Analysis of the pedagogical perspective of the MOOCs available in Portuguese

After an initial stage of exponential growth in MOOCs, a need has arisen of to address several different aspects of these innovations in order to understand and develop them from different perspectives, such as this one, with the analysis of pedagogical dimensions aimed at improving course design. This paper presents an updated review of the literature and proposes five research lines for an in-depth approach. This study is part of a broader research project1 and here analyses 356 MOOCs delivered in Portuguese by 16 different platforms. The research design is quantitative, non-experimental and transversal. An adaptation of the MOOC Educational and Interactive Indicators Instrument —INdiMOOC-EdI— was used in the data collection process. The reliability and internal consistency analysis of that adaptation for the whole sample resulted in a Cronbach alpha score of 0.731. The data obtained enable us to classify the existing MOOCs in Portuguese according to descriptive, formative, and interactive components. These different types correlate with the quality indices, being negative in the first dimension (descriptive) and positive in the second and third ones (formative and interactive).Funded by the call for R&D&i projects named: «Estudio del impacto de las erubricas federada en evaluación de las competencias en el practicum» (Study on the impact of federated eRubrics in the evaluation of the competences in the practicum). Plan Nacional de I+D+i de Excelencia (National R&D&i Excellence Plan) (2014-16) no. EDU2013-41974-

Modeling and forecasting extreme hot events in the central Ebro Valley, a continental-mediterranean area

This work has three objectives, first, to analyze the observed change in the summer maximum daily temperature during the period 1951–2004, in the centre of the Ebro river basin, a region situated in the NE of the Iberian Peninsula. Secondly, to characterize the extreme hot event behaviour by means of a statistical model consisting of a non-homogeneous Poisson process, to represent the occurrence, and three regression models, each with an adequate non-Normal error distribution, to model its severity. The model parameters are allowed to depend on temperature covariates, to take into account the influence of global warming in hot event generating process. Finally, using the fitted model and different outputs from a GCM, we obtain a medium term projection, up to 2050, of the expected behaviour of these extreme events

Time-critical decentralised situational awareness in emergencies: An adversarial biosecurity scenario

Abstract Crises in a global setting of interdependencies call for time-critical coordinated responses. However, it is often the case that the mechanisms responsible for these actions do not agree across all their hierarchies. This can be roughly attributed to personal estimations of the situation and to social influence. An ensuing lack of consensus against crises can be dire and echo across entire populations. One such instance is the case of biosecurity threats. A particularly interesting class of threats lie within urban environments, which tend to fall within the scope of bad actors. With this work we aim to computationally contribute to the understanding of the dynamics of perceived danger formation among agents responsible for responding to ongoing biological attacks in urban settings. We assume this perception is a function of a personal estimation of local information about the danger and of social influence stemming from the agents in question framed in an agent-based model. The simulations point towards a high dependence of perceived dangers on the personal estimations of the agents. The conditions under which the perceived dangers deviate from the real ones are explored over a range of assumptions on personal measurements and several dispositions towards the influencing environment. The insight provided by these results at the individual and collective level set the tone for further investigation on such behavioural phenomena, providing a flexible computational framework addressing generic threats (true dangers) in a time-critical context

The small-world network of global protests

Protest diffusion is a cascade process that can spread over different regions of the planet. The way and the extension that this phenomenon can occur is still not properly understood. Here, we empirically investigate this question using protest data from GDELT and ICEWS, two of the most extensive and longest-running data sets freely available. We divide the globe into grid cells and construct a temporal network for each data set where nodes represent cells and links are established between nodes if their protest events co-occur. We show that the temporal networks are small-world, indicating that the cells are directly linked or separated by a few steps on average. Furthermore, the average path lengths are decreasing through the years, which suggests that the world is becoming “smaller”. The persistent temporal hubs present in both data sets indicate that protests can spread faster through the hubs. This topological feature is consistent with the hypothesis that protests can quickly diffuse from one region to any other part of the globe

Using Wavelets to reject background in Dark Matter experiments

A method based on wavelet techniques has been developed and applied to background rejection in the data of the IGEX dark matter experiment. The method is presented and described in some detail to show how it efficiently rejects events coming from noise and microphonism through a mathematical inspection of their recorded pulse shape. The result of the application of the method to the last data of IGEX is presented.Comment: 14 pages, 8 figures. Submitted to Astrop. Phy