Buele, Jorge

Preferred name

Buele, Jorge

Main Affiliation

Facultad de Ingenierías

Ambato

jorgebuele@uti.edu.ec

ORCID

0000-0002-7556-0286

Scopus Author ID

57200380202

Now showing 1 - 10 of 96

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Ethical Use of Generative Artificial Intelligence Among Ecuadorian University Students
(2025)
Buele, Jorge
;
Ángel Ramón Sabando-García
;
Bosco Javier Sabando-García
;
Yánez Rueda, Hugo
Artificial intelligence has transformed educational environments by facilitating processes such as information retrieval, assisted writing, automated feedback, and personalized tutoring. Within university settings, the adoption of technologies capable of autonomously generating content has increased rapidly, becoming a common academic resource for students. However, this accelerated integration poses ethical challenges, particularly when such tools are used without a clear understanding of their implications. This study aimed to examine how students’ emotional attitudes (affective), understanding (cognitive), and practical use (behavioral) of AI relate to their ethical engagement with these technologies. A structured questionnaire was administered to 833 university students in Ecuador. The instrument showed excellent internal consistency (α = 0.992; Ω = 0.992), and the validity analyses confirmed that the dimensions measured distinct but related constructs. ChatGPT was reported as the most used tool (62.2%), followed by Gemini and Siri. The structural model indicated that emotional and cognitive dimensions substantially influenced ethical behavior (β = 0.413 and β = 0.567, respectively), whereas frequent use alone exhibited no significant effect (β = −0.128; p = 0.058). These results suggest that ethical engagement with AI is primarily driven by reflection and knowledge rather than habit. This study contributes to the literature by modeling how different learning dimensions shape ethical behavior in AI use and underscores the relevance of aligning academic practices with socially responsible uses of emerging technologies.
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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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Analysis of Ergonomic Risks Based on Physical and Postural Characteristics in the Food Industry
(2026)
Buele, Jorge
Musculoskeletal disorders are one of the leading causes of occupational disability worldwide, affecting workers across various industries, particularly in the food industry. These disorders are caused by factors such as improper postures, repetitive movements, and manual handling of loads. Despite efforts to mitigate these risks, ergonomic assessment in many work environments remains insufficient, as it is often limited to posture observation and does not include precise anthropometric measurements. This study aims to integrate anthropometric measurements with the Rapid Entire Body Assessment method for a more accurate and personalized evaluation of ergonomic risks in the food industry. Through a quantitative approach, anthropometric measurements of workers in a food production plant were analyzed and the Rapid Entire Body Assessment method was applied to assess working postures. The data obtained were statistically analyzed to identify correlations between the physical characteristics of employees and musculoskeletal discomfort. The results showed a significant correlation between anthropometric dimensions, such as elbow height and functional reach, with discomfort in areas such as the elbow, knees, and lower back. These findings emphasize the need to adapt workstations to the physical characteristics of employees to prevent injuries. The integration of anthropometric measurements and the Rapid Entire Body Assessment method provides a more accurate tool for assessing ergonomic risks and designing personalized interventions that improve occupational health and productivity in the food industry. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
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Perceptions and Dispositions of Parents and Teachers Toward Technological Learning Communities
(2023)
Núñez-Hernández C.
;
Buele, Jorge
The search for strategies to improve students’ academic performance is increasingly common in education. Parents’ participation and teachers’ attention are key factors in forming a learning community. This article presents the results of a survey in which relevant statistical data was obtained. A significant association (p = 0.571) was found between the frequency with which parents help their children understand school content and their willingness to be part of a learning community, representing 40.65% of the population. In addition, it was found that 66.67% of parents frequently meet with their children’s teachers because they often solve the children’s doubts. Regarding the attention of teachers, it was evidenced that 64.71% of parents who meet very frequently with teachers do so with those who very frequently resolve children’s doubts effectively, which shows a correlation significant (p = 0.467). Finally, the relationship between the degree of mastery of teachers in learning management platforms and their participation in forming learning communities was analyzed. A significant correlation (phi = 0.321) was found between the degree of mastery of teachers in these platforms and their participation in the formation of learning communities, with 28.24% of teachers having sufficient mastery and 20.61% of those with a moderate domain. These findings highlight the importance of parent-teacher collaboration in fostering a culture of learning in school and improving student academic achievement. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.
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Virtual environment application that complements the treatment of dyslexia (VEATD) in children
(2020)
Buele, Jorge
;
López, V.M.
;
Varela Aldas, José
;
Soria, A.
;
Palacios-Navarro, G.
The educational disorders that children present at an early age can cause them to not fully develop throughout their lives. In this research work a 3D virtual system that allows the child who has been diagnosed with dyslexia to complement the exercises performed in a conventional therapy is described. To achieve this an application was developed, the app consists of two games (each with three levels of difficulty), and that are part of the rehabilitation program. In each of these games virtual objects are combined with auditory messages to provide the user with an immersive experience, and to train more than one sense at a time. In the first game task, the activity asks the children to correctly locate the syllables that compose a word and for the second activity the children will listen to a word, after the games asks the children to select the correct word. This tool has been tested by a group of children (eight), with ages ranging from 8 to 12 years old, whose development can be supervised at home by their parents, since it is an intuitive and easy to use interface. The results obtained are stored in a database and in this way the medical specialist can monitor the progress of the child throughout his treatment. For the validation of this proposal the SUS usability test was used. © Springer Nature Switzerland AG 2020.
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Non-formal Virtual Training Strategies to Promote Entrepreneurship
(2025)
Mónica Naranjo-Costales
;
Núñez Hernández, Corina
;
Buele, Jorge
In the current context, entrepreneurship requires extensive knowledge for proper development. In Latin America, the lack of expertise in areas such as marketing and financial management leads to a high rate of business failure. This study addresses this issue by implementing a virtual learning environment called Emprende Virtual, designed to promote sustainable entrepreneurship through masterclasses and practical activities. The methodology used was a quantitative approach with an experimental design. A total of 59 participants were divided into two groups: an experimental group that received training through the digital resource of the virtual environment and a control group that received no intervention. Pre- and post-test surveys were conducted to measure the impact of the virtual learning environment on the participants’ entrepreneurial attitude, knowledge and skills. The results showed a significant improvement in the experimental group compared to the control group, especially in areas such as educational technology, innovation and entrepreneurship, and business management. This demonstrates that the strategy not only facilitates access to education but also contributes to the development of essential skills for business success, promoting sustainability and economic growth. Despite limitations such as the lack of geographical representativeness and variability in prior experience, the VLE proves to be an effective tool for developing entrepreneurs in the region.
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Support vector machine as tool for classifying coffee beverages
(2020)
Varela Aldas, José
;
Fuentes, E.M.
;
Buele, Jorge
;
Meló, R.G.
;
Barat, J.M.
Classifiers are tools widely used nowadays to process data and obtain prediction models that are trained through supervised learning techniques; there is a wide variety of sensors that acquire the data to be processed, such as the voltammetric electronic tongue, as a device employed to analyze food compounds. This paper presents a normal and decaffeinated coffee beverage classifier using a Support Vector Machine with a linear separation function, detailing the classification function and the model optimization method; to train the model, the data measured by 4 electrodes of a voltammetric tongue that is excited by a predetermined sequence of positive pulses is used. In addition, the results graphically show the measurements obtained, the support vectors and the evaluation data, the values of the classifier parameters are also presented. Finally, the conclusions establish an acceptable error in the classification of coffee drinks according to caffeine presence at the sample analyzed. © Springer Nature Switzerland AG 2020.
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An assessment of a ROS class using an educational mobile robot
(2024)
Varela Aldas, José
;
Junta, Christian
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Buele, Jorge
;
Guillermo Palacios-Navarro
The Robot Operating System (ROS) is a middleware that standardizes robot programming, both in simulation and with real equipment. Despite this open-source tool being available for several years, there's still a need to enhance its utilization in robotics education across all educational levels. In this study, a ROS class is assessed among university students using a commercial educational robot. The primary objective is to measure academic emotions in learning and student performance to determine the impact of the class using the open-access tool from a GitHub repository (https://github.com/joseVarelaAldas/ROS-Crowbot). This tool is based on the rosserial package, compatible with the ESP32 board. For class, CrowBot robots connected to the local wireless network via WiFi are used. TThe participants in this study were eight students from an electronics degree program at a higher education institution, who had no prior experience with ROS and received practical training using the educational mobile robot. For data collection on class performance, three parameters are assessed: execution time, functionality, and motivation, and to measure academic emotions, a validated self-report instrument is used. The results show an overall performance of 82.1%, and in the self-report on academic emotions, a high score in enjoyment (95%) and the lowest score in boredom (24.1 %) were obtained. In conclusion, the repository provides an interesting, practical, and accessible tool for an introduction into the world of robotics using ROS.
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Prototype of a Low Cost Turbine for the Generation of Clean Energy in the Ecuadorian Amazon
(2020)
Guáitara B.
;
Buele, Jorge
;
Salazar F.W.
;
Varela Aldas, José
Access to electricity supply in remote areas is limited, despite having wealth of other natural resources such as water. This document presents the design and construction of a scale electric generation system, taking advantage of the hydraulic energy produced by a constant flow of water flow. For this, the turbine design is described, which is based on the principles of Francis and Kaplan. In addition, the structural design made in CAD/CAM software and the actual implementation of the system are shown. To determine the generated electric potential, the electromagnetic analysis is performed based on the Maxwell-Faraday equation and the respective calculations. The validation of this proposal is determined by conducting experimental tests with balanced, unbalanced, series and parallel coils and with their implementation in a home. © 2020, Springer Nature Switzerland AG.
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Telemetry and Video Surveillance System in a UAV for the Control and Monitoring of Long-Distance Missions
(2020)
Buele, Jorge
;
Yánez-Arcos E.
;
Moscoso M.E.
;
Huilca J.S.
;
Jordán E.P.
Unmanned aerial vehicles (UAVs) are multidisciplinary technological tools, which are used in the military area for surveillance, reconnaissance and intelligence tasks in conflict zones. Due to its versatility and performance, this manuscript describes the implementation of a telemetry and video surveillance system to develop long-range missions in a UAV prototype. Communications subsystems and a ground station are integrated, with which an unmanned aerial system (UAS) is formed, carrying out the necessary calibrations and configurations. After a set of tests and the necessary adjustments, a long-distance mission is carried out and its energy consumption, height reached and trajectory tracking are analyzed. In addition, the video signal level obtained and the percentage of telemetry signal in each of the tests are established, which managed to be 90% with a distance greater than 4 km. They have good benefits, with a low economic investment, representing an interesting proposal for developing countries with a limited budget for their improvement. © 2020, Springer Nature Switzerland AG.
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