Facultad de Jurisprudencia y Ciencias Políticas
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Learning Natural Science Through Interactive Resources

2025 , Becerra García, Eulalia , Yánez Rueda, Hugo , Mora Rosales, José

Learning Natural Sciences through interactive resources enhances the understanding of complex concepts by offering visual and hands-on experiences. These tools allow students to explore natural phenomena, perform simulated experiments and visualize processes invisible in real life. Objective: Examine how interactive tools influence the retention of complex natural science concepts. Methodology: It follows a positivist paradigm, with a quantitative approach, a field study and a sample of 60 elementary school students to whom a questionnaire was applied to measure knowledge before and after applying the interactive resources. Results: A course was created within the Moodle virtual learning environment focused on improving the learning of Natural Sciences with interactive resources elaborated in the technological tools: powtoon, Phet Interactive Simulations and H5p Interactive with selected topics of natural sciences based on their pedagogical relevance and the capacity of concepts to be exploited with interactive simulators. Conclusions: Interactive resources were developed to improve natural science learning, with technological tools that made the contents more interactive, visual and accessible.

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The Evolution of E-voting and its Application on Electoral Process Abroad

2024 , Saltos-Hidalgo, Tatiana , Alex Fabián Mejía-Sandoval , Anthony Gaon-Cajamarca

The study analyzes the implementation of evoting in our democracies, based on the current discussion about its challenges to enhance our confidence in political institutions. The proposal aims to establish the aspects involved in this electoral mechanism, particularly in elections abroad.The scientific method is qualitative, based on the results of previous research and the data obtained from the electoral process in Ecuador when electronic voting was implemented. Moreover, it includes a descriptive analysis of the types of e-voting. The findings reveal a lack of global continuity in the adoption of e-voting due to cost, system reliability and political confidence concerns, causing the inverse effect in populations with low levels democratic participation as migrants. The study concludes in the examination of each country's context and electoral infrastructure, as essential to determine the most suitable e-voting modality based on pilot test results.

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Unraveling Psycholaboral Risk Factors: Ordinal Prediction of Teacher Well-Being in University Institutions in Ecuador

2025 , Espinosa Pinos, Carlos Alberto , Acosta Pérez, Paul Bladimir , Valarezo Calero, Camila

This article investigates the factors that affect the job satisfaction of university teachers for which 400 teachers from 4 institutions (public and private) were stratifiedly selected, resulting in a total of 1600 data collected through online forms. The research was of cross-sectional design and quantitative type using an ordinal logistic regression model, analyzing variables such as ethnic identity, field of knowledge, gender, number of children, job burnout, perceived stress and occupational risk. The results indicate that teachers belonging to ethnic groups such as Ethnicity White, Mestizo and Montubio have higher job satisfaction probabilities of 96.7%, 92.3% and 115.3%, respectively. In addition, teachers in Humanities and Communication and Information Sciences report higher job satisfaction, with increases of 53.7% and 55.6%. In contrast, those who identify as “Other” in terms of gender experience a 21.2% decrease in satisfaction. Each additional child is associated with a 21.2% decrease in job satisfaction, while an increase in Work-Related Burnout, Perceived Stress, and Occupational Risk is associated with decreases of 27.3%, 16.2%, and 31.4%, respectively. These findings highlight the need for inclusive policies and effective strategies to improve teacher well-being in the academic university environment

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Enhancing Industrial Processes Through Augmented Reality: A Scoping Review

2025 , Miranda, Alba , Aracely M. Vallejo , Paulina Ayala , Marcelo V. Garcia , Jose E. Naranjo

Augmented reality (AR) in industry improves training and technical assistance by overlaying digital information on real environments, facilitating the visualisation and understanding of complex processes. It also enables more effective remote collaboration, optimising problem solving and decision making in real time. This paper proposes a scoping review, using PRISMA guidelines, on the optimisation of industrial processes through the application of AR. The objectives of this study included characterising successful implementations of AR in various industrial processes, comparing different hardware, graphics engines, associated costs, and determining the percentage of optimisation achieved through AR. The databases included were Scopus, SpringerLink, IEEExplore, and MDPI. Eligibility criteria were defined as English-language articles published between 2019 and 2024 that provide significant contributions to AR applications in engineering. The Cochrane method was used to assess bias. The rigorous selection process resulted in the inclusion of 38 articles. Key findings indicate that AR reduces errors and execution times, improves efficiency and productivity, and optimises training and maintenance processes, leading to cost savings and quality improvement. Unity 3D is the most widely used graphics engine for AR applications. The main applications of AR are in maintenance, assembly, training and inspection, with maintenance being the most researched area. Challenges include the learning curve, high initial costs, and hardware limitations.

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The Impact of Gamification on Reading Comprehension: Transforming Literacy Skills Among High School Students in Puyo, Ecuador

2025 , Moyano Barahona, Álvaro , Espinosa Pinos, Carlos Alberto , Amaluisa Rendón, Paulina Magally

This research investigates the impact of gamification on reading comprehension among high school students in Puyo and Pastaza, Ecuador, where traditional methods face challenges compounded by limited technology access, COVID-19 disruptions, and specific community needs. Addressing the inadequacy of traditional approaches, the study explores gamification's potential to improve literacy skills. Employing a quantitative approach, the study involved 100 students divided into experimental and control groups. The experimental group received a gamified intervention using digital tools like Genially, while the control group followed traditional teaching methods. Reading comprehension was assessed using the PROLEC test, evaluating multiple dimensions of reading ability. The experimental group demonstrated significant improvements in reading comprehension, particularly in lexical selection, semantic categorization, and expository comprehension (p < 0.001). Student surveys confirmed increased engagement and motivation through gamification. The findings highlight the positive influence of digital gamification on reading development and critical thinking skills. Gamification positively impacts student engagement and academic performance in reading comprehension, offering an effective and replicable strategy for similar educational settings. However, the study underscores the necessity of robust technological infrastructure and adequate training for educators and students to fully leverage these strategies, ensuring improved literacy skills within challenging environments and addressing existing gaps in public education.

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Predicting Academic Performance in Mathematics Using Machine Learning Algorithms

2022 , Espinosa Pinos, Carlos Alberto , Ayala-Chauvin, Manuel Ignacio , Buele, Jorge

Several factors, directly and indirectly, influence students’ performance in their various activities. Children and adolescents in the education process generate enormous data that could be analyzed to promote changes in current educational models. Therefore, this study proposes using machine learning algorithms to evaluate the variables influencing mathematics achievement. Three models were developed to identify behavioral patterns such as passing or failing achievement. On the one hand, numerical variables such as grades in exams of other subjects or entrance to higher education and categorical variables such as institution financing, student’s ethnicity, and gender, among others, are analyzed. The methodology applied was based on CRISP-DM, starting with the debugging of the database with the support of the Python library, Sklearn. The algorithms used are Decision Tree (DT), Naive Bayes (NB), and Random Forest (RF), the last one being the best, with 92% accuracy, 98% recall, and 97% recovery. As mentioned above, the attributes that best contribute to the model are the entrance exam score for higher education, grade exam, and achievement scores in linguistic, scientific, and social studies domains. This confirms the existence of data that help to develop models that can be used to improve curricula and regional education regulations. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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The Use of Gamification in Mathematics Education: Enhancing Geometry Comprehension with High School Students

2024 , Espinosa Pinos, Carlos Alberto , Alex Mauricio Mazaquiza-Paucar , Clara Augusta Sánchez Benítez

The non-existence or non-application of strategies, methodologies, innovative techniques such as gamification, which offers a more attractive and dynamic way of approaching the mathematical topic about the equation of the line, a concept that is often abstract and difficult to understand for many students. The present study aims to analyze the effectiveness of gamification in the pedagogical process between educators and learners in relation to the understanding of the equation of the line in students of the tenth year of higher EGB. This analysis was carried out through a quantitative approach that included the administration of a knowledge test before and after applying gamification to 92 GBS tenth grade students. These students were divided into two groups of 46 students each, one experimental group (EG) worked on gamification activities and the other control group (CG) employed traditional techniques. The purpose of this division was to determine if there were significant differences in performance means between the two groups. The gamified proposal incorporates elements of games, challenges, rewards and competitions, taking into account the learners in a dynamic way, providing them with a sense of purpose and achievement. After the T-Student application, it was concluded that the proposal not only significantly increases the academic performance of the students, but also develops logical thinking and reasoning, and favors autonomous and collaborative work.

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Ecuador una tierra de contrastes: análisis sobre el bienestar animal en la producción ganadera ecuatoriana y los derechos de la naturaleza

2024 , Molina Torres, María Victoria

The Constitution of the Republic of Ecuador introduces a new perspective regarding environmental protection within the context of an economic, social, and solidarity development model. This approach becomes particularly relevant in addressing animal rights, initiating discussions that have opened new avenues in recognizing their rights as sentient beings. However, substantial success has not been achieved in materializing these rights within the legal framework and in generating effective policies that ensure humane treatment of animals and sustainably improve access to healthy food and sustainable production systems, in line with the social and environmental responsibility of solidarity economy organizations. The objective of this work is to conduct a critical review of animal protection policies within the context of the rights of nature, particularly in livestock production in Ecuador. The aim is to examine how these issues are being addressed, identify existing limitations, and propose possible pathways to progress towards a more just and sustainable balance between economic development, environmental protection, and animal welfare in the Ecuadorian livestock sector.

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Emission inventory processing of biomass burning from a global dataset for air quality modeling

2022 , Pino-Cortés E. , Carrasco S. , Díaz-Robles L.A. , Cubillos F. , Cereceda-Balic F. , Vallejo F. , Fu J.S.

Wildfires generate large amounts of atmospheric pollutants yearly. The development of an emission inventory for this activity is a challenge today, mainly to perform the air quality modeling. There are accessible available databases with historical information about this source. The main goal of this study was to process the results of biomass burning emissions for the year 2014 from the Global Fire Assimilation System (GFAS). The pollutants studied were black carbon, organic carbon, and fine and coarse particulate matter. The inputs were pre-formatted to enter into the simulation software of the emission inventory. In this case, the Sparse Matrix Operator Kernel Emissions (SMOKE) was used, and the values obtained in various cities were analyzed. As a result, the spatial distribution of the forest fire emissions in the Southern Hemisphere was achieved, with the polar stereographic projection. The highest emissions were located in the African continent, followed by the northern region of Australia. Future air quality modeling at a local level could apply the results and the methodology of this study. The biomass burning emissions could add a better performance of the results and more knowledge on the effect of this source. © 2021, The Author(s), under exclusive licence to Springer Nature B.V.

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Classification Tools to Assess Critical Thinking in Automotive Engineering Students

2024 , Espinosa Pinos, Carlos Alberto , Amaluisa Rendón, Paulina Magally , Noemi Viviana Rodríguez Ortiz

Inadequate conflict resolution skills in automotive engineering students can have negative consequences in the workplace. The development of mathematical logical thinking can help students develop critical analysis skills, improve problem-solving ability, develop reasoning skills, and effective communication, enabling them to deal effectively with conflicts and find creative solutions. This research aims to identify predictors of problem-solving ability using classification algorithms. Methodology: In this study, three classification algo-rithms were applied and the KDD process was used to identify predictors of problem-solving ability. The data set includes 60 records of students from the automotive engineering program at Universidad Equinoccial in Quito, Ecuador, to whom three tools were applied: a sociodemographic card, a Shatnawi test related to mathematical logical thinking, and a Watson Glaser test on conflict resolution ability. Results: The best classification model is the K-nearest neighbors’ algorithm and its predictive ability is very good, with a true positive rate versus false positive rate AUC of 0.75, along with a good performance in classifying negative cases. The model can be improved with increased sampling, cross-validation, or hyper-parameter adjustment. Conclusion: Age and mathematical logical thinking are strongly associated with conflict resolution ability. In future research it is important to consider additional variables such as experience in problem-solving projects, technical knowledge and communication skills; to explore the use of more advanced machine learning algo-rhythms; to design specific educational interventions based on the development of mathematical logical thinking; or to compare conflict resolution ability between different engineering disciplines.

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