Ensuring access to quality education and career training is a crucial challenge, especially in developing nations. Vocational, scientific, technological, and engineering education are essential for active participation in any community and play a significant role in shaping life perspectives. The ability to sustain competitiveness depends on receiving high-quality vocational, scientific, technological, or engineering education and professional growth. These factors are vital for the long-term growth of prosperous economies and nation-building. Hence, this perspective review attempts to provide information on some contemporary pedagogies in science, technology, engineering, and mathematics (STEM) and science, technology, engineering, arts, and mathematics (STEAM) vis-à-vis scientific and engineering education in Nigeria. The study zooms into the challenges and possible solutions that will promote and enhance pedagogies in scientific and engineering education in Nigeria. The study adopted a perspective review approach in overviewing prior accessible studies (literatures) as well as a methodological framework. It is believed that this perspective review study will serve as a way forward for other developing nations.

More and more urban studies researchers and students are using images. This choice often stems from the need to illustrate, analyse and understand territories and urban phenomena. This contribution seeks to demonstrate, on the basis of examples drawn from scientific productions in Greater Lomé, how the photographic approach makes it possible to apprehend the urban phenomenon. Three forms of image use can be identified in the documents consulted. On the one hand, images are a source of data to support information received through observation. On the other hand, photography is a technique for collecting metadata which, when triangulated with several sources, enables a query to be answered. Finally, the diachronic and chronological analysis of images of a social reality enables us to detect the visible and the invisible in order to take a critical look at the social world and the dynamics of social relationships.

In this paper, we assess the results of experiment with different machine learning algorithms for the data classification on the basis of accuracy, precision, recall and F1-Score metrics. We collected metrics like Accuracy, F1-Score, Precision, and Recall: From the Neural Network model, it produced the highest Accuracy of 0.129526 also highest F1-Score of 0.118785, showing that it has the correct balance of precision and recall ratio that can pick up important patterns from the dataset. Random Forest was not much behind with an accuracy of 0.128119 and highest precision score of 0.118553 knit a great ability for handling relations in large dataset but with slightly lower recall in comparison with Neural Network. This ranked the Decision Tree model at number three with a 0.111792, Accuracy Score while its Recall score showed it can predict true positives better than Support Vector Machine (SVM), although it predicts more of the positives than it actually is a majority of the times. SVM ranked fourth, with accuracy of 0.095465 and F1-Score of 0.067861, the figure showing difficulty in classification of associated classes. Finally, the K-Neighbors model took the 6th place, with the predetermined accuracy of 0.065531 and the unsatisfactory results with the precision and recall indicating the problems of this algorithm in classification. We found out that Neural Networks and Random Forests are the best algorithms for this classification task, while K-Neighbors is far much inferior than the other classifiers.

Rising fuel prices can affect driver behavior and thus the number of accidents, which is a key road safety issue. The aim of this paper was to assess and quantify the relationship between fuel prices (FP) and the number of road accidents in Europe. Content analysis of statistics from the countries was used to collect data, which were examined using Ramsey resets and Poisson distributions and then processed using negative binomial regression (NB), cluster analysis and visualization using contour plots. The results show that in Germany and Poland there is a statistically significant low negative correlation between fuel price and the number of traffic accidents, while in the Czech Republic and Denmark the relationship is weaker and statistically insignificant. In Iceland, no significant correlation was found. The contribution of this paper is to provide important insights that can be used in the development of transport policies and regulations to improve road safety. The main limitations include the difficulty of data collection, as many countries do not publish detailed statistics, and the low number of accidents in Iceland, which makes it impossible to perform a robust analysis for this country and may cause generalization of the results.

This article evaluates the Didactic Strategies for Teaching Mathematics (DSTM) program, designed to enhance the teaching of mathematical content in primary and secondary education in a hybrid modality. In alignment with SENACYT’s Gender-STEM-2040 Policy, which emphasizes gender equality as a foundational principle of education, this study aims to assess whether initial teacher training aligns with this policy through the use of mathematical strategies promoting gender equality. A descriptive-correlational approach was applied to a sample of 64 educators, selected based on their responses during the training, with the goal of improving teaching and data collection methodologies. Findings indicate that, although most teachers actively engage in training, an androcentric approach persists, with sexist language and a curriculum that renders girls invisible, hindering the fulfillment of the National Gender Equality Policy in Science, Technology, and Innovation of Panama (Gender-STEM Policy 2040). Additionally, through a serendipitous finding, a significant gap in student activity levels, especially in secondary school, was discovered. While in primary school, activity levels were similar between genders, a decline in active participation among girls in secondary school was observed. This discovery, not initially contemplated in the study’s objectives, provides valuable insights into gender differences in active participation, particularly in higher educational stages. The serendipity suggests the need for further exploration of social, environmental, and family factors that may influence this decrease in girls’ active participation. The article concludes with a preliminary diagnosis and a call to deepen gender equality training and the effective implementation of coeducation in Panama’s educational system.