High School Students and Artificial Intelligence: A neuroeducational perspective on literacy and self-improvement, thinking and creativity
DOI:
https://doi.org/10.1344/joned.v5i2.49030Keywords:
Artificial intelligence, students, literacy, self-improvement, thinking, creativity, educationAbstract
The incorporation of Artificial Intelligence (AI) in neuroeducation represents an enormous challenge for the development of digital skills and personalizing education from different angles. Despite the relatively recent global popularization of AI in the educational system, uncertainty prevails due to the lack of validated data available on how students integrate it into their daily academic life, which can limit the making of pertinent pedagogical adjustments; in addition, there is not enough comparative evidence of the management of this technology between the public and private sectors. To this end, the research aimed to: analyze the secondary education students, how they become literate in the use of AI and develop their cognitive and creative capacities with this technology, to consolidate personal and academic goals. The methodology adopted a quantitative, transversal and descriptive approach, supported by an ad hoc instrument applied to 576 secondary school students from public and private schools; Reliability tests were carried out using Cronbach's Alpha and non-parametric statistics through Pearson's Chi Square and Mann-Whitney U. The findings reveal that students about AI: recognize its importance and show interest in using it; not all have been taught to use it in their schools, some have learned to use it out of intrinsic motivation; they consider that it can help them consolidate achievements; they think that it can enhance their creativity, without diminishing their cognitive capacity; and they expressed that the excessive use of this technology can cause a strong dependence that leads to procrastination. It is concluded that educating students with AI can be crucial to incorporate them as digital citizens in a hyperconnected world; neuroeducationally, AI becomes a substantive element to optimize educational processes and promote cognitive and creative adaptation by personalizing learning, and more so by demonstrating that there is motivation among students to use it; the development of digital skills must be encouraged within an ethical and responsible framework; and teachers must assertively incorporate this technology into the classroom to promote meaningful and lasting learning.
References
UNESCO. Artificial Intelligence in Education: Challenges and Opportunities for Sustainable Development. París: UNESCO; 2019.
Ansari D, De Smedt B, Grabner RH. Neuroeducation – A Critical Overview of An Emerging Field. Neuroethics. 2012;5:105-17. Disponible en: https://doi.org/10.1007/s12152-011-9119-3
Jolles J, Jolles D. On Neuroeducation: Why and How to Improve Neuroscientific Literacy in Educational Professionals. Front Psychol. 2021;12. Disponible en: https://doi.org/10.3389/fpsyg.2021.752151
Júnior JC, De Medeiros Costa HC, Da Silva JM, Guimarães MR, De Faria PH, Braga FC, Vieira FB, De Melo EH. Inteligência Artificial e neuroeducação: O futuro do ensino personalizado. Lumen et Virtus. 2024;15(39):2241-51. Disponible en: https://doi.org/10.56238/levv15n39-051
Dai Y, Chai C, Lin P, Jong M, Guo Y, Qin J. Promoting Students’ Well-Being by Developing Their Readiness for the Artificial Intelligence Age. Sustainability. 2020;12(16):6597. Disponible en: https://doi.org/10.3390/su12166597
Yue M, Jong MS-Y, Dai Y. Pedagogical Design of K-12 Artificial Intelligence Education: A Systematic Review. Sustainability. 2022;14(23):15620. Disponible en: https://doi.org/10.3390/su142315620
Crawford J, Cowling M, Allen K. Leadership is needed for ethical ChatGPT: Character, assessment, and learning using artificial intelligence (AI). J Univ Teach Learn Pract. 2023;20(3):1-19. Disponible en: https://doi.org/10.53761/1.20.3.02
Velte P. Determinants and consequences of corporate social responsibility decoupling—Status quo and limitations of recent empirical quantitative research. Corp Soc Responsib Environ Manag. 2023;30(6):2695-2717. Disponible en: https://doi.org/10.1002/csr.2538
Pentang J. Quantitative research instrumentation for educators. Lecture Series on Research Process and Publication. 2023;1-7. Disponible en: https://philpapers.org/archive/PENQRI.pdf
Creswell JW. Research design: Qualitative, quantitative, and mixed methods approaches. 4th ed. SAGE Publications; 2014.
Parsons J, Clarke B. Rhizomic Thinking: Towards a New Consideration of Social Studies Practice. Soc Stud Res Pract. 2013;8(3):89-98. Disponible en: https://doi.org/10.1108/ssrp-03-2013-b0006
Creswell JW, Creswell JD. Research design: Qualitative, quantitative, and mixed methods approaches. 5th ed. SAGE Publications; 2018.
Babbie ER. The practice of social research. 15th ed. Cengage Learning; 2020.
Gatti A. Literacy and artificial intelligence. J Neuroeduc. 2024;5(1):52-58. Disponible en: https://doi.org/10.1344/joned.v5i1.46108
Llorens Largo F, Vidal J, García Peñalvo FJ. Ya llegó, ya está aquí, y nadie puede esconderse: La inteligencia artificial generativa en educación. Aula Magna. 2023;2. Disponible en: https://cuedespyd.hypotheses.org/14389
Ruiz-Bueno A. Método de encuesta: construcción de cuestionarios, pautas y sugerencias. REIRE. Rev Innov Investig Educ. 2009;96-110.
Albers M. Quantitative Data Analysis—In the Graduate Curriculum. J Techn Writ Commun. 2017;47(2):215-33. Disponible en: https://doi.org/10.1177/0047281617692067
González Alonso J, Pazmiño Santacruz M. Cálculo e interpretación del Alfa de Cronbach para el caso de validación de la consistencia interna de un cuestionario, con dos posibles escalas tipo Likert. Rev Publicando. 2015;2(1):62-67. Disponible en: https://revistapublicando.org/revista/index.php/crv/article/view/22/pdf_11
Ventura León J, Peña Calero BN. El mundo no debería girar alrededor del alfa de Cronbach≥, 70. Adicciones. 2020;33(4):369-72. Disponible en: https://www.adicciones.es/index.php/adicciones/article/view/1576/1177
Lederman N, Lederman J. Publishing Findings that are Not Significant: Can Non-significant Findings Be Significant? J Sci Teach Educ. 2016;27(4):349-55. Disponible en: https://doi.org/10.1007/s10972-016-9475-2
McShane B, Gal D, Gelman A, Robert C, Tackett J. Abandon Statistical Significance. Am Stat. 2017;73(1):235-45. Disponible en: https://doi.org/10.1080/00031305.2018.1527253
Petrescu M, Pop E, Mihoc T. Students' interest in knowledge acquisition in Artificial Intelligence. arXiv:2311.16193. 2023. Disponible en: https://arxiv.org/abs/2311.16193
Junior JCG, Costa HC de M, da Silva JM, Guimaraes MHR, de Faria PH, Braga FC, et al. Artificial Intelligence and neuroeducation: The future of personalized teaching. LEV [Internet]. 20 Agosto 2024;15(39):2241-5. Disponible en: https://periodicos.newsciencepubl.com/LEV/article/view/196
Chen L, Chen P, Lin Z. Artificial Intelligence in Education: A Review. IEEE Access. 2020;8:75264-78. Disponible en: https://doi.org/10.1109/ACCESS.2020.2988510
Díaz-Guerra D. El potencial de la inteligencia artificial en la mejora del aprendizaje y bienestar estudiantil: prácticas pedagógicas innovadoras desde una neurociencia educativa. Psiquemag. 2024;13(2):147-159. https://doi.org/10.18050/psiquemag.v13i2.3138
Zambrano-Muñoz CK. Pedagogía y neurociencia y sus conexiones emergentes en la educación actual. Horizon Nexus Journal [Internet]. 31 de Octubre de 2023;1(4):32-46. Disponible en: https://horizonnexusjournal.editorialdoso.com/index.php/home/article/view/27
Shete S, Koshti P, Pujari V. The Impact of AI-Powered Personalization on Academic Performance in Students. 2024 5th International Conference on Recent Trends in Computer Science and Technology (ICRTCST). 2024;295-301. Disponible en: https://doi.org/10.1109/ICRTCST61793.2024.10578480
Morandín-Ahuerma F. Neuroplasticidad: reconstrucción, aprendizaje y adaptación. En: Neuroeducación como herramienta epistemológica. Puebla: Consejo de Ciencia y Tecnología del Estado de Puebla (CONCYTEP); 2022;23-43. Disponible en: https://philarchive.org/archive/MORNRA-7
Restrepo Pineda AF. Conectando mentes y máquinas: neuroeducación e IA en la era del pensamiento computacional. Plumilla Educativa. 20 de Junio de 2024;33(1):1-15. Disponible en: https://revistasum.umanizales.edu.co/ojs/index.php/plumillaeducativa/article/view/5090
López Iglesias M, Tapia-Frade A, Ruiz Velasco CM. Patologías y dependencias que provocan las redes sociales en los jóvenes nativos digitales. RCyS [Internet]. 2 de enero de 2023;13:1-22. Disponible en: https://www.revistadecomunicacionysalud.es/index.php/rcys/article/view/301
Del Cisne Loján M, Antonio Romero J, Sancho Aguilera D, Yajaira Romero A. Consecuencias de la Dependencia de la Inteligencia Artificial en Habilidades Críticas y Aprendizaje Autónomo en los Estudiantes. Ciencia Latina [Internet]. 27 de abril de 2024;8(2):2368-82. Disponible en: https://ciencialatina.org/index.php/cienciala/article/view/10678
Hasibuan R, Azizah A. Analyzing the Potential of Artificial Intelligence (AI) in Personalizing Learning to Foster Creativity in Students. Enigma Educ. 2023;1(1):6-10. Disponible en: https://doi.org/10.61996/edu.v1i1.2
Bavelier D, Green CS, Dye MW. Children, wired: For better and for worse. Neuron. 2010;67(5):692-701. Disponible en: https://pubmed.ncbi.nlm.nih.gov/20826302/
Lluch L, Ni I. El ágora de la neuroeducación: La neuroeducación explicada y aplicada. Barcelona: Universidad de Barcelona; 2019. Disponible en: https://www.ub.edu/idp/web/sites/default/files/2019-12/Agora%20neuroeducacion.pdf
Forés Miravalles A, Ligioiz Vázquez M. Descubrir la neurodidáctica: aprender desde, en y para la vida. Barcelona: Editorial UOC; 2012. Disponible en: https://books.google.com.mx/books/about/Descubrir_la_neurodidáctica.html?id=YgjGeeEoMiAC&redir_esc=y
Bueno i Torrens D, Forés Miravalles A. Neurociencia aplicada a la educación. Cómo aprende el cerebro y qué consecuencias tiene. Reptes de la comunicació especialitzada. 2021;19. Disponible en: https://doi.org/10.1344/LSC-2021.19.5
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