Intelligence and Big Data: Transforming Higher Education in Latin America
DOI:
https://doi.org/10.70577/xf92ng40Keywords:
Learning, Artificial Intelligence, Big Data, Higher Education, Employability.Abstract
This study analyzed the impact of Artificial Intelligence (AI) and Big Data on the transformation of higher education in Latin America, identifying opportunities, challenges, and best practices. AI was found to positively influence student academic performance, operational efficiency, and graduate employability, with significant coefficients. Excellent technological infrastructure is crucial to maximize these benefits. However, the results revealed an unexpected negative impact of AI and data volume on learning personalization, suggesting that mere data accumulation or current personalization strategies may be ineffective. The statistical robustness of the findings was confirmed by high adjusted R-squared and significant P-values. In conclusion, AI is a driver of optimization and improvement on several educational fronts, but its implementation in personalization and Big Data management requires a more strategic and refined approach. For effective transformation, institutions must focus on a robust infrastructure, adapt AI to real pedagogical needs, and prioritize data quality over quantity.
References
[1] Salas-Pilco, S. Z., & Yang, Y. (2022). Artificial intelligence applications in Latin American higher education: A systematic review. International Journal of Educational Technology in Higher Education, 19(1), 21. https://doi.org/10.1186/s41239-022-00326-w
[2] Özsezer, G., & Mermer, G. (2022). Using artificial intelligence in the COVID-19 Pandemic: A systematic review. Acta Medica Iranica, 387-397. http://dx.doi.org/10.18502/acta.v60i7.10208
[3] Tian, Y., Zhu, W., Zhang, X., & Jin, Y. (2023). A practical tutorial on solving optimization problems via PlatEMO. Neurocomputing, 518, 190-205. https://doi.org/10.1016/j.neucom.2022.10.075
[4] Kamalov, F., Santandreu Calonge, D., & Gurrib, I. (2023). New era of artificial intelligence in education: Towards a sustainable multifaceted revolution. Sustainability, 15(16), 12451. https://doi.org/10.3390/su151612451
[5] Cruz Zuniga, M., Santrac, N., Kwiatkowski, A., & Abood, B. (2024). What do college students think about artificial intelligence? We ask them. Journal of Integrated Global STEM, 1(1), 33–40. https://doi.org/10.1515/jigs-2024-0005
[6] Zhai, X., Chu, X., Chai, C. S., Jong, M. S. Y., Istenic, A., Spector, M., ... & Li, Y. (2021). A Review of Artificial Intelligence (AI) in Education from 2010 to 2020. Complexity, 2021(1), 8812542. http://dx.doi.org/10.1155/2021/8812542
[7] Barakina, E. Y., Popova, A. V., Gorokhova, S. S., & Voskovskaya, A. S. (2021). Digital Technologies and Artificial Intelligence Technologies in Education. European Journal of Contemporary Education, 10(2), 285-296. https://eric.ed.gov/?id=EJ1311498
[8] Cerdá Suárez, L. M., Núñez-Valdés, K., & Quirós y Alpera, S. (2021). A systemic perspective for understanding digital transformation in higher education: Overview and subregional context in Latin America as evidence. Sustainability, 13(23), 12956. https://doi.org/10.3390/su132312956
[9] Rodríguez-Alegre, L. R., Calderón-De-Los-Ríos, H., Hurtado-Zamora, M. M., & Ocaña-Rodríguez, Á. W. (2023). Inteligencia artificial en la gestión organizacional: Impacto y realidad latinoamericana. Revista Arbitrada Interdisciplinaria Koinonía, 8, 226-241. http://dx.doi.org/10.35381/r.k.v8i1.2782
[10] De La Torre, A., & Baldeon-Calisto, M. (2024). Generative artificial intelligence in latin american higher education: A systematic literature review. 2024 12th International Symposium on Digital Forensics and Security (ISDFS), 1–7. https://doi.org/10.1109/ISDFS60797.2024.10527283
[11] D’Alva, O. A., & Paraná, E. (2024). Official statistics and big data in Latin America: Data enclosures and counter-movements. Big Data & Society, 11(1), 20539517241229696. http://dx.doi.org/10.1177/20539517241229696
[12] Cornejo, J., Barrera, S., Ruiz, C. H., Gutiérrez, F., Casasnovas, M. O., Kot, L., ... & L'huillier, E. A. (2023). Industrial, collaborative and mo-bile robotics in Latin America: Review of mech-atronic technologies for advanced automa-tion. Emerging Science Journal, 7(4), 1430-1458. http://dx.doi.org/10.28991/ESJ-2023-07-04-025
[13] Lin, C. C., Huang, A. Y., & Lu, O. H. (2023). Artificial intelligence in intelligent tutoring systems toward sustainable education: a systematic review. Smart Learning Environments, 10(1), 41. http://dx.doi.org/10.1186/s40561-023-00260-y
[14] Ouyang, F., Dinh, T. A., & Xu, W. (2023). A systematic review of AI-driven educational assessment in STEM education. Journal for STEM Education Research, 6(3), 408-426. http://dx.doi.org/10.1007/s41979-023-00112-x
[15] Bu, K., Liu, Y., & Ju, X. (2024). Efficient utilization of pre-trained models: A review of sentiment analysis via prompt learning. Knowledge-Based Systems, 283, 111148. https://dl.acm.org/doi/abs/10.1016/j.knosys.2023.111148
[16] Flores Jaramillo, J. D., & Nuñez Olivera, N. R. (2024). Aplicación de inteligencia artificial en la educación de américa latina: Tendencias, beneficios y desafíos. Revista Veritas de Difusão Científica, 5(1), 01–21. https://doi.org/10.61616/rvdc.v5i1.52
[17] Nasim, S. F., Ali, M. R., & Kulsoom, U. (2022). Artificial intelligence incidents & ethics a narrative review. International Journal of Technology Innovation and Management (IJTIM), 2(2), 52-64. http://dx.doi.org/10.54489/ijtim.v2i2.80
[18] Huang, C., Zhang, Z., Mao, B., & Yao, X. (2022). An overview of artificial intelligence ethics. IEEE Transactions on Artificial Intelligence, 4(4), 799-819. http://dx.doi.org/10.1109/TAI.2022.3194503
[19] Kasun, G. S., Liao, Y.-C., Margulieux, L. E., & Woodall, M. (2024). Unexpected outcomes from an AI education course among education faculty: Toward making AI accessible with marginalized youth in urban Mexico. Frontiers in Education, 9, 1368604. https://doi.org/10.3389/feduc.2024.1368604
[20] Palle, R. R., & Kathala, K. C. R. (2024). AI in Data Privacy and Ethics. In Privacy in the Age of Innovation: AI Solutions for Information Security (pp. 111-118). Berkeley, CA: Apress. http://dx.doi.org/10.1007/979-8-8688-0461-8_9
[21] Yang, E., & Beil, C. (2024). Ensuring data privacy in AI/ML implementation. New Directions for Higher Education, 2024(207), 63-78. https://doi.org/10.1002/he.20509
[22] Lee, C. S., Cheang, P. Y. S., & Moslehpour, M. (2022). Predictive analytics in business analytics: decision tree. Advances in Decision Sciences, 26(1), 1-29. http://dx.doi.org/10.47654/v26y2022i1p1-30
[23] Shafiq, D. A., Marjani, M., Habeeb, R. A. A., & Asirvatham, D. (2022). Student retention using educational data mining and predictive analytics: a systematic literature review. IEEE Access, 10, 72480-72503. http://dx.doi.org/10.1109/ACCESS.2022.3188767
[24] Teichert, L., Anderson, J., Anderson, A., Hare, J., & McTavish, M. (2021). Access and use of digital technologies in early childhood: A review of mixed messages in popular media. Language and Literacy, 23(3), 106-128. http://dx.doi.org/10.20360/langandlit29546
[25] Guerrero-Quiñonez, A. J., Bedoya-Flores, M. C., Mosquera-Quiñonez, E. F., Mesías-Simisterra, Á. E., & Bautista-Sánchez, J. V. (2023). Artificial Intelligence and its scope in Latin American higher education. Ibero-American Journal of Education & Society Research, 3(1), 264–271. https://doi.org/10.56183/iberoeds.v3i1.627
[26] Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: The state of the field. International Journal of Educational Technology in Higher Education, 20(1), 22. https://doi.org/10.1186/s41239-023-00392-8
[27] Montecé Mosquera, F. W., Esteves Fajardo, Z. I., Pizarro Vargas, V. J., Guamán Hernández, V. A., Alarcón Salvatierra, P. A., Chiriboga Posligua, M. F., Jurado Ronquillo, M. C., Núñez Núñez, M. A., Wila Ayovi, A. W., & Segura Villamar, F. I. (2024). La IA. Un entorno educativo en América Latina (1st ed.). Mawil Publicaciones de Ecuador, 2024. https://doi.org/10.26820/978-9942-654-14-4
[28] Savari, G. F., Sathik, M. J., Raman, L. A., El-Shahat, A., Hasanien, H. M., Almakhles, D., ... & Omar, A. I. (2023). Assessment of charging technologies, infrastructure and charging station recommendation schemes of electric vehicles: A review. Ain Shams Engineering Journal, 14(4), 101938. https://doi.org/10.1016/j.asej.2022.101938
[29] Bin Eid, A., Almutairi, M., Alzahrani, A., Alomair, F., Albinhamad, A., Albarrak, Y., ... & Bin Abdulrahman, K. (2021). Examining learning styles with gender comparison among medical students of a Saudi University. Advances in Medical Education and Practice, 309-318. http://dx.doi.org/10.2147/AMEP.S295058
[30] Machado, I. A., Costa, C., & Santos, M. Y. (2022). Data mesh: concepts and principles of a paradigm shift in data architectures. Procedia Computer Science, 196, 263-271. https://doi.org/10.1016/j.procs.2021.12.013
[31] Reda Taha, M., Ayyub, B. M., Soga, K., Daghash, S., Heras Murcia, D., Moreu, F., & Soliman, E. (2021). Emerging technologies for resilient infrastructure: Conspectus and roadmap. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 7(2), 03121002. https://www.researchgate.net/publication/350121828_Emerging_Technologies_for_Resilient_Infrastructure_Conspectus_and_Roadmap
[32] Vrontis, D., Christofi, M., Pereira, V., Tarba, S., Makrides, A., & Trichina, E. (2023). Artificial intelligence, robotics, advanced technologies and human resource management: a systematic review. Artificial intelligence and international HRM, 172-201. http://dx.doi.org/10.1080/09585192.2020.1871398
[33] Lim, H. W., & Kim, S. J. (2021). A study on ways to make employment improve through Big Data analysis of university information public. International Journal of Advanced Culture Technology, 9(3), 174-180. https://doi.org/10.17703/IJACT.2021.9.3.174
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