA- with THEME. Furthermore, all these studies use mixed methods research. Results from these studies have indicated a certain amount of similarity between the biological, temporal, and spatial patterns of human social interactions and the interactions between the contents of their constituent cells. TPA has become an important, widely-used technique in applied behavioral science research. The objectives of the current review were: (1) To identify the results of research over the last 4 years related to the concepts of T-Pattern, TPA, and THEME, since it is in this period in which more publications on these topics have been detected (2) To examine the key concepts and areas in the selected articles with respect to those concepts, applying data and text mining techniques. The results indicate that, over the last 4 years, 20% of the studies were laboratory focused with non-humans, 18% were in sports environments, 9% were in psychological therapy environments and 9% were in natural human contexts. There were also indications that TPA is beginning to be used in workplace environments, which is a very promising setting for future research in this area

Clustering extension of MOVICAB-IDS to identify SNMP community searches

There are many security systems to protect information resources, but we are still not free from possible successful attacks. This study aims at being one step towards the proposal of an intrusion detection system (IDS) that faces those attacks not previously seen (zero-day attacks), by studying the combination of clustering and neural visualization techniques. To do that, MObile VIsualization Connectionist Agent-Based IDS (MOVICAB-IDS), previously proposed as a hybrid intelligent IDS based on a visualization approach, is upgraded by adding clustering methods. One of the main drawbacks of MOVICAB-IDS was its dependence on human processing; it could not automatically raise an alarm to warn about attacks. Additionally, human users could fail to detect an intrusion even when visualized as an anomalous one. To overcome this limitation, present work proposes the application of clustering techniques to provide automatic response to MOVICAB-IDS to quickly abort intrusive actions while happening. To check the validity of the proposed clustering extension, it faces now an anomalous situation related to the Simple Network Management Protocol: a community search. This attack to get the community string (password guessing) is analysed by clustering and neural tools, individually and in conjunction. Through the experimental stage, it is shown that the combination of clustering and neural projection improves the detection capability on a continuous network flow