Integrative Model of Theory and Practice for Engineering and Management Education in Latin America
DOI:
https://doi.org/10.14571/brajets.v18.n1.211-231Abstract
This project targets the alignment of academic theory with practical industry application in Latin American engineering and management education. It introduces a model that integrates research with teaching, encouraging students to actively participate in and shape their own learning experiences. Utilizing a 'Push and Pull' strategy, the project intertwines structured academic goals with demand-driven learning, aligning education with industrial needs. The outcome is a student-centered approach where learners engage as active participants, bridging the gap between theory and practice.
The effectiveness of this method is discussed in terms of its potential to transform passive learning into a dynamic, collaborative process. It suggests that early engagement in research can enhance students' educational outcomes. The project underlines the importance of industry-relevant education and positions it as a catalyst for student innovation and practical problem-solving. It implies that active student involvement in research is necessary for the modernization of educational practices.
In conclusion, the project advocates for an industry-focused educational approach as essential for improving engineering and management training in Latin America. This model promotes a deep integration of theoretical knowledge and practical skills, proposing a new standard for educational institutions aiming to prepare students for professional success.
References
Acuña Acuña, EG (2023). Aplicación de Minería de Datos e Internet de las Cosas (IoT) para productos Biomédicos. REVISIÓN TECNO. Revista Internacional de Tecnología, Ciencia y Sociedad, 13 (1), 145–169. https://doi.org/10.37467/revtechno.v12.3444
Acuña Acuña, E. G. (2022). Analysis of the Impact of TIC on Higher Education in Latin America. EDUTECH REVIEW. International Education Technologies Review / Revista Internacional De Tecnologías Educativas, 9(1), 15–29. https://doi.org/10.37467/gkarevedutech.v9.3277
Banco Interamericano de Desarrollo (BID). (2019). Empresas sostenibles: ¿cómo se benefician y qué pueden hacer? Retrieved from https://publications.iadb.org/publications/spanish/document/Empresas-sostenibles-Como-se-benefician-y-que-pueden-hacer.pdf
Calvo-Lorenzo, I., & Uriarte-Llano, I. (2024). Generación masiva de historias clínicas sintéticas con ChatGPT: un ejemplo en fractura de cadera. Medicina Clínica. https://doi.org/10.1016/j.medcli.2023.11.027
Dong, Y. (2024). Application of user preference mining algorithms based on data mining and social behavior in brand building. Data Science and Management. https://doi.org/10.1016/j.dsm.2024.03.007
Feng, G., & Fan, M. (2024). Research on learning behavior patterns from the perspective of educational data mining: Evaluation, prediction, and visualization. Expert Systems with Applications, 237(Part B), 121555. https://doi.org/10.1016/j.eswa.2023.121555
Gu, H., Qin, J., Wen, J., Lin, Y., Jia, X., Wang, W., & Yin, H. (2024). Unveiling the structural properties and induced resistance activity in rice of Chitin/Chitosan-Glucan Complex of Rhizoctonia solani AG1 IA inner cell wall. Carbohydrate Polymers, 337, 122149. https://doi.org/10.1016/j.carbpol.2024.122149.
Guo, H., Song, Y., Chu, Y., He, Y., Gao, W., & Guan, X. (2024). Data-mining framework for in-depth quantitative study of influences on low-wind-velocity area from morphological parameters of cuboid-form buildings. Heliyon, 10(7), e29137. https://doi.org/10.1016/j.heliyon.2024.e29137
Hellali, R., Dagdia, Z. C., Ktaish, A., Zeitouni, K., & Annane, D. (2024). Corticosteroid sensitivity detection in sepsis patients using a personalized data mining approach: A clinical investigation. Computer Methods and Programs in Biomedicine, 245, 108017. https://doi.org/10.1016/j.cmpb.2024.108017
Iborra, E., Herranz-Pinilla, C., & López-Costea, M. (2024). Robotic Assisted Aortic Banding for Type Ia Endoleak. European Journal of Vascular and Endovascular Surgery. https://doi.org/10.1016/j.ejvs.2024.03.033
Jaber, A., & Csonka, B. (2023). Investigating the temporal differences among bike-sharing users through comparative analysis based on count, time series, and data mining models. Alexandria Engineering Journal, 77, 1-13. https://doi.org/10.1016/j.aej.2023.06.087
Kitchenham, B., Brereton, O. P., Budgen, D., Turner, M., Bailey, J., & Linkman, S. (2009). Systematic literature reviews in software engineering—a systematic literature review. Information and Software Technology, 51(1), 7-15.
Lee, J. Y., Choi, J. W., Choi, J.-H., & Lee, B.-H. (2023). Text-mining analysis using national R&D project data of South Korea to investigate innovation in graphene environment technology. International Journal of Innovation Studies, 7(1), 87-99. https://doi.org/10.1016/j.ijis.2022.09.005
Lee, M., Jo, H., & Park, H. (2020). Sustainable innovation practices in South Korean firms: A multiple-case study analysis. Sustainability, 12(7), 2738.
Leslie, M. (2024). Artificial Intelligence, Like Cryptocurrency, Eats Energy—Lots of It. Engineering, 32, 7-9. https://doi.org/10.1016/j.eng.2023.11.006.
Lu, F., Jin, Z., & Zhang, X. (2023). An analysis of data mining techniques in software engineering database design. Procedia Computer Science, 228, 47-56. https://doi.org/10.1016/j.procs.2023.11.007
Maldonado-Guzmán, G., & Aguilar-Barajas, I. (2018). Corporate Social Responsibility as a Tool for Sustainable Development in Latin America. Journal of Cleaner Production, 196, 1429-1440.
Orozco-Hernández, A. J., Cortés-García, F. J., & San-JoséRevuelta, L. M. (2021). Implementation of Circular Economy Strategies in Latin America: A Literature
Ouadah, O., Saidi, F., Miloudi, M. E. A., Ziani, O., Mahmoudi, A., & Nasr, S. (2021). DFT investigation analyzed with data mining technique of rare-earth dihydrides REH2 for hydrogen storage. International Journal of Hydrogen Energy, 46(65), 32962-32973. https://doi.org/10.1016/j.ijhydene.2021.07.137
Pepper-Loza, J. (2019). [Title of the referenced article or book chapter, if available].
Philippi, D., Maccari, E., Da Costa, P., & Dos Santos, J. (2023). Capital humano científico y técnico en la transferencia tecnológica universidad-empresa: el caso de una innovación radical. Revista Gestão & Tecnologia, 23(4), 508–527. https://doi.org/10.20397/2177-6652/2023.v23i4.2141
Salgado, F. Ángel Álvarez, Chan, CAD, Acuña, EGA, Cruz, LMH, Álvarez, DCM, Chiquini, CM de JL, Kú, RG, & Arjona, PSH (2024). Prototipo sustentable con implementación de IoT para monitoreo remoto de apiarios de Apis mellifera en regiones mayas de Campeche, México. Revista Brasileña de Tecnología, 7 (2), e69054. https://doi.org/10.38152/bjtv7n2-001
Shankar, D. D., Azhakath, A. S., Khalil, N., Sajeev, J., Mahalakshmi, T., & Sheeba, K. (2024). Data mining for cyber biosecurity risk management – A comprehensive review. Computers & Security, 137, 103627. https://doi.org/10.1016/j.cose.2023.103627
Szczesniewski, J. J., Ramos Alba, A., Rodríguez Castro, P. M., Lorenzo Gómez, M. F., Sainz González, J., & Llanes González, L. (2024). Quality of information about urologic pathology in English and Spanish from ChatGPT, BARD, and Copilot. Actas Urológicas Españolas (English Edition). https://doi.org/10.1016/j.acuroe.2024.02.009.
Vidal-Alaball, J., Panadés Zafra, R., Escalé-Besa, A., & Martinez-Millana, A. (2024). The artificial intelligence revolution in primary care: Challenges, dilemmas, and opportunities. Atención Primaria, 56(2), 102820. https://doi.org/10.1016/j.aprim.2023.102820.
Yao, K. (2024). Application of sensor-based speech data mining in E-commerce operations data analysis. Measurement: Sensors, 33, 101118. https://doi.org/10.1016/j.measen.2024.101118
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Edwin Gerardo Acuña Acuña
This work is licensed under a Creative Commons Attribution 4.0 International License.
The BRAJETS follows the policy for Open Access Journals, provides immediate and free access to its content, following the principle that making scientific knowledge freely available to the public supports a greater global exchange of knowledge and provides more international democratization of knowledge. Therefore, no fees apply, whether for submission, evaluation, publication, viewing or downloading of articles. In this sense, the authors who publish in this journal agree with the following terms: A) The authors retain the copyright and grant the journal the right to first publication, with the work simultaneously licensed under the Creative Commons Attribution License (CC BY), allowing the sharing of the work with recognition of the authorship of the work and initial publication in this journal. B) Authors are authorized to distribute non-exclusively the version of the work published in this journal (eg, publish in the institutional and non-institutional repository, as well as a book chapter), with acknowledgment of authorship and initial publication in this journal. C) Authors are encouraged to publish and distribute their work online (eg, online repositories or on their personal page), as well as to increase the impact and citation of the published work.