Simulation of academic performance rates, estimation of indicators of subjects and of a complete degree

The purpose of this paper is to present a program written in Matlab-Octave for the simulation of the time evolution of student curricula, i.e, how students pass their subjects along time until graduation. The program computes, from the simulations, the academic performance rates for the subjects of the study plan for each semester as well as the overall rates, which are a) the efficiency rate defined as the ratio of the number of students passing the exam to the number of students who registered for it and b) the success rate, defined as the ratio of the number of students passing the exam to the number of students who not only registered for it but also actually took it. Additionally, we compute the rates for the bachelor academic degree which are established for Spain by the National Quality Evaluation and Accreditation Agency (ANECA) and which are the graduation rate (measured as the percentage of students who finish as scheduled in the plan or taking an extra year) and the efficiency rate (measured as the percentage of credits which a student who graduated has really taken). The simulation is done in terms of the probabilities of passing all the subjects in their study plan. The application of the simulator to Polytech students in Madrid, where requirements for passing are specially stiff in first and second year subjects, is particularly relevant to analyze student cohorts and the probabilities of students finishing in the minimum of four years, or taking and extra year or two extra years, and so forth. It is a very useful tool when designing new study plans. The calculation of the probability distribution of the random variable "number of semesters a student has taken to complete the curricula and graduate" is difficult or even unfeasible to obtain analytically, and this is even truer when we incorporate uncertainty in parameter estimation. This is why we apply Monte Carlo simulation which not only provides illustration of the stochastic process but also a method for computation. The stochastic simulator is proving to be a useful tool for identification of the subjects most critical in the distribution of the number of semesters for curriculum vitae (CV) completion and subsequently for a decision making process in terms of CV planning and passing standards in the University. Simulations are performed through a graphical interface where also the results are presented in appropriate figures. The Project has been funded by the Call for Innovation in Education Projects of Universidad Politécnica de Madrid (UPM) through a Project of its school Escuela Técnica Superior de Ingenieros Industriales ETSII during the period September 2010-September 2011.

Diffusion of photovoltaic in Germany: policy vs. consumers

In some countries photovoltaic (PV) technology has already achieved a stage of development at which it can compete with conventional electricity sources. Germany provides a good illustration of this where PV market has reached a mature stage. As a manifest of this, the German government has recently reduced subsidies for households and industry by decreasing the feed in tariff for PV. This development raises fundamental questions: could the PV industry survive? Will consumers be motivated to continue to adopt PV when feed-in tariff diminish? The point of departure for the relevant literature on diffusion of PV has been on the effect of subsidies but little attention has paid to consumer motives when the policy support is scaled down. This paper introduces an in-depth analysis on understanding the consumer motives for adopting photovoltaic applications. Anchored in an extensive exploratory case study on PV consumers and PV system providers, this study aims to provide an encompassing explanation of diffusion of PV by revealing the link between consumer motives and the impact of policy.

Implications of data-intensive applications for next generation mobile networks

Lately, the mobile data market has moved into a growth stage triggered by two facts: affordability of mobile broadband, and availability of data-friendly devices. At this stage, market growth is no longer dependent on push strategies from suppliers; on the contrary, demand is now driving the market. However, it will not be easy for mobile operating companies to cope up with the demand to come in the near future. The infrastructure that is needed to support corresponding demand is far from completion. Operators are forced to make heavy investments to upgrade and expand their networks. To decide how to handle the present and upcoming demand, they need to identify and understand the characteristics of the scenarios they face. This is precisely the aim of this article, which provides figures on the consequences for mobile infrastructures of a generalised mobile media uptake. Data from the Spanish mobile deployment case have been used to arrive at practical figures and illustration of results, but the conclusions are easily extended to other countries and regions