Automated Academic Reporting System that Optimizes Educational Management
DOI:
https://doi.org/10.5281/zenodo.19689946Keywords:
Educational Management, Automated System, User Experience, Cluster Analysis, Artificial IntelligenceAbstract
In the context of digital transformation, vocational education institutions face gaps in academic management related to scheduling, learner monitoring, and the generation of reports for decision-making. This article introduces the Automated Academic Reporting System (SARA), whose objective is to describe its technical development and implementation of artificial intelligence, as well as to assess its contribution to academic management through bibliometric analysis and instructor perceptions. The research is applied in nature, with a mixed-methods approach and a descriptive–exploratory scope. SARA’s architectural framework is based on the Model–View–Controller (MVC) pattern and a NoSQL database, ensuring modular scalability and the efficient integration of more than 140,000 heterogeneous records (Excel, SOFIA Plus, JSON). For the bibliometric analysis, the Scopus database was consulted, identifying 4,922 documents processed with VOSviewer® using co-authorship analysis. In addition, semistructured interviews were conducted with seven instructors, whose responses were analyzed using natural language processing techniques to systematize perceptions. The findings highlight in the literature the relevance of frameworks for interoperability, data governance, and digital sustainability, while also revealing a positive perception of SARA regarding ease of use, reduction of administrative workload, and utility in decision-making. In conclusion, SARA is presented as a scalable and replicable tool that strengthens academic management and generates pedagogical and organizational implications from an interdisciplinary perspective.
References
Aghaei, S., Shahbazi, Y., Pirbabaei, M. y Beyti, H. (2023). A hybrid SEM-neural network method for modeling the academic satisfaction factors of architecture students. Computers and Education: Artificial Intelligence, 4, 100122. https://doi.org/10.1016/j.caeai.2023.100122
Arias Ortiz, E., Eusebio, J., Pérez Alfaro, M., Vásquez, M. y Zoido, P. (2021). Los Sistemas de Información y Gestión Educativa (SIGED) de América Latina y el Caribe: la ruta hacia la transformación digital de la gestión educativa. Inter-American Development Bank. https://doi.org/10.18235/0003345
Brauer, M., Roth, G. A., Aravkin, A. Y., Zheng, P., Abate, K. H., Abate, Y. H., Abbafati, C., et al. (2024). Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. The Lancet, 403(10440), 2162-2203. https://doi.org/10.1016/S0140-6736(24)00933-4
Briceño Toledo, M., Correa Castillo, S., Valdés Montecinos, M. y Hadweh Briceño, M. (2020). Modelo de gestión educativa para programas en modalidad virtual de aprendizaje. Revista de Ciencias Sociales, 26(2), 286-298. https://doi.org/10.31876/rcs.v26i2.32442
Camones Gonzales, F. C., Sihuay Fernandez, M. T., Nolberto Sifuentes, V. A. y Padilla Caballero, J. E. A. (2024). Minería de datos: Un enfoque perspectivo desde el contexto educativo. Revista Tribunal, 4(9), 138-160. https://doi.org/10.59659/revistatribunal.v4i9.70
Campos-Malpartida, J., Ordoñez-Ramos, E. y Huaylla-Quispe, A. (2024). Análisis del Sentimiento con NLP en tutoría académica: la vocación como factor de mejora en el rendimiento académico. C&T Riqchary Revista de Investigación en Ciencia y Tecnología, 6(2), 7-13. https://doi.org/10.57166//riqchary.v6.n2.2024.123
Chen, C., Zheng, F., Cui, J., Cao, Y., Liu, G., Wu, J. y Zhou, J. (2024). Survey and open problems in privacy-preserving knowledge graph: merging, query, representation, completion, and applications. International Journal of Machine Learning and Cybernetics, 15(8), 3513-3532. https://doi.org/10.1007/s13042-024-02106-6
European Commission. (2020). Digital Education Action Plan 2021–2027. Publications Office of the European Union. https://education.ec.europa.eu/focus-topics/digital-education/actions
Feigin, V. L., Abate, M. D., Abate, Y. H., Abd ElHafeez, S., Abd-Allah, F., Abdelalim, A., Abdelkader, A., et al. (2024). Global, regional, and national burden of stroke and its risk factors, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. The Lancet Neurology, 23(10), 973-1003. https://doi.org/10.1016/S1474-4422(24)00369-7
Ferrari, A. J., Santomauro, D. F., Aali, A., Abate, Y. H., Abbafati, C., Abbastabar, H., Abd ElHafeez, S., et al. (2024). Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. The Lancet, 403(10440), 2133-2161. https://doi.org/10.1016/S0140-6736(24)00757-8
García-Peñalvo, F. J. y Corell, A. (2020). La COVID-19: ¿enzima de la transformación digital de la docencia o reflejo de una crisis metodológica y competencial en la educación superior? Campus Virtuales, 9(2), 83-98. https://hdl.handle.net/10366/144140
Graue, E., Martuscelli, J. y Martínez Leyva, C. (2019). Educación superior, el futuro del trabajo y la automatización. Universidades, (81), 65-76. https://doi.org/10.36888/udual.universidades.2019.81.38
Haleem, A., Javaid, M., Qadri, M. A. y Suman, R. (2022). Understanding the role of digital technologies in education: A review. Sustainable Operations and Computers, 3, 275-285. https://doi.org/10.1016/j.susoc.2022.05.004
Holmes, W., Bialik, M. y Fadel, C. (2019). Artificial Intelligence in Education: Promises and Implications for Teaching and Learning (2nd ed.). Center for Curriculum Redesign. https://www.researchgate.net/publication/332180327
Javaid, M., Haleem, A., Singh, R. P. y Sinha, A. K. (2024). Digital economy to improve the culture of industry 4.0: A study on features, implementation and challenges. Green Technologies and Sustainability, 2(2), 100083. https://doi.org/10.1016/j.grets.2024.100083
Javaid, M., Haleem, A., Singh, R. P. y Suman, R. (2022). Enabling flexible manufacturing system (FMS) through the applications of industry 4.0 technologies. Internet of Things and Cyber-Physical Systems, 2, 49-62. https://doi.org/10.1016/j.iotcps.2022.05.005
Javaid, M., Haleem, A., Singh, R. P. y Suman, R. (2023). Towards insighting cybersecurity for healthcare domains: A comprehensive review of recent practices and trends. Cyber Security and Applications, 1, 100016. https://doi.org/10.1016/j.csa.2023.100016
Jiménez Riofrío, S. M. (2022). Gestión educativa y liderazgo educativo; las tic en la mejora de la competitividad. Neutrosophic Computing and Machine Learning, 19, 66-74. https://fs.unm.edu/NCML2/index.php/112/article/view/184
Kung, C. A. L. L., Noriega, E. R., Huarmiyuri, A. C. y Romero, N. J. G. (2024). Transformación Educativa en la Era Digital: Integración y Futuro de las TIC en el Aprendizaje (Vol. Editorial Internacional ALEMA). https://editorialalema.org/libros/index.php/alema/article/view/33
Liu, F., Li, Z., Wang, B., Wu, J., Yang, J., Huang, J., Zhang, Y., et al. (2022). eRiskCom: an e-commerce risky community detection platform. The VLDB Journal, 31(5), 1085-1101. https://doi.org/10.1007/s00778-021-00723-z
Ma, X., Wu, J., Xue, S., Yang, J., Zhou, C., Sheng, Q. Z., Xiong, H., et al. (2021). A Comprehensive Survey on Graph Anomaly Detection With Deep Learning. IEEE Transactions on Knowledge and Data Engineering, 35(12), 12012-12038. https://doi.org/10.1109/TKDE.2021.3118815
Mendieta Lucas, L. M., Garzón Moreno, G. J., Enríquez Delgado, R. A. y Martínez Ángulo, M. A. (2025). Evolución e innovación digital en la educación superior como impulso para el fortalecimiento institucional: aplicación de inteligencia artificial en la gestión académica y administrativa para una toma de decisiones más eficiente y sostenible. Reincisol, 4(7), 2469-2492. https://doi.org/10.59282/reincisol.V4(7)2469-2492
Mensah, G. A., Fuster, V., Murray, C. J. L., Roth, G. A., Mensah, G. A., Abate, Y. H., Abbasian, M., et al. (2023). Global Burden of Cardiovascular Diseases and Risks, 1990-2022. Journal of the American College of Cardiology, 82(25), 2350-2473. https://doi.org/10.1016/j.jacc.2023.11.007
Mienye, I. D. y Sun, Y. (2022). A Survey of Ensemble Learning: Concepts, Algorithms, Applications, and Prospects. IEEE Access, 10, 99129-99149. https://doi.org/10.1109/ACCESS.2022.3207287
Mienye, I. D. y Sun, Y. (2023). A Deep Learning Ensemble With Data Resampling for Credit Card Fraud Detection. IEEE Access, 11, 30628-30638. https://doi.org/10.1109/ACCESS.2023.3262020
Morandín-Ahuerma, F. (2022). What is Artificial Intelligence? International Journal of Research Publication and Reviews, 3(12), 1947-1951. https://doi.org/10.55248/gengpi.2022.31261
Mustafa, F., Almaududi Ausat, A. M. y Kraugusteeliana, K. (2024). The Role of Business Information Systems in Strategic Decision-Making: Implications for Innovation and Market Adaptation. Jurnal Minfo Polgan, 13(2), 1468-1475. https://doi.org/10.33395/jmp.v13i2.14099
Naghavi, M., Ong, K. L., Aali, A., Ababneh, H. S., Abate, Y. H., Abbafati, C., Abbasgholizadeh, R., et al. (2024). Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. The Lancet, 403(10440), 2100-2132. https://doi.org/10.1016/S0140-6736(24)00367-2
Nelson Salgado, R. (2024). Automatización de tareas en sistemas de información: implementación de sistemas inteligentes para la automatización de tareas repetitivas y procesos rutinarios en entornos de sistemas de información. Revista Científica FIPCAEC, 9(1), 104-115. https://doi.org/10.23857/fipcaec.v9i1.935
Ng, M., Gakidou, E., Lo, J., Abate, Y. H., Abbafati, C., Abbas, N., Abbasian, M., et al. (2025). Global, regional, and national prevalence of adult overweight and obesity, 1990–2021, with forecasts to 2050: a forecasting study for the Global Burden of Disease Study 2021. The Lancet, 405(10481), 813-838. https://doi.org/10.1016/S0140-6736(25)00355-1
OECD. (2019). The OECD Learning Compass 2030. OECD Publishing. https://www.oecd.org/en/data/tools/oecd-learning compass-2030.html
OECD. (2023). OECD Digital Education Outlook 2023: Towards an Effective Digital Education Ecosystem. OECD Publishing. https://doi.org/10.1787/c74f03de-en
Park, S.-M. y Kim, Y.-G. (2022). A Metaverse: Taxonomy, Components, Applications, and Open Challenges. IEEE Access, 10, 4209-4251. https://doi.org/10.1109/ACCESS.2021.3140175
Quintero López, C., Gil Vera, V. D., Ángel Gómez, K., Valencia Ochoa, J., Restrepo Camargo, Y., Rivera Montoya, Y. y Herrera Vélez, A. (2024). Análisis de sentimientos sobre la educación remota en tiempos de pandemia: Latinoamérica. Revista Palobra “palabra que obra”, 24(1), 51-72. https://doi.org/10.32997/2346-2884-vol.24-num.1-2024-4145
Rivera Aguilera, L. R., Rivera Aguilera, J. C. y Ramos Fandiño, G. P. (2024). Elementos a considerar en el diseño de sistemas de información para la gestión documental en instituciones públicas en México. En B. Cabral Vargas y J. M. Castillo Fonseca (Eds.), Contexto y prospectiva del quehacer y desarrollo archivístico (pp. 231-254). Universidad Nacional Autónoma de México. Instituto de Investigaciones Bibliotecológicas y de la Información. https://ru.iibi.unam.mx/jspui/handle/IIBI_UNAM/1056
Romero, C. y Ventura, S. (2020). Educational data mining and learning analytics: An updated survey. WIREs Data Mining and Knowledge Discovery, 10(3), e1355. https://doi.org/10.1002/widm.1355
Sánchez Armas, M. y Delgado Bardales, J. M. (2020). Gestión Educativa en el desarrollo del aprendizaje en las Instituciones Educativas. Ciencia Latina Revista Científica Multidisciplinar, 4(2), 1819-1838. https://doi.org/10.37811/cl_rcm.v4i2.196
Santos, C., Pedro, N. y Mattar, J. (2021). Competencia digital de profesores de educación superior:: análisis de factores académicos e institucionales. Obra digital, (21), 69-92. https://doi.org/10.25029/od.2021.311.21
Sarker, I. H. (2022). AI-Based Modeling: Techniques, Applications and Research Issues Towards Automation, Intelligent and Smart Systems. SN Computer Science, 3(2), 158. https://doi.org/10.1007/s42979-022-01043-x
Sarker, I. H., Colman, A., Han, J. y Watters, P. (2021). Context-Aware Machine Learning and Mobile Data Analytics: Automated Rule-based Services with Intelligent Decision-Making. Springer. https://doi.org/10.1007/978-3-030-88530-4
Schumacher, A. E., Kyu, H. H., Aali, A., Abbafati, C., Abbas, J., Abbasgholizadeh, R., Abbasi, M. A., et al. (2024). Global age sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021. The Lancet, 403(10440), 1989-2056. https://doi.org/10.1016/S0140-6736(24)00476-8
Steinmetz, J. D., Seeher, K. M., Schiess, N., Nichols, E., Cao, B., Servili, C., Cavallera, V., et al. (2024). Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. The Lancet Neurology, 23(4), 344-381. https://doi.org/10.1016/S1474-4422(24)00038-3
Su, X., Xue, S., Liu, F., Wu, J., Yang, J., Zhou, C., Hu, W., et al. (2022). A Comprehensive Survey on Community Detection With Deep Learning. IEEE Transactions on Neural Networks and Learning Systems, 35(4), 4682-4702. https://doi.org/10.1109/TNNLS.2021.3137396
UNESCO. (2022). Reimaginar juntos nuestros futuros: un nuevo contrato social para la educación. UNESCO Publishing. https://unesdoc.unesco.org/ark:/48223/pf0000381560
Van Gelder, I. C., Rienstra, M., Bunting, K. V., Casado-Arroyo, R., Caso, V., Crijns, H. J. G. M., De Potter, T. J. R., et al. (2024). 2024 ESC Guidelines for the management of atrial fibrillation developed in collaboration with the European Association for Cardio Thoracic Surgery (EACTS): Developed by the task force for the management of atrial fibrillation of the European Society of Cardiology (ESC), with the special contribution of the European Heart Rhythm Association (EHRA) of the ESC. Endorsed by the European Stroke Organisation (ESO). European Heart Journal, 45(36), 3314-3414. https://doi.org/10.1093/eurheartj/ehae176
Wu, J., Lin, D., Chen, W., Zhang, L., Shen, X., Fu, D., Li, Y., et al. (2025). Research status and hotspots of oral frailty in older adults: a bibliometric analysis from 2013 to 2024. Frontiers in Oral Health, 6, 1533159. https://doi.org/10.3389/froh.2025.1533159
Wu, J., Wang, Y., Shen, Z. y Liu, L. (2023). Adaptive client and communication optimizations in Federated Learning. Information Systems, 116, 102226. https://doi.org/10.1016/j.is.2023.102226
Wu, J., Xu, Z., Huang, Q. y Cai, J. (2024). What motivates knowledge sharing? Evaluating the quality of answer contribution in online Q&A communities. Data and Information Management, 9(3), 100086. https://doi.org/10.1016/j.dim.2024.100086
Yu, Z., Wu, J., Song, X., Fu, W. y Zhai, C. (2022). The Quantitative Research on Behavioral Intention towards 5G Rich Communication Services among University Students. Systems, 10(5), 136. https://doi.org/10.3390/systems10050136
Zhou, S., Xu, H., Zheng, Z., Chen, J., Li, Z., Bu, J., Wu, J., et al. (2024). A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions. ACM Computing Surveys, 57(3), 1-38. https://doi.org/10.1145/3689036
Zhu, D., Yin, H., Xu, Y., Wu, J., Zhang, B., Cheng, Y., Yin, Z., et al. (2023). A Survey of Advanced Information Fusion System: from Model-Driven to Knowledge-Enabled. Data Science and Engineering, 8(2), 85-97. https://doi.org/10.1007/s41019-023-00209-8
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