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There is an increasing need for innovative educational methods that can motivate and engage students in subjects that are often perceived as difficult or boring. One such approach is the UPCT-Bloopbusters educational project, developed by a group of professors at the Universidad Politécnica de Cartagena (UPCT), Spain, wherein concepts from the fields of physics and technology are presented and exemplified in the classroom through scenes from different movies in conjunction with experiments. The project was conducted on three subjects, one from each of the three bachelor of electrical engineering degree programs offered at the UPCT, namely Physics I, Applied Physics, and Optical Communications. This paper describes the methodology of the educational project and then presents and discusses the academic results of the students involved in terms of success and performance rates both before and after the application of the new methodology. Moreover, the results of a survey carried out on the students are presented. Finally, some of the exercises used in this methodology for the teaching and learning of science based on different movie scenes are provided as examples. The results of the project show that the students were receptive of the methodology and further indicated that it may lead to increased academic performance due to their enhanced understanding of physics and technology concepts. [ABSTRACT FROM AUTHOR]

The knowledge of signal demodulation processes using superheterodyne receivers is of great importance in the field of telecommunications. Superheterodyne receivers receive the current focus of many scientists in a wide variety of applications. This topic is part of the syllabus of the Communication Theory course at the School of Telecommunications of the Polytechnic University of Cartagena, Spain. The authors found that the academic performance of the students had not been entirely satisfactory in recent years. This situation was aggravated during the COVID-19 lockdown. Students had to reinforce their knowledge independently at home, despite the support provided by teachers. To the best of the authors' knowledge, there is a noticeable lack of educational tools in this area; of those that are available, they exhibit a mismatch with the specific needs of this subject. This manuscript shows how the design of the educational software tool DOSHER, tailored to enhance the understanding of superheterodyne receivers, successfully alleviated the aforementioned drawbacks. DOSHER was designed, developed, and applied during the 2020–2021 academic year (during the COVID-19 lockdown). The results show that students were not only very satisfied with its use, but they also improved their marks. Analysis of students' academic performance in the year of DOSHER implementation showed an average improvement in their marks of between 9–12% compared with previous years. In 2021–2022, when DOSHER was fully operational from the start, the improvement in terms of pass rate (31%) at the first mid-term was significant compared to previous years (<20%). [ABSTRACT FROM AUTHOR]

This work analyzes the impact of admission grade point average (AGPA) on academic results of electrical engineering university students throughout their undergraduate studies. The analysis was carried out on two bachelor engineering degree programs offered at the School of Telecommunication Engineering at the Universidad Politécnica de Cartagena, Spain: Telecommunication Systems Engineering and Telematics Engineering. Data from seven consecutive academic years were used to compute three indicators regarding the same cohort of students: exam attendance rate, success rate, and performance rate. The results show that although there exists a significant correlation between AGPA and student performance, it is truly relevant only in the first two academic courses (in this work, a course is assumed to be the compilation of all subjects in a year). In view of the results, a set of guidelines is proposed in order to soften the impact of AGPA on the progress of university students. [ABSTRACT FROM AUTHOR]

This work compares the academic performance and retention rates of women and men in electrical engineering studies. The analysis is carried out in two bachelor engineering degree programs offered in the School of Telecommunication Engineering, at the Universidad Politécnica de Cartagena, Spain: Telecommunication Systems Engineering and Telematics Engineering. Data from seven consecutive academic years have been used to compute three indicators regarding the same cohort of students: exam attendance rate, success rate, and performance rate. The results show that, in general, women obtain better academic performance rates than men in the first two academic courses while, from the third course on, there seems to be a trend toward uniformity in the academic results between female and male students. Furthermore, women generally present lower attrition rates than men, especially in the first year, and better graduation rates. Such facts could be explained by the higher motivation of female students when enrolling engineering programs—due to the adverse stereotyped context that they have to overcome—which lead to higher retention rates throughout the academic years as compared to their male counterparts. [ABSTRACT FROM AUTHOR]

Gender-Based Violence (GBV) is a serious problem that societies and governments must address using all applicable resources. This requires adequate planning in order to optimize both resources and budget, which demands a thorough understanding of the magnitude of the problem, as well as analysis of its past impact in order to infer future incidence. On the other hand, for years, the rise of Machine Learning techniques and Big Data has led different countries to collect information on both GBV and other general social variables that in one way or another can affect violence levels. In this work, in order to forecast GBV, firstly, a database of features related to more than a decade's worth of GBV is compiled and prepared from official sources available due to Spain's open access. Then, secondly, a methodology is proposed that involves testing different methods of features selection so that, with each of the subsets generated, four techniques of predictive algorithms are applied and compared. The tests conducted indicate that it is possible to predict the number of GBV complaints presented to a court at a predictive horizon of six months with an accuracy (Root Median Squared Error) of 0.1686 complaints to the courts per 10,000 inhabitants—throughout the whole Spanish territory—with a Multi-Objective Evolutionary Search Strategy for the selection of variables, and with Random Forest as the predictive algorithm. The proposed methodology has also been successfully applied to three specific Spanish territories of different populations (large, medium, and small), pointing to the presented method's possible use elsewhere in the world. [ABSTRACT FROM AUTHOR]