An xAPI application profile to monitor self-regulated learning strategies

Self-regulated learning (SRL) is being promoted and adopted increasingly due to the needs of current education, student centered and focused on competence development. One of the main components of SRL is learners' self-monitoring, which eventually contributes to a better performance. Monitoring is also important for teachers, as it enables them to know to what extent their learners are doing well and progressing properly. At the same time, the use of technology for learning is now common and facilitates monitoring. Nevertheless, the available software still offers poor support from the SRL point of view, especially, for SRL monitoring. This clashes with the growth of learning analytics and educational data mining. The main issue is the wide variety of SRL actions that need to be captured, commonly performed in different tools, and the need to integrate them to support the development of analytics and data mining developments, making imperative the search of interoperable solutions. This paper focuses on the standardization of SRL traces to enable data collection from multiple sources and data analysis with the goal of easing the monitoring process for teachers and learners. First, the paper analyzes current monitoring software and its limitations for SRL. Then, after a brief analysis of available standards on this area, an application profile for the eXperience API specification is proposed to enable the interoperable recording of the SRL traces. The paper describes the process followed to create the profile, from the analysis to the final implementation, including the selection of the interactions that represent relevant SRL actions, the selection of vocabularies to record them and a case study.Xunta de Galicia | Ref. ED431B 2017/67Xunta de Galicia | Ref. ED431D 2017/1

Engineering modular web-based education systems to support EML units of learning

Educational Modeling Languages (EMLs) have been proposed to support the modeling of units of learning enabling the description of different pedagogical approaches. Eventually, such models are intended to support the operation of appropriate computer systems, controlling and managing the corresponding units of learning. This paper considers EMLs involving a set of independent perspectives. Our purpose is to use this set of perspectives to facilitate the development of Web-based education systems that are able to support the execution of EML models. As a result, we obtain a modular architecture where different pedagogical approaches can be supported.Education for the 21 st century - impact of ICT and Digital Resources ConferenceRed de Universidades con Carreras en Informática (RedUNCI

Morphological Bases of Human Leydig Cell Dysfunction

In this chapter, we describe the histophysiology of human Leydig cells, their cytological characteristics, their differentiation processes, and the physiopathological processes occurring at various times throughout life. We first focus on the normal development of fetal Leydig cells as well as the pathologies of fetal Leydig cells that can affect numbers or hyperplasic processes (e.g., hypogonadotropic hypogonadism, cryptorchidism, congenital Leydig cell hyperplasia secondary to diabetes, and isoimmunization). Next, we explain the changes occurring at puberty with the onset and differentiation of adult Leydig cells and the pathophysiology of delayed puberty. We then describe the histophysiology of adult Leydig cells and the most frequent pathologies (e.g., hypogonadotropic hypogonadism, testicular dysgenesia, mild androgen insensitivity syndrome, 5-α-reductase defect, and Klinefelter syndrome). Finally, we discuss the morphological changes of these cells in the elderly

An SIRS Epidemic Model Supervised by a Control System for Vaccination and Treatment Actions Which Involve First-Order Dynamics and Vaccination of Newborns

This paper analyses an SIRS epidemic model with the vaccination of susceptible individuals and treatment of infectious ones. Both actions are governed by a designed control system whose inputs are the subpopulations of the epidemic model. In addition, the vaccination of a proportion of newborns is considered. The control reproduction number Rc of the controlled epidemic model is calculated, and its influence in the existence and stability of equilibrium points is studied. If such a number is smaller than a threshold value R¯¯¯c, then the model has a unique equilibrium point: the so-called disease-free equilibrium point at which there are not infectious individuals. Furthermore, such an equilibrium point is locally and globally asymptotically stable. On the contrary, if Rc>R¯¯¯c, then the model has two equilibrium points: the referred disease-free one, which is unstable, and an endemic one at which there are infectious individuals. The proposed control strategy provides several free-design parameters that influence both values Rc and R¯¯¯c. Then, such parameters can be appropriately adjusted for guaranteeing the non-existence of the endemic equilibrium point and, in this way, eradicating the persistence of the infectious disease.This research received support from the Spanish Government through grant RTI2018-094336-B-I00 (MCIU/AEI/FEDER, UE)

On a generalized SVEIR epidemic model under regular and adaptive impulsive vaccination

A model for a generic disease with incubation and recovered stages is proposed. It incorporates a vaccinated subpopulation which presents a partial immunity to the disease. We study the stability, periodic solutions and impulsive vaccination design in the generalized modeled system for the dynamics and spreading of the disease under impulsive and non-impulsive vaccination. First, the effect of a regular impulsive vaccination on the evolution of the subpopulations is studied. Later a non-regular impulsive vaccination strategy is introduced based on an adaptive control law for the frequency and quantity of applied vaccines. We show the later strategy improves drastically the efficiency of the vaccines and reduce the infectious subpopulation more rapidly over time compared to a regular impulsive vaccination with constant values for both the frequency and vaccines quantity

Sustainability of Open Educational Resources: the eCity case

[EN]The promotion of Open Educational Resources (OER) as reusable tools for teachers and students is highly relevant but the nature of the income model requires specific strategies to maintain and update those resources. eCity is a city simulation game that supports a Problem Based Learning (PBL) pedagogical methodology in secondary schools and, at the same time, fosters the interest of students in following an Engineering career. The game is freely available through online stores and the generated interest (about 100.000 downloads so far) has raised the need to discuss and adopt a sustainability strategy for the maintenance of the game and the development of new versions. This article presents possible alternatives for that strategy

Sustainability of Open Educational Resources: the eCity case

[EN]The promotion of Open Educational Resources (OER) as reusable tools for teachers and students is highly relevant but the nature of the income model requires specific strategies to maintain and update those resources. eCity is a city simulation game that supports a Problem Based Learning (PBL) pedagogical methodology in secondary schools and, at the same time, fosters the interest of students in following an Engineering career. The game is freely available through online stores and the generated interest (about 100.000 downloads so far) has raised the need to discuss and adopt a sustainability strategy for the maintenance of the game and the development of new versions. This article presents possible alternatives for that strategy

Novel RNA viruses from the Atlantic Ocean: Ecogenomics, biogeography, and total virioplankton mass contribution from surface to the deep ocean

Marine viruses play a major role in the energy and nutrient cycle and affect the evolution of their hosts. Despite their importance, there is still little knowledge about RNA viruses. Here, we have explored the Atlantic Ocean, from surface to deep (4.296 m), and used viromics and quantitative methods to unveil the genomics, biogeography, and the mass contribution of RNA viruses to the total viroplankton. A total of 2481 putative RNA viral contigs (>500 bp) and 107 larger bona fide RNA viral genomes (>2.5 kb) were identified; 88 of them representing novel viruses belonging mostly to two clades: Yangshan assemblage (sister clade to the class Alsuviricetes) and Nodaviridae. These viruses were highly endemic and locally abundant, with little or no presence in other oceans since only ≈15% of them were found in at least one of the Tara sampling metatranscriptomes. Quantitative data indicated that the abundance of RNA viruses in the surface and deep chlorophyll maximum zone was within ≈106 VLP/mL representing a potential contribution of 5.2%–24.4% to the total viroplankton community (DNA and RNA viruses), with DNA viruses being the predominant members (≈107 VLP/mL). However, for the deep sample, the observed trend was the opposite, although as further discussed, several biases should be considered. Together these results contribute to our understanding of the diversity, abundance, and distribution of RNA viruses in the oceans and provide a basis for further investigation into their ecological roles and biogeography.This work was supported by the Generalitat Valenciana ACIF2020 grant and by the research grants funded by Spanish Ministry of Science and Innovation (refs. RTI2018-094248-B-I00 and PID2021-125175OB-I00), and by the Gordon and Moore Foundation (ref. 5334)

Predictors and early warning systems in higher education: a systematic literature review

The topic of predictive algorithms is often regarded among the most relevant fields of study within the data analytics discipline. Nowadays, these algorithms are widely used by entrepreneurs and researchers alike, having practical applications in a broad variety of contexts, such as in finance, marketing or healthcare. One of such contexts is the educational field, where the development and implementation of learning technologies led to the birth and popularization of computerbased and blended learning. Consequently, student-related data has become easier to collect. This Research Full Paper presents a literature review on predictive algorithms applied to higher education contexts, with special attention to early warning systems (EWS): tools that are typically used to analyze future risks such as a student failing or dropping a course, and that are able to send alerts to instructors or students themselves before these events can happen. Results of using predictors and EWS in real academic scenarios are also highlighted

Profiling students’ self-regulation with learning analytics: a proof of concept

The ability to regulate one's own learning processes is a key factor in educational scenarios. Self-regulation skills notably affect students' ef cacy when studying and academic performance, for better orworse. However, neither students or instructors generally have proper understanding of what self-regulated learning is, the impact that it has or how to assess it. This paper has the purpose of showing how learning analytics can be used in order to generate simple metrics related to several areas of students' selfregulation, in the context of a rst-year university course. These metrics are based on data obtained from a learning management system, complemented by more speci c assessment-related data and direct answers to self-regulated learning questionnaires. As the end result, simple self-regulation pro les are obtained for each student, which can be used to identify strengths and weaknesses and, potentially, help struggling students to improve their learning habits.Xunta de Galicia | Ref. ED431B 2020/3