Review of Current Student-Monitoring Techniques used in eLearning-Focused recommender Systems and Learning analytics. The Experience API & LIME model Case Study

Recommender systems require input information in order to properly operate and deliver content or behaviour suggestions to end users. eLearning scenarios are no exception. Users are current students and recommendations can be built upon paths (both formal and informal), relationships, behaviours, friends, followers, actions, grades, tutor interaction, etc. A recommender system must somehow retrieve, categorize and work with all these details. There are several ways to do so: from raw and inelegant database access to more curated web APIs or even via HTML scrapping. New server-centric user-action logging and monitoring standard technologies have been presented in past years by several groups, organizations and standard bodies. The Experience API (xAPI), detailed in this article, is one of these. In the first part of this paper we analyse current learner-monitoring techniques as an initialization phase for eLearning recommender systems. We next review standardization efforts in this area; finally, we focus on xAPI and the potential interaction with the LIME model, which will be also summarized below

Design of a Remote Signal Processing Student Lab

[EN] We describe our experience of introducing digital signal processing (DSP) concepts via a software-defined radio project using a very inexpensive TV USB capture dongle. Through a series of weekly lab exercises, the students learned and applied DSP concepts to design a completely digital FM receiver. The proposed lab experience introduced concepts, such as sampling, IQ signal representation, sample rate conversion, filter design, filter delays, and more, all with an attractive learn-by-doing approach. The first offering of this course initially took place in Fall 2014 and has been successfully offered and repeated with growing success ever since. Our experience can serve as a proof of concept of the possibility of carrying out, in a massive open online course-like fashion, certain engineering labs that require inexpensive and readily available hardware components.This work was supported by the Universidad Internacional de la Rioja through the Research Institute for Innovation and Technology in Education.Albiol Colomer, A.; Corbi, A.; Burgos, D. (2017). Design of a Remote Signal Processing Student Lab. IEEE Access. 5:16068-16076. doi:10.1109/ACCESS.2017.2736165S1606816076

Automatic determination of the Atterberg limits with machine learning

In this study, we determine the liquid limit (Wt), plasticity index (PI), and plastic limit (Wp) of several natural fine-grained soil samples with the help of machine-learning and statistical methods. This enables us to locate each soil type analysed in the Casagrande plasticity chart with a single measure in pressure-membrane extractors. These machine-learning models showed adjustments in the determination of the liquid limit for design purposes when compared with standardised methods. Similar adjustments were achieved in the determination of the plasticity index, whereas the plastic limit determinations were applicable for control works. Because the best techniques were based in Multiple Linear Regression and Support Vector Machines Regression, they provide explainable plasticity models. In this sense, (Equation presented), and (Equation presented). So that, we propose an alternative, automatic, multi-sample, and static method to address current issues on Atterberg limits determination with standardised tests.En este estudio, determinamos el límite líquido (), el índice de plasticidad (PI) y el límite plástico () de suelos naturales finos con ayuda de machine-learning y métodos estadísticos. Ello permite localizarlos en la Carta de Plasticidad de Casagrande con una sola medida en extractores de presión-membrana. Los modelos de machine-learning mostraron ajustes en la determinación de apropiados para propósitos de diseño, comparados con métodos estandarizados. Ajustes similares se alcanzaron en la determinación de PI, mientras que las determinaciones de permiten ajustes apropiados para trabajos de control. Debido a que las técnicas más apropiadas se basaron en Regresión Lineal Múltiple y Máquinas de Soporte de Vectores, aportaron modelos de plasticidad explicables. En este sentido, =(9.94±4.2)+(2.25±0.3)∙4.2,=(−20.47±5.6)+(1.48±0.3)∙4.2+(0.21±0.1)∙y=(23.32±3.5)+(0.60±0.2)∙4.2−(0.13±0.04)∙. Por consiguiente, proponemos un método alternativo, automático, estático y multimuestra para enfrentar problemas frecuentes en la determinación de los Límites de Atterberg con ensayos normalizados

Reliability of IBM’s Public Quantum Computers

One of the challenges of the current ecosystem of quantum computers (QC) is the stabilization of the coherence associated with the entanglement of the states of their inner qubits. In this empirical study, we monitor the reliability of IBM’s public-access QCs network on a daily basis. Each of these state-of-the-art machines has a totally different qubit association, and this entails that for a given (same) input program, they may output a different set of probabilities for the assembly of results (including both the right and the wrong ones). Although we focus on the computing structure provided by the “Big Blue” company, our survey can be easily transferred to other currently available quantum mainframes. In more detail, we probe these quantum processors with an ad hoc designed computationally demanding quaternary search algorithm. As stated, this quantum program is executed every 24 hours (for nearly 100 days) and its goal is to put to the limit the operational capacity of this novel and genuine type of equipment. Next, we perform a comparative analysis of the obtained results according to the singularities of each computer and over the total number of executions. In addition, we subsequently apply (for 50 days) an improvement filtering to perform noise mitigation on the results obtained proposed by IBM. The Yorktown 5-qubit computer reaches noise filtering of up to 33% in one day, that is, a 90% confidence level is reached in the expected results. From our continuous and long-term tests, we derive that room still exists regarding the improvement of quantum calculators in order to guarantee enough confidence in the returned outcomes

Multisite Phosphorylation of the Sum1 Transcriptional Repressor by S-Phase Kinases Controls Exit from Meiotic Prophase in Yeast.

Activation of the meiotic transcription factor Ndt80 is a key regulatory transition in the life cycle of Saccharomyces cerevisiae because it triggers exit from pachytene and entry into meiosis. The NDT80 promoter is held inactive by a complex containing the DNA-binding protein Sum1 and the histone deacetylase Hst1. Meiosis-specific phosphorylation of Sum1 by the protein kinases Cdk1, Ime2, and Cdc7 is required for NDT80 expression. Here, we show that the S-phase-promoting cyclin Clb5 activates Cdk1 to phosphorylate most, and perhaps all, of the 11 minimal cyclin-dependent kinase (CDK) phospho-consensus sites (S/T-P) in Sum1. Nine of these sites can individually promote modest levels of meiosis, yet these sites function in a quasiadditive manner to promote substantial levels of meiosis. Two Cdk1 sites and an Ime2 site individually promote high levels of meiosis, likely by preparing Sum1 for phosphorylation by Cdc7. Chromatin immunoprecipitation reveals that the phosphorylation sites are required for removal of Sum1 from the NDT80 promoter. We also find that Sum1, but not its partner protein Hst1, is required to repress NDT80 transcription. Thus, while the phosphorylation of Sum1 may lead to dissociation from DNA by influencing Hst1, it is the presence of Sum1 on DNA that determines whether NDT80 will be expressed

Physical activity and exercise for the prevention and management of mild cognitive impairment and dementia:A collaborative international guideline

Background: Physical activity and exercise have been suggested as effective interventions for the prevention and management of mild cognitive impairment (MCI) and dementia, but there are no international guidelines. Objectives: To create a set of evidence- and expert consensus-based prevention and management recommendations regarding physical activity (any bodily movement produced by skeletal muscles that results in energy expenditure) and exercise (a subset of physical activity that is planned, structured, repetitive), applicable to a range of individuals from healthy older adults to those with MCI/dementia. Methods: Guideline content was developed with input from several scientific and lay representatives' societies. A systematic search across multidisciplinary databases was carried out until October 2021. Recommendations for prevention and management were developed according to the GRADE and complemented by consensus statements from the expert panels. Recommendations: Physical activity may be considered for the primary prevention of dementia. In people with MCI there is continued uncertainty about the role of physical activity in slowing the conversion to dementia. Mind-body interventions have the greatest supporting evidence. In people with moderate dementia, exercise may be used for maintaining disability and cognition. All these recommendations were based on a very low/low certainty of evidence. Conclusions: Although the scientific evidence on the beneficial role of physical activity and exercise in preserving cognitive functions in subjects with normal cognition, MCI or dementia is inconclusive, this panel, composed of scientific societies and other stakeholders, recommends their implementation based on their beneficial effects on almost all facets of health

Uso de tecnologías digitales en el diseño de una autoevaluación formativa en el curso de Genética General de la Facultad de Ciencias Veterinarias

Los nuevos planteamientos curriculares en la universidad demandan una integración de los contenidos, saberes y una actitud renovada de los docentes frente a las estrategias metodológicas, hechos estos que evocan la evaluación formativa como la manera más propia de acompañar el aprendizaje y la enseñanza. En la FCV- UNLP, las nuevas tecnologías de la información y comunicación (TIC), se comenzaron a utilizar ampliamente en los últimos cinco años para mejorar los modelos formativos y organizativos que sustentan el aprendizaje. El curso Genética General de la Carrera de Ciencias Veterinarias- UNLP (Plan 406/04) se concibe como la base del conocimiento de la Genética y el individuo. El objetivo fue diseñar una autoevaluación virtual optativa, utilizando el entorno virtual Moodle. A partir de los conceptos desarrollados por los docentes, se diseño un cuestionario con 20 preguntas del tipo opciones múltiples; respuesta corta; de emparejamiento y verdadero o falso. Sobre un total de 193 (100%) alumnos, 85 (44%) resolvieron el cuestionario; 47 (55%) aprobaron. En una Universidad presencial, el uso de tecnologías digitales como herramienta pedagógica representa una propuesta innovadora, se utiliza como complemento de las actividades curriculares presenciales.Facultad de Ciencias Veterinaria

Docencia, Investigación y Formación del Profesorado. Trabajo desde el Departamento de Psicología Evolutiva y Didáctica

El objetivo de este trabajo es reflexionar y analizar todo el trabajo que se está realizando desde el Departamento de Psicología Evolutiva y Didáctica de la Universidad de Alicante en tres ámbitos fundamentalmente: docencia, investigación y formación permanente. Con la coordinación del equipo directivo y la subcoordinación de un profesor de cada una de las áreas integrantes del Departamento (Didáctica y Organización Escolar y Psicología Evolutiva y de la Educación) se llevó a cabo un proceso de revisión y reflexión del trabajo realizado por todos los integrantes del Departamento, con el fin de poner en valor las fortalezas del equipo de docentes/investigadores y detectar las áreas de mejora, para poder actuar en consecuencia, potenciando su superación y mejorando la calidad del trabajo. La valoración por parte de los participantes en la experiencia es muy positiva ya que ha permitido tomas conciencia de las potencialidades del equipo y ha servido para estimular acciones de mejora