Most relevant characteristics to improve residential energy efficiency

Urban areas play a crucial role in global energy demand and in policies to mitigate climate change. Energy use in residential buildings is one of the main sources of greenhouse gas emissions in cities. Spain has more than 25.8 million dwellings, of which around 9.3 million are more than 50 years old. Of these, 16.4% are in a poor or deficient state of conservation (INE, Population and Housing Census 2011). This situation of obsolescence and poor conservation of the building stock requires a major structural, functional and energy refurbishment. As a research hypothesis, it is proposed that the current Spanish building stock has a great potential for energy savings and CO2 reduction and that with an appropriate selection of interventions aimed at refurbishment it is possible to increase the energy efficiency of buildings and make them more sustainable. The main objective proposed is to identify the architectural, design and building system or installation factors that are most relevant for improving the energy efficiency of existing residential buildings in Spain. A large database with geo-referenced observations of housing energy certificates is used for this purpose. The certificates correspond to individual dwellings located in blocks of buildings in the city of Barcelona (C2 climate zone according to the CTE). From these certificates, information on energy consumption and CO₂ emissions, as well as the technical characteristics of the envelope and heating/cooling systems, can be obtained for each dwelling. The dataset contains information on energy consumption and CO₂ emissions with their rating (energy letter); in addition to the characteristics of the buildings such as the surfaces and transmittances of the envelope (opaque and glazed enclosures), the climate zone, type of dwelling, year and building code, heating and air-conditioning installations, percentage of windows according to orientation, etc. Using a linear regression model, the influence of each housing characteristic on energy consumption and CO₂ emissions can be estimated. The interpretation of the regression coefficients allows determining to what extent energy consumption can be reduced, for example by improving the envelope (opaque or glazed), systems/installations, thermal bridges, among other aspects. The linear regression analysis has shown promising results due to its reasonable accuracy for model estimation, and the relative simplicity of its application and interpretation compared to other methods (Fumo et al., 2015).Financiado por la Generalitat Valenciana: Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital (GV/2021/131)

The influence of housing location on energy ratings price premium in Alicante, Spain

Location is, along with other aspects, one of the most important characteristics when determining the sale or rental price of a residential property. Energy rating is one of the characteristics involved in determining the rent or sale price of a house. Past research has shown the importance of this attribute in numerous studies. Moreover, these studies have found mixed results regarding the magnitude, direction, and statistical significance of energy rating price premiums. This research aims to determine whether housing location influences energy rating price premium. To achieve this objective, a least squares regression model and a multilevel model were estimated using a sample of 70,170 different residences that were offered for sale in the province of Alicante. The multilevel models show that, once the differences due to the location (comarca) had been eliminated, the energy rating label itself had an effect on the asking price and also that there was an effect for the relationship of the energy rating with the location characteristics (comarca). On the other hand, the variables that defined the energy ratings were not those responsible for the differences between the average asking prices of the residences in the comarcas

Taxonomía de los estudiantes del grado en Arquitectura Técnica

Se pretende realizar un estudio que permita reconocer y clasificar los distintos perfiles de los estudiantes del grado en Arquitectura Técnica en función de sus resultados académicos. Existen estudiantes con mayores habilidades en el lenguaje escrito, en matemáticas o en dibujo, favoreciendo mejores resultados en unas asignaturas más afines a esas habilidades. Para ello se han recogido los resultados académicos de los estudiantes en las asignaturas del primer curso de la titulación, se ha realizado un estudio de correlación entre los resultados de las asignaturas y un posterior análisis de conglomerados que permite agrupar a los estudiantes en distintas agrupaciones o clases (taxonomía). Esta clasificación permite identificar en qué asignaturas destaca cada grupo de estudiantes y en cuáles tienen mayores dificultades. El conocer estos perfiles puede ayudar en la toma de decisiones para la orientación académica de los estudiantes, ayudando a identificar futuras debilidades en función de las características del alumnado

Factores determinantes del rendimiento académico en el grado de Arquitectura Técnica de la Universidad de Alicante

El rendimiento académico de los estudiantes universitarios está influenciado por una gran diversidad de factores y es uno de los elementos que influye principalmente al abandono de las enseñanzas universitarias. Conocer los factores que pueden estar interviniendo en el rendimiento académico de los estudiantes puede resultar de vital importancia para mejorar el proceso de enseñanza-aprendizaje y la calidad universitaria. En esta investigación se pretende determinar los posibles factores que influyen en el rendimiento académico de los estudiantes universitarios del grado en Arquitectura técnica de la Universidad de Alicante. El estudio se ha centrado en determinar el poder explicativo y predictivo de siete variables para pronosticar el rendimiento académico de los estudiantes. Los resultados arrojan que cinco de las variables estudiadas son estadísticamente significativas y que dos de ellas tienen una gran influencia sobre el rendimiento académico

Factors involved in the academic performance of students of Technical Architecture degree from the University of Alicante

The academic performance of university students is influenced by a wide variety of factors and is one of the main elements which influence students’ leaving their university studies. Knowing which factors and, to what extent they may be taking part in students’ academic performance, would be of the utmost importance in improving the teaching-learning process, the university excellence and the students’ academic performance. It is the aim of this study to identify the potential factors which influence in the academic performance of the students of the degree in Technical Architecture. The study focuses on determining the explanatory and predictive power of seven variables so as to predict the students’ academic performance throughout three academic courses. We used the statistical technique of multiple linear regression, in which statistically significant variables and the relative importance each of them has upon the academic performance of students have been identified.This research has been supported financially under the “University Teaching Research Networks Project 2013-2014”, supported by the Pro-Vice-Chancellor of Strategic Planning and Quality and the Institute of Education Sciences at the University of Alicante

Housing Price Prediction Using Machine Learning Algorithms in COVID-19 Times

Machine learning algorithms are being used for multiple real-life applications and in research. As a consequence of digital technology, large structured and georeferenced datasets are now more widely available, facilitating the use of these algorithms to analyze and identify patterns, as well as to make predictions that help users in decision making. This research aims to identify the best machine learning algorithms to predict house prices, and to quantify the impact of the COVID-19 pandemic on house prices in a Spanish city. The methodology addresses the phases of data preparation, feature engineering, hyperparameter training and optimization, model evaluation and selection, and finally model interpretation. Ensemble learning algorithms based on boosting (Gradient Boosting Regressor, Extreme Gradient Boosting, and Light Gradient Boosting Machine) and bagging (random forest and extra-trees regressor) are used and compared with a linear regression model. A case study is developed with georeferenced microdata of the real estate market in Alicante (Spain), before and after the pandemic declaration derived from COVID-19, together with information from other complementary sources such as the cadastre, socio-demographic and economic indicators, and satellite images. The results show that machine learning algorithms perform better than traditional linear models because they are better adapted to the nonlinearities of complex data such as real estate market data. Algorithms based on bagging show overfitting problems (random forest and extra-trees regressor) and those based on boosting have better performance and lower overfitting. This research contributes to the literature on the Spanish real estate market by being one of the first studies to use machine learning and microdata to explore the incidence of the COVID-19 pandemic on house prices

Online Teaching in Construction of Structures: Participative Tools

In the last years, traditional teaching has turned around to blended teaching, enabling students and teachers to have a continuous exchange of documentation by using new technologies in the classroom. This kind of teaching is increasingly significant as it combines traditional methods with innovative applications that allow online tracking. This proposal is applied in the subjects “Construction of Structures I and II” of the Degree in Building Engineering; it implements new methodologies as an alternative to traditional education, strengthening theoretical and practical contents by performing exercises that are corrected in a participatory way using online tools. The aim of this paper is to analyse the use of these tools (such as online tests, participation in forums, virtual tutorials, download of documentation, etc.) in the Moodle platform to encourage interaction and learning. The delivery of online exercises reinforces the acquisition of specific skills and facilitates communication both between teacher-student and between the students themselves. In conclusion, the use of these online tools offered by the Moodle platform has enabled continuous and participatory learning in Construction of Structures; this new proposal is highly valued by students as it allows direct and personalized monitoring by teachers

Teachers’ Features in the Degree of Building Engineering at the University of Alicante

All new university degrees (implemented a few years ago) are undergoing a process to renew the accreditation of qualifications (ACREDITA program) by quality assessment and accreditation agencies. This process aims to "check whether the results of the degree are suitable and guarantee the continuity of their teaching until the next reaccreditation"; to do so, the assessment is structured in two main phases. First, a self-evaluation is performed where each university describes and assesses the situation of the degree considering several guidelines and criteria. Second, there is an external evaluation in which an accrediting agency makes a valuation of the situation to verify the degree of compliance with the conditions mentioned above. There are three internationally recognized quality principles which are valued in the ACREDITA program: title management, resources and results; at the same time, these dimensions are subdivided into seven criteria. One of these criteria is to assess the academic profile of teachers who teach in every university degree, a key feature throughout the entire teaching process. The present research aims to contextualize the evolution and current situation of the academic staff who teaches and has taught in the Degree of Building Engineering at the University of Alicante, to establish proposals for the improvement during the monitoring of the title. To this end, we have analysed the results of the main indicators used by quality agencies, as well as other characteristics proposed by the authors to draw conclusions about the reality of university teachers

Geometry in 18th Century Bell Towers in Bajo Segura, Spain

Bell towers are essential elements of religious architecture, which have been part of villagers’ lives for centuries and have marked their identity and orientation from a far distance. This research provides widens our knowledge of geometrical aspects of bell towers through a search for common building patterns. Throughout the history of construction and architecture, there have been specific studies about particular bell towers, but few have taken a more general approach, studying 18th-century architectural treatises and building warnings for ecclesiastical buildings after the Council of Trent. In the Spanish ecclesiastical territorial organisation, the Diocese of Orihuela and its region (Bajo Segura) had great importance, with outstanding social development and territorial expansion due to the colonising action of the clergy and nobility in the 18th century. In 1829, an earthquake had destructive effects on the area’s architectural heritage. This paper studies the bell towers that endured the earthquake by recording data in situ, generating a catalogue, and analysing and comparing the data obtained. The results outline a construction model that meets the established guidelines of the architectural treatises as far as geometrical proportions and building patterns are concerned

Method for quality evaluation of digital learning tools

The students´ overcrowding in classrooms and the offer of digital media courses imply the need of new learning objects in education, as these reusable electronic tools allow objective evaluation in large groups by using few resources. The aim of this research is a proposal for a massive assessment in the quality of digital learning tools used in the students´ learning process, by using statistical methods (cluster analysis). This method facilitates the classification and identification of gaps within the assessment and self-learning instruments from different psychometric indicators. The research corresponds to a study case using a learning virtual platform (moodle) where different digital learning objects were implemented and used by students as tools for learning and assessment. Teachers analysed the results applied to objective evaluation and self- assessment tests, which determined whether they were properly designed learning activities and their discriminatory properties. In conclusion, the use of statistical methods massively detected failures or errors in the design of objective tests, allowing an important improvement in the quality and reuse of these resources.This research is based on the findings of the “Research in the use of Learning Object for academic teaching”, and was conducted within the context of the call for proposals issued by the "University Teaching Research Networks Project 2012-2013", supported by the Pro-Vice-Chancellor of Strategic Planning and Quality and the Institute of Education Sciences at the University of Alicante