Realistic performance prediction in nanostructured solar cells as a function of nanostructure dimensionality and density

The behavior of quantum dot, quantum wire, and quantum well InAs/GaAs solar cells is studied with a very simplified model based on experimental results in order to assess their performance as a function of the low bandgap material volume fraction fLOW. The efficiency of structured devices is found to exceed the efficiency of a non-structured GaAs cell, in particular under concentration, when fLOW is high; this condition is easier to achieve with quantum wells. If three different quasi Fermi levels appear with quantum dots the efficiency can be much higher.

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.

Learning Analytics and Interactions in Virtual Learning Environments. A Comparative Study of Typologies and their Relationship with Academic Performance

Analysis of learning data (learning analytics) is a new research field with high growth potential. The main objective of Learning analytics is the analysis of data (interactions being the basic data unit) generated in virtual learning environments, in order to maximize the outcomes of the learning process; however, a consensus has not been reached yet on which interactions must be measured and what is their influence on learning outcomes. This research is grounded on the study of e-learning interaction typologies and their relationship with students? academic performance, by means of a comparative study between different interaction typologies (based on the agents involved, frequency of use and participation mode). The main conclusions are a) that classifications based on agents offer a better explanation of academic performance; and b) that each of the three typologies are able to explain academic performance in terms of some of their components (student-teacher and student-student interactions, evaluating students interactions and active interactions, respectively), with the other components being nonrelevant.

Predicting academic performance with learning analytics in virtual learning environments: A comparative study of three interaction classifications

Learning analytics is the analysis of static and dynamic data extracted from virtual learning environments, in order to understand and optimize the learning process. Generally, this dynamic data is generated by the interactions which take place in the virtual learning environment. At the present time, many implementations for grouping of data have been proposed, but there is no consensus yet on which interactions and groups must be measured and analyzed. There is also no agreement on what is the influence of these interactions, if any, on learning outcomes, academic performance or student success. This study presents three different extant interaction typologies in e-learning and analyzes the relation of their components with students? academic performance. The three different classifications are based on the agents involved in the learning process, the frequency of use and the participation mode, respectively. The main findings from the research are: a) that agent-based classifications offer a better explanation of student academic performance; b) that at least one component in each typology predicts academic performance; and c) that student-teacher and student-student, evaluating students, and active interactions, respectively, have a significant impact on academic performance, while the other interaction types are not significantly related to academic performance.

Teamwork, motivational profiles and academic performance in computer science engineering

The present work is aimed at discussing several issues related to the teamwork generic competence, motivational profiles and academic performance. In particular, we study the improvement of teamwork attitude, the predominant types of motivation in different contexts and some correlations among these three components of the learning process. The above-mentioned aspects are of great importance. Currently, the professional profile of engineers has a strong teamwork component and the motivational profile of students determines both their tendencies when they come to work as part of a team, as well as their performance at work. Taking these issues into consideration, we suggest four hypotheses: (H1) students improve their teamwork capacity through specific training and carrying out of a set of activities integrated into an active learning process; (H2) students with higher mastery motivation have a better attitude towards teamwork; (H3) students with different types of motivations reach different levels of academic performance; and (H4) students show different motivation profiles in different circumstances: type of courses, teaching methodologies, different times of the learning process. This study was carried out with Computer Science Engineering students from two Spanish universities. The first results point to an improvement in teamwork competence of students if they have previously received specific training in facets of that competence. Other results indicate that there is a correlation between the motivational profiles of students and their perception of teamwork competence. Finally, results point to a clear relationship between some kind of motivation and academic performance. In particular, four kinds of motivation are analyzed and students are classified into two groups according to them. After analyzing several marks obtained in compulsory courses, we perceive that those students that show higher motivation for avoiding failure obtain, in general, worse academic performance.

Student academic performance stochastic simulator based on the Monte Carlo method

In this paper, a computer-based tool is developed to analyze student performance along a given curriculum. The proposed software makes use of historical data to compute passing/failing probabilities and simulates future student academic performance based on stochastic programming methods (MonteCarlo) according to the specific university regulations. This allows to compute the academic performance rates for the specific subjects of the curriculum for each semester, as well as the overall rates (the set of subjects in the semester), which are the efficiency rate and the success rate. Additionally, we compute the rates for the Bachelors degree, which are the graduation rate measured as the percentage of students who finish as scheduled or taking an extra year and the efficiency rate (measured as the percentage of credits of the curriculum with respect to the credits really taken). In Spain, these metrics have been defined by the National Quality Evaluation and Accreditation Agency (ANECA). Moreover, the sensitivity of the performance metrics to some of the parameters of the simulator is analyzed using statistical tools (Design of Experiments). The simulator has been adapted to the curriculum characteristics of the Bachelor in Engineering Technologies at the Technical University of Madrid(UPM).

Relationships among multiple intelligences, motor performance and academic achievement in secondary school children

This study examines the relationships between multiple intelligences, academic achievement and motor performance in a group of secondary school children. Four hundred and eighty schoolchildren participated in this study (171 female and 309 male) with an average age of 13.33 years (SD: 1.41). The Revised self-efficacy Inventory for Multiple Intelligences (IAIM-R) and the motor test Sportcomp were applied, and the average results of the academic year they had made were obtained. The analysis of the results showed how female scored significantly higher on the Linguistic, Spatial and Interpersonal intelligences, and older pupils scored significantly higher on the linguistic and naturalistic intelligences. It was the logical-mathematical intelligence which showed significant relationships with academic performance and it was the intelligence that better predicted this achievement. It was the bodily-kinesthetic intelligence that was significantly related to motor competence and the best intelligence that predicted its achievement. Finally, indicate that schoolchildren with better scores in the motor test were those who scored higher in both academic achievement and all the multiple intelligences, with the exception of musical intelligence.

Teamwork competence and academic motivation in computer science engineering studies.

The present work is focused on studying two issues: the “teamwork” generic competence and the “academic motivation”. Currently the professional profile of engineers has a strong component of teamwork. On the other hand, motivational profile of students determines their tendencies when they come to work in team, as well as their performance at work. In this context we suggest four hypotheses: (H1) students improve their teamwork capacity by specific training and carrying out a set of activities integrated into an active learning process; (H2) students with higher mastery motivation have better attitude towards team working; (H3) students with higher mastery motivation obtain better results in academic performance; and (H4) students show different motivation profiles in different circumstances: type of courses, teaching methodologies, different times of the learning process. This study was carried out with computer science engineering students from two Spanish universities. The first results point to an improvement in teamwork competence of students if they have previously received specific training in facets of that competence. Other results indicate that there is a correlation between the motivational profiles of students and their perception about teamwork competence. Finally, and contrary to the initial hypothesis, these profiles appear to not influence significantly the academic performance of students.

Accurate Simulation of MPPT Methods Performance When Applied to Commercial Photovoltaic Panels

Anew, simple, and quick-calculationmethodology to obtain a solar panel model, based on the manufacturers’ datasheet, to perform MPPT simulations, is described. The method takes into account variations on the ambient conditions (sun irradiation and solar cells temperature) and allows fast MPPT methods comparison or their performance prediction when applied to a particular solar panel. The feasibility of the described methodology is checked with four different MPPT methods applied to a commercial solar panel, within a day, and under realistic ambient conditions.

A characterisation of passive and active interactions and their influence on student's achievement using Moodle LMS Logs

During the last years, there has been much concern about learning management systems' (LMS) effectiveness when compared to traditional learning and about how to assess students' participation during the course. The tracking and monitoring capabilities of most recent LMS have made it possible to analyse every interaction in the system. The issues addressed on this study are: a) Is LMS student's interaction an indicator of academic performance?; b) Are different results in performance expected between distance and in-class LMS-supported education?; c) How can LMS interactions from logs be categorised?; d) May this categorisation detect 'learning witnesses'? To answer these questions, a set of interaction types from Moodle LMS activity record logs has been analysed during two years in online and in-class Master's degrees at the UPM. The results show partial or no evidence of influence between interaction indicators and academic performance, although the proposed categorisation may help detect learning witnesses.

Analytic model of a cache-only memory architecture

An approximate analytic model of a shared memory multiprocessor with a Cache Only Memory Architecture (COMA), the busbased Data Difussion Machine (DDM), is presented and validated. It describes the timing and interference in the system as a function of the hardware, the protocols, the topology and the workload. Model results have been compared to results from an independent simulator. The comparison shows good model accuracy specially for non-saturated systems, where the errors in response times and device utilizations are independent of the number of processors and remain below 10% in 90% of the simulations. Therefore, the model can be used as an average performance prediction tool that avoids expensive simulations in the design of systems with many processors.

Numerical simulation of Ge solar cells using D-AMPS-1D code

A solar cell is a solid state device that converts the energy of sunlight directly into electricity by the photovoltaic effect. When light with photon energies greater than the band gap is absorbed by a semiconductor material, free electrons and free holes are generated by optical excitation in the material. The main characteristic of a photovoltaic device is the presence of internal electric field able to separate the free electrons and holes so they can pass out of the material to the external circuit before they recombine. Numerical simulation of photovoltaic devices plays a crucial role in their design, performance prediction, and comprehension of the fundamental phenomena ruling their operation. The electrical transport and the optical behavior of the solar cells discussed in this work were studied with the simulation code D-AMPS-1D. This software is an updated version of the one-dimensional (1D) simulation program Analysis of Microelectronic and Photonic Devices (AMPS) that was initially developed at The Penn State University, USA. Structures such as homojunctions, heterojunctions, multijunctions, etc., resulting from stacking layers of different materials can be studied by appropriately selecting characteristic parameters. In this work, examples of cells simulation made with D-AMPS-1D are shown. Particularly, results of Ge photovoltaic devices are presented. The role of the InGaP buffer on the device was studied. Moreover, a comparison of the simulated electrical parameters with experimental results was performed.

Measuring the influence of Cooperative Learning and Project Based Learning on problem solvin skill.

The aim of this study is to evaluate the effects obtained after applying two active learning methodologies (cooperative learning and project based learning) to the achievement of the competence problem solving. This study was carried out at the Technical University of Madrid, where these methodologies were applied to two Operating Systems courses. The first hypothesis tested was whether the implementation of active learning methodologies favours the achievement of ?problem solving?. The second hypothesis was focused on testing if students with higher rates in problem solving competence obtain better results in their academic performance. The results indicated that active learning methodologies do not produce any significant change in the generic competence ?problem solving? during the period analysed. Concerning this, we consider that students should work with these methodologies for a longer period, besides having a specific training. Nevertheless, a close correlation between problem solving self appraisal and academic performance has been detected.

Tutoring and mentoring project for foreign students of forest engineering degrees

We present an innovative educational project dedicated to improve the academic performance of foreign students by enhancing the integration of international students during their academic attendance in the programs offered at Universidad Politécnica de Madrid?s School of Forest Engineering (Spain).

Good and bad practices in pv plants

The PVCROPS project (PhotoVolta ic Cost r€duction, Reliability, Operational performance, Prediction and Simulation), cofinanced by European Commission in the frame of Seventh Framework Programme, has compiled in the “Good and bad practices: Manual to improve the quality and reduce the cost of PV systems” a collection of good and bad practices in actual PV plants . All the situations it collects represent the state-of-the-art of existing PV installations all around Europe. They show how the different parts of an installation can be implem ented properly or not. The aim of this manual is to represent a reference text which can help any PV actor (installers, electricians, maintenance operators, owners, etc.) not only to check and improve an already existing installation but will also, and mainly, avoid the previously known bad practices for the construction of a new PV installation. Thus, solving a priori the known errors, new PV installations will be more reliable, efficient and cost-effective and can recover the initial investment in a shorter time. The manual is going to be free available in the PVCROPS website in several languages.