English language learning model using machine learning algorithms

Main Article Content

Daniela Fernanda Guano Merino
Zoila Victoria Herrera Andrade
Carina Fernanda Vallejo Barreno

Abstract

Introduction. The article demonstrates why some types of ICT can be considered Artificial Intelligence systems, how their introduction in the educational process affects the cognitive changes of the student and what role the degree of trust plays in said systems. The study aims to determine how artificial intelligence (AI) influences a student using information and communication technologies (ICT) during English language classes in higher education. The article explains why some types of ICT can be considered AI systems, how their inclusion in the educational process influences a student's cognitive changes, and what role a student's degree of trust in such a system plays. The scientific novelty of the work lies in considering the influence of ICT on the cognitive abilities of a student learning a foreign language through the lens of AI. As a result, it was found that the closer the AI ​​capabilities in ICT are to human activities while working with a foreign language, the less the activation of cognitive performance in a student. Objective. To determine the characteristics of the influence of artificial intelligence (AI) on the student using information and communication technologies (ICT) in foreign language classes in higher education. Methodology. The study consists of considering the impact of ICT on the cognitive abilities of a student studying a foreign language through the prism of Artificial Intelligence. The possibilities of information and communication technologies are studied using digital intelligence in general and specifically, from the perspective of its suitability for teaching the English language. It is briefly reviewed, and some digital learning systems are differentiated as alternative resources for learning English. The work is based on the applicability of virtual linguistic interaction using in the information and education space: virtual teachers in the e-Learning environment, interactive agents (Chatbots) in the English learning process. Results. As a result, it has been established that the closer the possibilities of AI in ICT are to human activity when working with a foreign language, the lower the activation of cognitive activity by the student. Conclusion. Classical pedagogical technologies with the concomitant use of artificial intelligence allow the implementation of alternative learning models and make the transition from reproductive means of learning to innovative-reflexive ones.

Downloads

Download data is not yet available.

Article Details

How to Cite
Guano Merino, D. F., Herrera Andrade, Z. V., & Vallejo Barreno, C. F. (2023). English language learning model using machine learning algorithms. Explorador Digital, 7(1), 29-43. https://doi.org/10.33262/exploradordigital.v7i1.2451
Section
Artículos

References

Arana, C. (2021). Inteligencia artificial aplicada a la educación: logros, tendencias y perspectivas. INNOVA UNTREF. Revista Argentina de Ciencia y Tecnología. http://revistas.untref.edu.ar/index.php/innova/article/view/1107
Argimon Pallás, J. M., & Jiménez Villa, J. (2004). Estudios descriptivos. Métodos de Investigación Clínica y Epidemiológica, 90–100. https://doi.org/10.1016/B978-84-8174-709-6.50009-9
Badi, H. S., & Hussein, S. (2014). Hand posture and gesture recognition technology. Neural Computing and Applications, 25(3–4), 871–878. https://doi.org/10.1007/S00521-014-1574-4
Castro Villalobos, S., Casar Espino, L., García Martínez, A., Castro Villalobos, S., Casar Espino, L., & García Martínez, A. (2019). Reflexiones sobre la enseñanza inclusiva del inglés apoyada por tecnologías emergentes. Revista Cubana de Educación Superior, 38(1). http://scielo.sld.cu/scielo.php?script=sci_arttext&pid=S0257-43142019000100012&lng=es&nrm=iso&tlng=es
Díaz, J. P., Siles, I. S., Contreras, E. P., & Sánchez, A. (2022). Aplicación de técnicas de inteligencia artificial para reconocimiento facial en sistemas de seguridad en ambientes de intranet. Mare Ingenii, 4(1), 20–32. https://doi.org/10.52948/MARE.V4I1.682
Escudero Villanueva, F. M., De la Cruz, I. L., Funegra Orbegoso, R. J. M., & García Chirinos, A. A. (2022). Plan de negocio para el desarrollo de una empresa que brinde servicio educativo del idioma inglés basado en tecnología de realidad virtual, Inteligencia artificial y Machine Learning. Tesis de Maestría, ESAN BUSSINES. https://repositorio.esan.edu.pe///handle/20.500.12640/3104
García-Ruiz, M. A. (2002). Inteligencia artificial en la educación: aplicaciones y proyectos IHCLab-Low-Cost Hardware for visualizing VR and teaching HCI View project Design, development and testing of multisensory human-computer interfaces View project. https://www.researchgate.net/publication/354153360
Medina-Chicaiza, P., & Martínez-Ortega, A. G. (2020). Tecnologías en la inteligencia artificial para el Marketing: una revisión de la literatura. Pro Sciences: Revista de Producción, Ciencias e Investigación, 4(30), 36–47. https://doi.org/10.29018/ISSN.2588-1000VOL4ISS30.2020PP36-47
Mustafa, M. (2021). A study on Arabic sign language recognition for differently abled using advanced machine learning classifiers. Journal of Ambient Intelligence and Humanized Computing, 12(3), 4101–4115. https://doi.org/10.1007/S12652-020-01790-W
Nakjai, P., & Katanyukul, T. (2019). Hand Sign Recognition for Thai Finger Spelling: An application of Convolution Neural Network. Journal of Signal Processing Systems, 91(2), 131–146. https://doi.org/10.1007/S11265-018-1375-6
Naranjo Álvarez, O. B., Rosales, M., & Méndez Berrueta, H. (2013). La inteligencia lingüística y el aprendizaje del inglés en alumnos. Exploraciones, Intercambios y Relaciones Entre El Diseño y La Tecnología, 57–79. https://doi.org/10.16/CSS/JQUERY.DATATABLES.MIN.CSS
Ortiz-Farfán, N., & Camargo-Mendoza, J. E. (2020). Modelo computacional para reconocimiento de lenguaje de señas en un contexto colombiano. TecnoLógicas, 23(48), 197–232. https://doi.org/10.22430/22565337.1585
Quesada, L., López, G., & Guerrero, L. (2017). Automatic recognition of the American sign language fingerspelling alphabet to assist people living with speech or hearing impairments. Journal of Ambient Intelligence and Humanized Computing, 8(4), 625–635. https://doi.org/10.1007/S12652-017-0475-7
Ruíz Parrales, E. C., & Bastidas Zambrano, L. I. (2017). Posicionamiento SEO mediante la optimización de sitios web para el marketing digital. Pro Sciences: Revista de Producción, Ciencias e Investigación, 1(1), 6–9. https://doi.org/10.29018/ISSN.2588-1000VOL1ISS1.2017PP14-25
Trujillo Hernández, A. D., & E, G. A. L. (2007). Inteligencia artificial: emulación de mecanismos. Tecnointelecto, 4(2), 116–120. http://www.itvictoria.edu.mx/personal/default.html
Wadhawan, A., & Kumar, P. (2021). Sign Language Recognition Systems: A Decade Systematic Literature Review. Archives of Computational Methods in Engineering, 28(3), 785–813. https://doi.org/10.1007/S11831-019-09384-2

Most read articles by the same author(s)