Serious game as support for the development of computational thinking for children with hearing impairment

Computational thinking (CT) has been a topic of interest in research, not only in the field of computer science, but also in education, since it allows the development of a set of competencies in the child related to problem-solving and decision-making. However, few studies on CT are focused on children with disabilities. Developing computational thinking skills for children with hearing problems is a challenge, even more so when their language skills are limited. Following a methodology for conception of serious games for children with hearing impairment called MECONESIS (Acronym in Spanish, MEtodología para CONcepción de juEgos Serios para nIños con discapacidad auditiva), we designed the serious game Perdi-Dogs for children between 7 and 11 years old with hearing impairment. We considered a set of aspects, such as challenges/learning, control, rules, feedback, interaction, rewards, surprise, communication/language, and fantasy. Perdi-Dogs involves both a physical and a digital interface, specifically a physical board together with digital interaction, by means of a QR (Quick Response) code and vibrotactile feedback system. Perdi-Dogs simulates a real environment, using physical elements able to interact simultaneously with technology. Evaluation was carried out with a group of seven children between 7 and 11 years old from the Institute for Deaf and Blind Children (Colombia). The results showed a high motivation to play for all of the children involved in the experiment

¿Agroecología en la España despoblada?

Después de reflexionar sobre las dinámicas complementarias de creciente concentración de la población en ciudades y despoblación rural, se describe el caso de la iniciativa Activa Valverde. Un grupo de vecinos ha creado en este pequeño pueblo de Extremadura una plataforma ciudadana para afrontar la posible desaparición de la localidad, para lo que ha establecido fuertes vínculos con la Universidad de Sevilla. La descripción de los actores implicados, las acciones y los resultados preliminares de la iniciativa son parte de los resultados preliminares del proceso.In this paper we reflect on the complementary demographic dynamics with population increasingly concentrating in cities and rural depopulation. Afterwards we describe the Activa Valverde initiative, in which a group of neighbors has created a citizen platform to face the possible disappearance of this little town in Extremadura. They have established strong links with the University of Seville. We present a description of the actors involved, the actions and the preliminary results of the initiative

Fecal Occult Blood Test (FOBT) efficacy in hospitalized patients

Introduction:Fecal occult blood test (FOBT) is one of the most popular diagnostic tools for screening colorectal cancer in the inpatient setting. Despite that, its outpatient use has been largely replaced by more advanced tools that decrease cost and increase sensitivity/specificity. This is essential when factors including diet and medications contribute to the low sensitivity and elevated false positive results FOBT demonstrate when detecting gastrointestinal (GI) bleeds

The Role of Technology in the Learning Process: A Decision Tree-Based Model Using Machine Learning

Machine learning approaches may establish a complex and non-linear relationship among input and response variables for the assessment of the Basic Education Development Index (IDEB) database and show indicators that may contribute to monitoring the quality of education. This paper uses extensive experimental databases from public schools, consisting of a case study in Brazil, to analyze data such as the physical and technological structure of schools and teacher profiles. The research proposes decision tree-based machine learning models for predictions of the best attributes to positively contribute to IDEB. It employs a newly developed SHapley Additive exPlanations (SHAP) approach to classify input variables, so to identify variables that impact the most the final model; a non-probabilistic sample was used, composed from three official databases of 450 schools, and 617 teachers. Results show that the number of computers per student, teachers’ service time, broadband internet access, investments in technology training for teachers, and computer labs in schools are the variables that have the greatest effect on IDEB. The model applied shows high prediction accuracy for test data (MSE = 0.2094 and R² = 0.8991). This article contributes to improving efficiency when monitoring parameters used to measure the quality of a teaching-learning process. Doi: 10.28991/ESJ-2022-SIED-020 Full Text: PD

Gravity or turbulence? -III. Evidence of pure thermal Jeans fragmentation at ~0.1 pc scale

We combine previously published interferometric and single-dish data of relatively nearby massive dense cores that are actively forming stars to test whether their `fragmentation level' is controlled by turbulent or thermal support. We find no clear correlation between the fragmentation level and velocity dispersion, nor between the observed number of fragments and the number of fragments expected when the gravitationally unstable mass is calculated including various prescriptions for `turbulent support'. On the other hand, the best correlation is found for the case of pure thermal Jeans fragmentation, for which we infer a core formation efficiency around 13 per cent, consistent with previous works. We conclude that the dominant factor determining the fragmentation level of star-forming massive dense cores at 0.1 pc scale seems to be thermal Jeans fragmentation.Comment: accepted in MNRA

Remote Sensing for the Characterization of Covers and Meteorological Conditions of the Chimborazo Fauna Production Reserve

The objective of this research is to characterize the vegetation cover and meteorological conditions through a multispectral analysis of the Chimborazo Wildlife Production Reserve. The methodology used for this research is the one proposed by Chuvieco, which began with the definition of objectives, bibliographic review of the reserve’s canopy, download of the most appropriate satellite image (without cloud cover), definition of canopy categories, image correction, calculation of spectral indices, supervised classification, adjustments, map generation using GIS tools, and interpretation of the results. Additionally, a National Solar Radiation Database web platform was used to download meteorological data for the year 2020, which were used to characterize the study area; the results were compared with the data acquired in 2017 with a station installed in the reserve. In the end, it was determined that multispectral analysis allows generating data close to a field work study. For the faunal reserve, the following area of established covers were obtained: shrub vegetation 55.8 km2, snow 47.9 km2, eroded zone 125 km2, moor 190 km2, pasture 76 km2 and crops 30.56 km2. Average temperature 5∘C, relative humidity 95.8% and water precipitation 1.37. Keywords: Remote sensing, vegetation cover characterization, Chimborazo Wildlife Reserve, meteorological data, multispectral analysis, Vegetation Index. Resumen La presente investigación tiene como objetivo realizar una caracterización de las cubiertas vegetales y condiciones meteorológicas a través de un análisis multitespectral de la Reserva de Producción Faunística Chimborazo. La metodología que se utilizó para esta investigación es la propuesta por Chuvieco donde se empezó con la definición de objetivos, revisión bibliográfica de las cubiertas de la reserva, descarga de la imagen satelital más adecuada (sin nubosidad), definición de categorías de cubiertas, corrección de imágenes, cálculo de índices espectrales, clasificación supervisada, ajustes, generación de mapas mediante herramientas SIG e interpretación de los resultados. Adicionalmente se utilizó una plataforma web National Solar Radiation Database para la descarga de datos meteorológicos del año 2020 que sirvieron para realizar la caracterización de la zona de estudio, los resultados fueron comparados con los datos adquiridos del año 2017 con una estación instalada en la reserva. Al final se determinó que el análisis multiespectral permite generar datos cercanos a un estudio de trabajo en campo. Para la reserva faunística se obtuvo las siguientes área de las cubiertas establecidas: vegetación arbustiva 55.8 km2, nieve 47.9 km2, zona erosionada 125 km2, páramo 190 km2, pastos 76 km2 y cultivos 30.56 km2. La temperatura media 5∘C, humedad relativa 95.8 % y precipitación de agua 1.37. Palabras Clave: Sensoramiento Remoto, caracterización de cubiertas vegetales, Reserva Faunística Chimborazo, datos meteorológicos, análisis multiespectral, Indice de vegetació