Una de las características del curso 2019-2020, en la Educación Superior, fue la intensificación del uso de las Tecnologías de la Información y la Comunicación como consecuencia de la irrupción del COVID-19. Esta situación se prolongó en el curso 2020-2021, caracterizado por la incertidumbre derivada del cambio de situación sanitaria y un reajuste del tipo de modalidad docente presencial a híbrida u online. Así, este trabajo expone las estrategias adoptadas por el profesorado de asignaturas de diferentes áreas (ciencias sociales e ingenierías) de dos universidades públicas (Universitat de València y Universidad Rey Juan Carlos) para adaptar el proceso de enseñanza-aprendizaje, así como el alumnado. ' evaluación de la gestión del profesorado. Cabe destacar el volumen de trabajo que ha supuesto la adaptación de la metodología docente, requiriendo la digitalización de algunas actividades, y la disparidad de estrategias según las características de las asignaturas ya que, a modo de ejemplo, el perfil del alumnado en asignaturas obligatorias difiere del de asignaturas optativas. Cuando se encuestó a los alumnos sobre la gestión del profesorado, ésta fue más que aceptable (media de 8,9 sobre 10). Sin embargo, la acogida fue más favorable en las materias optativas que en las obligatorias (media de 9,8 vs. 8,2).-------------------------------------------------- ---------------------------------- One of the characteristics of the 2019-2020 academic year, in Higher Education, was the intensification of the use of Information and Communication Technologies as a consequence of the irruption of COVID-19. This situation was prolonged in 2020-2021, characterized by the uncertainty derived from the changing health situation and a readjustment of the type of face-to-face teaching modality to hybrid or online. Thus, this work exposes the strategies adopted by the teaching staff of subjects in different areas (social sciences and engineering) of two public universities (Universitat de València and Universidad Rey Juan Carlos) to adapt the teaching-learning process, as well as the students' assessment of the teaching staff's management. It is worth highlighting the volume of work involved in adapting the teaching methodology, requiring the digitalization of some activities, and the disparity of strategies according to the characteristics of the subjects since, as an example, the profile of students in compulsory subjects differs from that of elective subjects. When the students were polled about the management of the teaching staff, it was more than acceptable (average of 8.9 out of 10). However, the reception was more favorable in elective subjects than in compulsory subjects (mean of 9.8 vs. 8.2).

The clinical course of COVID-19 is highly variable. It is therefore essential to predict as early and accurately as possible the severity level of the disease in a COVID-19 patient who is admitted to the hospital. This means identifying the contributing factors of mortality and developing an easy-to-use score that could enable a fast assessment of the mortality risk using only information recorded at the hospitalization. A large database of adult patients with a confirmed diagnosis of COVID-19 (n = 15,628; with 2,846 deceased) admitted to Spanish hospitals between December 2019 and July 2020 was analyzed. By means of multiple machine learning algorithms, we developed models that could accurately predict their mortality. We used the information about classifiers' performance metrics and about importance and coherence among the predictors to define a mortality score that can be easily calculated using a minimal number of mortality predictors and yielded accurate estimates of the patient severity status. The optimal predictive model encompassed five predictors (age, oxygen saturation, platelets, lactate dehydrogenase, and creatinine) and yielded a satisfactory classification of survived and deceased patients (area under the curve: 0.8454 with validation set). These five predictors were additionally used to define a mortality score for COVID-19 patients at their hospitalization. This score is not only easy to calculate but also to interpret since it ranges from zero to eight, along with a linear increase in the mortality risk from 0% to 80%. A simple risk score based on five commonly available clinical variables of adult COVID-19 patients admitted to hospital is able to accurately discriminate their mortality probability, and its interpretation is straightforward and useful.

A novel methodology is proposed for defining multivariate raw material specifications providing assurance of quality with a certain confidence level for the critical to quality attributes (CQA) of the manufactured product. The capability of the raw material batches of producing final product with CQAs within specifications is estimated before producing a single unit of the product, and, therefore, can be used as a decision making tool to accept or reject any new supplier raw material batch. The method is based on Partial Least Squares (PLS) model inversion taking into account the prediction uncertainty and can be used with historical/happenstance data, typical in Industry 4.0. The methodology is illustrated using data from three real industrial processes.

IMPACT OF THE HEALTH ALARM ON THE TEACHING-LEARNING PROCESS IN UNDERGRADUATE AND POSTGRADUATE STUDIES

Appears in: EDULEARN22 Proceedings Publication year: 2022Pages: 6868-6873ISBN: 978-84-09-42484-9ISSN: 2340-1117doi: 10.21125/edulearn.2022.1614Conference name: 14th International Conference on Education and New Learning TechnologiesDates: 4-6 July, 2022Location: Palma, Spain

On March 11th 2020, ten years after the implementation of the syllabus derived from the Bologna Process, the World Health Organization (WHO) declared COVID-19 a pandemic for the first time. Three days later, the Spanish government decreed a state of alarm leading to, among other consequences, the suspension of face-to-face classes at all educational levels across the board. Suddenly most teachers and students found themselves in an unprecedented situation that demanded swift action, for which few resources were available and great efforts were required.This work presents the adapting process to the new sanitary crisis for a subject within the syllabus of an official master degree at the Universitat de València, for which the teaching-learning process occurred both before, during and after the adaptation to the health emergency situation.It must be noted that, in this case, higher priority was given to the use of some Information and Communication Technologies (ICTs) over others. As an example, Audience Response Systems (ARS) requiring the student’s presence saw their use diminished while video tutorials, prepared by the teaching staff themselves, became a more frequent resource aimed mainly at complimenting the part of the syllabus related to the use of software. At the same time, questionnaires were prepared to better assess the student’s progress in absence of direct face-to-face communication.A preliminary analysis of the gathered information allows concluding that the adapting process was successful. In terms of academic performance, all of the students attending the first examination session (80% of those enrolled) passed the subject, similarly to previous promotions.With regards to the students’ perception, their assessment of the ICTs was found to be slightly less positive than it was compared to the previous promotion, but positive nonetheless. On the other hand, they regarded video tutorials in a more positive light in terms of how useful they found them to better understand the concepts taught during the course.

La irrupción en nuestra sociedad de la COVID-19 ha supuesto un gran impacto en el campo de la Educación Superior, que ha necesitado reajustar y adaptar todas las actividades que intervienen en el proceso de enseñanza-aprendizaje: desde la preparación de materiales didácticos e impartición de las materias hasta la evaluación de las mismas. Los dos agentes implicados, profesorado y alumnado, han ido sorteando, en este último curso académico, los embites de la pandemia que, en la mayoría de los casos, ha provocado cambios de escenario: desde la docencia presencial a la docencia online, pasando por formatos híbridos. En estas circunstancas, ha resultado más complicado de lo habitual separar la vertiente personal y académica, pues la situación de una ha impactado más clara y fuertemente en la otra. Parece, por tanto, conveniente analizar cómo ha percibido el alumnado el impacto de la alarma sanitaria, en este periodo académico de su vida, en su motivación, asimilación y evaluación de los contenidos de las materias, etc. Así, en este trabajo se realiza dicho estudio a partir de los datos proporcionados, mediante un cuestionario ad-hoc, por los estudiantes de una asignatura optativa corespondiente al plan de estudios de un doble grado ofertado por la Universitat de València. Un primer análisis de los mismos permite concluir que, aunque existe unanimidad en cuanto a la acertada gestión del profesorado ante la complicada situación, el impacto no es homogéneo si se desagrega al alumando atendiendo a sus prioridades en la elección de la titulación, constatándose diferencias significativas entre los que habían seleccionado este doble grado como primera opción y el resto.

Appears in: EDULEARN21 Proceedings Publication year: 2021Pages: 8388-8393ISBN: 978-84-09-31267-2ISSN: 2340-1117doi: 10.21125/edulearn.2021.1697Conference name: 13th International Conference on Education and New Learning TechnologiesDates: 5-6 July, 2021Location: Online Conference

The complex data characteristics collected in Industry 4.0 cannot be efficiently handled by classical Six Sigma statistical toolkit based mainly in least squares techniques. This may refrain people from using Six Sigma in these contexts. The incorporation of latent variables-based multivariate statistical techniques such as principal component analysis and partial least squares into the Six Sigma statistical toolkit can help to overcome this problem yielding the Multivariate Six Sigma: a powerful process improvement methodology for Industry 4.0. A multivariate Six Sigma case study based on the batch production of one of the star products at a chemical plant is presented.

Latent variable regression model (LVRM) inversion is a relevant tool for finding, if they exist, different combinations of manufacturing conditions that yield the desired process outputs. Finding the best manufacturing conditions can be done by optimizing an appropriately formulated objective function using nonlinear programming. To this end, different formulations of the optimization problem based on LVRM inversion have been proposed in the literature that allow the use of happenstance data (eg, historical data) for this purpose, present lower computational costs than optimizing in the space of the original variables, and guarantee that the solution will conform to the correlation structure of available data from the past. However, these approaches, as presented, suffer from some limitations, such as having to actively modify the constraints imposed on the solution to achieve different sets of conditions to those available in the LVRM calibration dataset, or the lack of a standardized approach for optimizing a linear combination of variables. Furthermore, when minimizing or maximizing one or more outputs, a severe handicap is also present related to the definition of arbitrarily low or high "desired" values. This paper aims at tackling all of these issues. The resulting proposed formulation of the optimization problem is illustrated with three case studies.

An increase in the heterogeneity of the students, with respect to both their curricula and knowledge acquired in previous degrees, constitutes a challenge additional to already existing ones in many teaching-learning processes, especially at the level of master degrees. This will, as a consequence, affect the correct development of activities in the classroom related the program these students access to, as soon as this heterogeneity impacts their competences regarding necessary knowledge in any subject. In this sense, some of the deficiencies detected are related to a lack of experience in the management of spreadsheets, the result of the great variability in the capability to make use of this tools on the students' side. This has, in many cases, a negative impact on the learning and application of concepts in various subjects in which this tool is necessary. Thus, in order to solve this problem, in a master's degree offered by the University of Valencia, the addition into the curriculum of an eight-hour long workshop of voluntary assistance, divided into two sessions, was proposed and implemented. Additionally, a compulsory activity was requested to all students who accessed the master for the first time, in order to evaluate it. This course addressed the use of several tools for their use in some subjects later on, in which spreadsheets were used, such as: modification of sheet format, data management, data analysis, and elaboration of graphics. In order to validate the usefulness of this workshop and, if needed, propose changes in future editions, an ad-hoc questionnaire was prepared and completed by the students at the end of the second session. Thus, a high degree of satisfaction was observed by the students (over 70% of them would recommend it to other students), as well as the need to extend the time dedicated to some of the tools taught (according to almost 80% of the students). On the other hand, the heterogeneity in the level of the students was reflected in the fact that a small percentage of them indicated otherwise. Additionally, a reduction of around 10% was observed in the percentage of students whose level in the use of spreadsheets was lower than that required for quantitative subjects of the master's curriculum, with respect to the previous promotion (in which said workshop was not offered). Thus, in the present work the results are detailed in terms of the improvement observed as a result of the implementation of this workshop, as well as the difference in perception regarding the usefulness of the course depending on the gender and curricula of the students.

The implementation of the Bologna process in Spanish universities, which has been active for a decade as of this academic year, facilitated the implementation of multiple teaching methodologies where numerous Information and Communication Technologies (ICTs) and e-learning tools have had a place. Thus, at this point, an analysis ought to be carried out of the impact that their use may have had on the teaching-learning process for the students. The results from such study will allow selecting the tools that could potentially optimize the results of the aforementioned process. Once the best ones among them have been identified, and taking into account their face-to-face or online nature, it will be posible to make a proposal of which teaching methodologies will lead to the best results in three possible scenarios: face-to-face, online or mixed teaching. While most reaserach in this field focuses on the academic performance as the main output to optimize, measured through the student's qualification, the present work aims at taking the student’s opinion into consideration. Therefore, the perception of the students with regards to some pedagogical tools is assessed in this work. Specifically, two tools have been selected: one face-to-face tool (an Audience Response Tool, H.R.A.) and another e-learning one (a hypermedia container) that, logically, does not require attendance. The data collection required for its posterior analysis was carried out through an ad-hoc questionnaire presented to the students of a degree offered by the University of Valencia,. The first results reflect a better reception to H.R.A., with a higher average score (higher than 8), although e-learning is postulated useful for self-evaluation.

There are few techniques available to calculate the corrosion rate (i(corr)) of reinforcing steel in concrete structures. This is due not only to a lack of instrumentation but also because it is necessary to take into account that polarization can irreversibly modify the metal surface and can affect the results or the future state of the metal. This is the reason some researchers prefer to test reinforcing steel with reversible techniques. The main objective of this study is to predict the corrosion rate of reinforced concrete using electrochemical methods combined with statistical tools such as multivariate analysis. Using reinforcements embedded in mortar samples, the corrosion rates were determined at different ages using the Tafel method, and values obtained were compared with other techniques: linear polarization resistance (LPR), potentiostatic pulse testing (PPT), and AC electrochemical impedance spectroscopy (EIS). In addition, these values were compared to those obtained using a mixed technique based on partial least squares (PLS). With this technique, we were able to automatically analyze the current data obtained from LPR, PPT, and EIS and to predict the i(corr) value. The study allows us to conclude that it is possible to obtain reliable i(corr) values, very close to those obtained with the Tafel method by using PLS combined with PPT or LPR. Furthermore, it presents several advantages, such as being able to directly treat data without requiring an established Stern-Geary constant (B) for LPR and not having to use an equivalent circuit (EC) in EIS to calculate i(corr) because only the impedance spectra are necessary.

In contrast with more traditional teaching methods, based on the so-called master class, the use of other models has been generalized in Higher Education, with the purpose of adapting the teaching-learning process so that the teacher acts more as a support and guide, and the student becomes the protagonist of their own learning. One such model, Flipped Learning (FL), also called Flip Teaching or Flipped Classroom, has been used successfully in both qualitative and quantitative subjects. One of the characteristics of this model is the use of resources that allow students to acquire knowledge necessary to perform activities within it outside the classroom, as well as to obtain feedback on their progress. Among these resources, some remarkable ones are those of an audio-visual nature and the so-called Audience Response Systems (ARS). In addition to assessing the impact that their use may have on the students' academic performance, it is also worth evaluating their perception of the use of these tools in their learning process, if that perception depends on certain factors (motivation, pre-university studies, gender.), etc. This is because, by knowing the impact of these resources in students with a certain profile, the faculty would have relevant information to better schedule the activities to be carried out and tools to make use of. In an attempt to answer the questions raised, the present work reflects the results obtained from assessing of students' perception of these tools for the teaching/assimilation of a quantitative subject of a degree imparted by the University of Valencia. To collect the required data a questionnaire was prepared in which they were asked for information related to the subject in question, as well as questions of a personal nature (pre-university studies, if the center where said studies were conducted was private or public, motivation to access the degree...).

The methodology used in the teaching-learning process in Higher Education has been subject to revision by teachers in recent years, as a consequence of an evolving scenario in which the two agents involved (teachers and students) have seen their roles transformed and had to adapt to these changes in order to optimize their results. In this context, Information and Communication Technologies (ICTs) have exploded both inside and outside the classroom. Thus, the Clickers, an electronic voting system, is one of the ICTs that, together with the videos of academic content, are postulated as tools that provide good results. There are many researches dedicated to the evaluation of the use of this type of tools, from the point of view of their impact on the academic performance of students, usually measured through the qualification obtained by the latter, as well as by the acquisition of competences collected in the syllabus of the subjects. There are, however, not as many studies whose objective is to identify the opinion that students have of the use of ICTs. In this line, this work aims to analyze and quantify, as much as possible, the perception that the students have of the use of both the Clickers and the videos in their learning process. Special emphasis will be made on whether factors such as gender, pre-university studies, if the center where these have been studied was private or public, or the motivation of the students (assessed according to the order of preference of the degree course) influence this perception. For this purpose, the data provided by students of a degree offered by the Universitat de Valencia will be used. The results obtained show that some of the factors mentioned are significant. Thus, by way of example, the gender factor influences their perception, with male students valuing the Clickers more positively than female students. Furthermore, although males tend to resort to videos to a lesser extent than female students, they also provide higher scores when evaluating them.

La reestructuración de los contenidos impartidos en las asignaturas que forman los planes de estudio, así como su ubicación en los mismos, a consecuencia de la redefinición de los últimos planes de estudio, ha dificultado en buena medida la forma en que debe enfocarse el proceso de enseñanza-aprendizaje. A esto se suma el hecho de que muchos alumnos que acceden a la universidad lo hacen con un nivel de conocimientos generalmente inadecuado para el nivel exigido en diversas asignaturas. El presente trabajo se centra, por todo ello, en la propuesta de actividades y uso de medios tecnológicos para la evaluación de los resultados de aprendizaje. Esto se debe a que el grado en que se haya logrado la optimización del proceso de enseñanza-aprendizaje vendrá determinado por la medida en que se hayan conseguido una correcta asimilación de los contenidos de cada materia y la adquisición de las competencias requeridas. La correcta y eficiente evaluación de dicha asimilación resulta, por tanto, indispensable. Para ello se propone, haciendo uso de la gamificación, una actividad por equipos de no más de 8 alumnos. Cada equipo deberá responder a una serie de cuestiones relacionadas con la materia, compitiendo con el resto de equipos por la máxima puntuación. El uso de “Plickers” permitirá recoger todas las respuestas de forma eficiente y precisa, y da la oportunidad a los estudiantes de conocer sus resultados y ‘autoevaluarse’ en tiempo real. De este modo se propicia el trabajo en equipo, y tanto el profesor como los estudiantes revisan los conceptos trabajados y evalúan los resultados de aprendizaje adquiridos.

Latent Variable Regression Model (LVRM) inversion can be an efficient tool to find the so-called Design Space (DS), i.e. the different combinations of inputs (e.g. process conditions, raw materials properties …) that lead to the desired outputs (e.g. product quality, benefits …). This is especially critical when first-principles models cannot be resorted to, running experimental designs is unfeasible and only data from daily production (i.e. historical data) are available. Since data-driven methods are not free of uncertainty, different approaches have been proposed in the literature to delimit a subspace that is expected to contain the DS of a product. However, some of these methods are computationally costly or depend on the existence of at least one combination of inputs that provides, according to the model, the desired values for all output variables simultaneously. Furthermore, no approach to date offers an analytical expression for the confidence region limits for this subspace. In this paper a new way to find the DS is proposed, so the above limitations are overcome. To this end, the analytical definition of the estimation of the DS, and its confidence region limits, as well as a way to transfer restrictions on the original space to the latent space are suggested. An extension of these methods to quality attributes defined as linear combinations of outputs is also provided. The proposed methodology is illustrated using three simulated case studies.