Improving the Teaching of Hypothesis Testing Using a Divide-and-Conquer Strategy and Content Exposure Control in a Gamified Environment

This article belongs to the Special Issue Active Methodologies for the Promotion of Mathematical LearningHypothesis testing has been pointed out as one of the statistical topics in which students present more misconceptions. In this article, an approach based on the divide-and-conquer methodology is proposed to facilitate its learning. The proposed strategy is designed to sequentially explain and evaluate the different concepts involved in hypothesis testing, ensuring that a new concept is not presented until the previous one has been fully assimilated. The proposed approach, which contains several gamification elements (i.e., points or a leader-board), is implemented into an application via a modern game engine. The usefulness of the proposed approach was assessed in an experiment in which 89 first-year students enrolled in the Statistics course within the Industrial Engineering degree participated. Based on the results of a test aimed at evaluating the acquired knowledge, it was observed that students who used the developed application based on the proposed approach obtained statistically significant higher scores than those that attended a traditional class (p-value < 0.001), regardless of whether they used the learning tool before or after the traditional class. In addition, the responses provided by the students who participated in the study to a test of satisfaction showed their high satisfaction with the application and their interest in the promotion of these tools. However, despite the good results, they also considered that these learning tools should be considered as a complement to the master class rather than a replacement

Automatic Personality Assessment through Movement Analysis

Obtaining accurate and objective assessments of an individual’s personality is vital in many areas including education, medicine, sports and management. Currently, most personality assessments are conducted using scales and questionnaires. Unfortunately, it has been observed that both scales and questionnaires present various drawbacks. Their limitations include the lack of veracity in the answers, limitations in the number of times they can be administered, or cultural biases. To solve these problems, several articles have been published in recent years proposing the use of movements that participants make during their evaluation as personality predictors. In this work, a multiple linear regression model was developed to assess the examinee’s personality based on their movements. Movements were captured with the low-cost Microsoft Kinect camera, which facilitates its acceptance and implementation. To evaluate the performance of the proposed system, a pilot study was conducted aimed at assessing the personality traits defined by the Big-Five Personality Model. It was observed that the traits that best fit the model are Extroversion and Conscientiousness. In addition, several patterns that characterize the five personality traits were identified. These results show that it is feasible to assess an individual’s personality through his or her movements and open up pathways for several research.This research was partially funded by the Spanish National Project, grant number RTI2018- 101857-B-I00. Additionally, by Instituto Salud Carlos III, grant number DTS21/00091. It has been also partially supported by Ministerio de Ciencia e Innovación PID2020-114911GB-I00

NeuroTessMesh: A Tool for the Generation and Visualization of Neuron Meshes and Adaptive On-the-Fly Refinement

Gaining a better understanding of the human brain continues to be one of the greatest challenges for science, largely because of the overwhelming complexity of the brain and the difficulty of analyzing the features and behavior of dense neural networks. Regarding analysis, 3D visualization has proven to be a useful tool for the evaluation of complex systems. However, the large number of neurons in non-trivial circuits, together with their intricate geometry, makes the visualization of a neuronal scenario an extremely challenging computational problem. Previous work in this area dealt with the generation of 3D polygonal meshes that approximated the cells’ overall anatomy but did not attempt to deal with the extremely high storage and computational cost required to manage a complex scene. This paper presents NeuroTessMesh, a tool specifically designed to cope with many of the problems associated with the visualization of neural circuits that are comprised of large numbers of cells. In addition, this method facilitates the recovery and visualization of the 3D geometry of cells included in databases, such as NeuroMorpho, and provides the tools needed to approximate missing information such as the soma’s morphology. This method takes as its only input the available compact, yet incomplete, morphological tracings of the cells as acquired by neuroscientists. It uses a multiresolution approach that combines an initial, coarse mesh generation with subsequent on-the-fly adaptive mesh refinement stages using tessellation shaders. For the coarse mesh generation, a novel approach, based on the Finite Element Method, allows approximation of the 3D shape of the soma from its incomplete description. Subsequently, the adaptive refinement process performed in the graphic card generates meshes that provide good visual quality geometries at a reasonable computational cost, both in terms of memory and rendering time. All the described techniques have been integrated into NeuroTessMesh, available to the scientific community, to generate, visualize, and save the adaptive resolution meshes

NeuroEditor: a tool to edit and visualize neuronal morphologies

The digital extraction of detailed neuronal morphologies from microscopy data is an essential step in the study of neurons. Ever since Cajal’s work, the acquisition and analysis of neuron anatomy has yielded invaluable insight into the nervous system, which has led to our present understanding of many structural and functional aspects of the brain and the nervous system, well beyond the anatomical perspective. Obtaining detailed anatomical data, though, is not a simple task. Despite recent progress, acquiring neuron details still involves using labor-intensive, error prone methods that facilitate the introduction of inaccuracies and mistakes. In consequence, getting reliable morphological tracings usually needs the completion of post-processing steps that require user intervention to ensure the extracted data accuracy. Within this framework, this paper presents NeuroEditor, a new software tool for visualization, editing and correction of previously reconstructed neuronal tracings. This tool has been developed specifically for alleviating the burden associated with the acquisition of detailed morphologies. NeuroEditor offers a set of algorithms that can automatically detect the presence of potential errors in tracings. The tool facilitates users to explore an error with a simple mouse click so that it can be corrected manually or, where applicable, automatically. In some cases, this tool can also propose a set of actions to automatically correct a particular type of error. Additionally, this tool allows users to visualize and compare the original and modified tracings, also providing a 3D mesh that approximates the neuronal membrane. The approximation of this mesh is computed and recomputed on-the-fly, reflecting any instantaneous changes during the tracing process. Moreover, NeuroEditor can be easily extended by users, who can program their own algorithms in Python and run them within the tool. Last, this paper includes an example showing how users can easily define a customized workflow by applying a sequence of editing operations. The edited morphology can then be stored, together with the corresponding 3D mesh that approximates the neuronal membrane

Attention deficit hyperactivity disorder assessment based on patient behavior exhibited in a car video game: A pilot study

This article belongs to the Special Issue Advances in ADHD.Symptoms of Attention Deficit Hyperactivity Disorder (ADHD) include excessive activity, difficulty sustaining attention, and inability to act in a reflective manner. Early diagnosis and treatment of ADHD is key but may be influenced by the observation and communication skills of caregivers, and the experience of the medical professional. Attempts to obtain additional measures to support the medical diagnosis, such as reaction time when performing a task, can be found in the literature. We propose an information recording system that allows to study in detail the behavior shown by children already diagnosed with ADHD during a car driving video game. We continuously record the participants" activity throughout the task and calculate the error committed. Studying the trajectory graphs, some children showed uniform patterns, others lost attention from one point onwards, and others alternated attention/inattention intervals. Results show a dependence between the age of the children and their performance. Moreover, by analyzing the positions by age over time using clustering, we show that it is possible to classify children according to their performance. Future studies will examine whether this detailed information about each child"s performance pattern can be used to fine-tune treatment.This research was partially funded by: Ministerio de Ciencia, Innovación y Universidades, Spanish National Project, grant number RTI2018-101857-B-I00, Ministerio de Universidades (Grant for the requalification of permanent lectures, David Delgado-Gómez), Instituto Salud Carlos III, grant number DTS21/00091

Análisis de los mecanismos y técnicas utilizadas en el proceso de selección de personal en la empresa Tempolider para mejorar la eficiencia y eficacia en su objeto social

No aplicaEste estudio tiene por objeto revisar y adecuar todas las técnicas y mecanismos utilizados por la Empresa Tempolider, mediante el diagnóstico de las políticas que direccionan el proceso de selección de personal examinando las herramientas y estrategias utilizadas en la búsqueda y retención del talento humano requerido por las organizaciones que se benefician de estos servicios basados en las necesidades y objetivos de las mismas, para el mejoramiento del reclutamiento de personal idóneo solicitado, puesto que la razón de ser de este tipo de organizaciones se concentra en buscar a los mejores talentos para cumplir con la misión y la visión de la empresa y ante todo la satisfacción de los clientes. Dado el contexto la herramienta de recolección de datos utilizada fue la encuesta, para evaluar la eficiencia en las técnicas de selección de personal de esta empresa, de esta manera se observa, analiza y determinan las deficiencias existentes, así como las propuestas necesarias y adecuadas para contrarrestar las falencias encontradas. Evaluar estas técnicas contribuyó de manera significativa a la elaboración de informes de estudio y seguimiento a las actividades que desempeña el área de talento humano de Tempolider, lo que permitió consolidar los resultados de esta investigación logrando proponer acciones de mejora en cada uno de sus directrices y procedimientos que realizan.The purpose of this study is to review and adapt all the techniques and mechanisms used by the Tempolider Company, through the diagnosis of the policies that guide the personnel selection process, examining the tools and strategies used in the search and retention of the human talent required by organizations that benefit from these services based on their needs and objectives, to improve the recruitment of suitable personnel requested, since the raison d'être of this type of organization focuses on seeking the best talent to meet the mission and vision of the company and, above all, customer satisfaction. Given the context, the data collection tool used was the survey, to evaluate the efficiency in the personnel selection techniques of this company, in this way the existing deficiencies are observed, analyzed, and determined, as well as the necessary and adequate proposals for counteract the shortcomings found. Evaluating these techniques contributed significantly to the preparation of study reports and monitoring of the activities carried out by the human talent area of Tempolider, which allowed consolidating the results of this investigation, proposing improvement actions in each of its guidelines. and procedures they perform

A Unified Framework for Neuroscience Morphological Data Visualization

The complexity of the human brain makes its understanding one of the biggest challenges that science is currently confronting. Due to its complexity, the brain has been studied at many different levels and from many disciplines and points of view, using a diversity of techniques for getting meaningful data at each specific level and perspective, producing sometimes data that are difficult to integrate. In order to advance understanding of the brain, scientists need new tools that can speed up this analysis process and that can facilitate integrating research results from different disciplines and techniques. Visualization has proved to be useful in the analysis of complex data, and this paper focuses on the design of visualization solutions adapted to the specific problems posed by brain research. In this paper, we propose a unified framework that allows the integration of specific tools to work together in a coordinated manner in a multiview environment, displaying information at different levels of abstraction and combining schematic and realistic representations. The two use cases presented here illustrate the capability of this approach for providing a visual environment that supports the exploration of the brain at all its organizational levels

Entrenamiento Vocal III - EA18 - 202101

Descripción: El curso Entrenamiento Vocal III fortalece el proceso de integración de los conceptos tratados en Entrenamiento Vocal II. Profundiza teorías, prácticas y usos de la producción vocal, y la adquisición de herramientas para el análisis de prosodia y musicalidad subyacente al texto, así como fonética adquiridos en el ciclo anterior. Continúa también la exploración vocal creativa y de expresividad del alumno para ponerla al servicio de la creación actoral. Profundiza los conocimientos sobre comunicación oral. Asimismo, aporta a los alumnos un conocimiento musical básico de solfeo rítmico, lo que les permitirá componer una partitura rítmica básica aplicable a los textos del coro griego. Desde diferentes puntos de partida se estudiará la composición de esquemas vocales desde diferentes desafíos para la construcción de personajes. Propósito: El curso desarrolla la competencia general de Comunicación Oral (Nivel 2) y la competencia específica de Actoralidad: Producción Vocal (Nivel 2). El estudiante tendrá un trabajo vocal más minucioso, integrando de manera definitiva el trabajo vocal y corporal. Adquiere una sólida base rítmico-musical y conozca los elementos básicos del Coro Griego. Afianza el reconocimiento de la musicalidad del lenguaje hablado en su idioma y explorando el de otros idiomas, dialectos y culturas. Del mismo modo se busca, que sea capaz de analizar un texto para extraer todas las posibilidades expresivas y sonoras que aporta, ampliando su repertorio vocal y expresividad. Relaciona, de manera complementaria, la comunicación oral y la producción vocal. El estudiante requiere haber aprobado el curso de Entrenamiento Vocal II.

Attention and impulsivity assessment using virtual reality games

Abstract The assessment of cognitive functions is mainly based on standardized neuropsychological tests, widely used in various fields such as personnel recruitment, education, or health. This paper presents a virtual reality game that allows collecting continuous measurements of both the performance and behaviour of the subject in an immersive, controllable, and naturalistic experience. The application registers variables related to the user’s eye movements through the use of virtual reality goggles, as well as variables of the game performance. We study how virtual reality can provide data to help predict scores on the Attention Control Scale Test and the Barratt Impulsiveness Scale. We design the application and test it with a pilot group. We build a random forest regressor model to predict the attention and impulsivity scales’ total score. When evaluating the performance of the model, we obtain a positive correlation with attention (0.434) and with impulsivity (0.382). In addition, our model identified that the most significant variables are the time spent looking at the target or at distractors, the eye movements variability, the number of blinks and the pupil dilation in both attention and impulsivity. Our results are consistent with previous results in the literature showing that it is possible to use data collected in virtual reality to predict the degree of attention and impulsivity