Publicación: Evaluación de la percepción de estudiantes de la Facultad de Ciencias y Humanidades de la Universidad del Valle de Guatemala respecto al uso de la inteligencia artificial
| dc.contributor.author | Morán Rivera, Carlos Adolfo | |
| dc.contributor.educationalvalidator | Cosenza Barnéond, Marie Andre | |
| dc.date.accessioned | 2025-10-27T22:00:18Z | |
| dc.date.issued | 2024 | |
| dc.description | Formato PDF digital — 68 páginas — incluye gráficos, tablas y referencias bibliográficas. | |
| dc.description.abstract | La implementación de la inteligencia artificial (IA) en la educación se está transformando en un instrumento esencial para los métodos de enseñanza. La comprensión y percepción de la IA por parte de los estudiantes de la Facultad de Ciencias y Humanidades de la Universidad del Valle de Guatemala han sido determinadas en el presente estudio. El objetivo principal fue explorar las percepciones y preocupaciones de los estudiantes respecto al uso de la IA en la experiencia educativa. En el presente trabajo, se ha explorado la autopercepción del conocimiento y las expectativas de los estudiantes acerca de la implementación de la IA en el sistema educativo mediante encuestas electrónicas. Se efectuó un estudio en el que se evaluó la percepción de 84 estudiantes de la Facultad de Ciencias y Humanidades de la Universidad del Valle de Guatemala respecto al uso de la IA en la educación universitaria. La muestra incluyó estudiantes de nueve carreras, de esta facultad. El 62% de los estudiantes reportó tener un conocimiento básico o intermedio de la IA, mientras que solo un 7% lo considera avanzado y un 1% señaló no tener conocimiento respecto a la IA. A pesar de esto, el 92.8% reportó usar IA en su vida diaria, particularmente en aplicaciones de navegación como en Física (32%), también las aplicaciones de streaming como en el caso de Química Farmacéutica (27.7%) y traducción en el caso de Matemática Aplicada (31,6%). No obstante, el 83% expresó que no ha recibido ningún taller o curso relacionado con IA dentro de la universidad. Respecto a la mejora en la educación universitaria, un 73.8% se mostró de acuerdo o totalmente de acuerdo con esta afirmación. Además, el 58.3% indicó el análisis de datos educativos como el principal beneficio, seguido por la personalización de la experiencia educativa (hasta un 57.1% en Física). Únicamente un 9.3% seleccionaron a los exámenes automatizados como un beneficio. Las preocupaciones más frecuentes indicadas por los estudiantes en relación con la implementación de la IA fueron: La posibilidad de errores de la IA (40.5%), dilemas éticos (26.4%), privacidad (19.2%), y sustitución de docentes (17.3%). Estas inquietudes estuvieron presentes reiteradamente, especialmente en las respuestas pertenecientes a Comunicación Estratégica, Biotecnología Molecular, Física y Química Farmacéutica. En conclusión, el estudio evidenció una actitud mayoritariamente positiva en relación con la implementación de la IA en la educación, pero simultáneamente demuestra una carencia de formación formal y una preocupación legítima por los riesgos éticos y técnicos. Por lo tanto, se recomienda incorporar contenidos relacionados a la IA en los planes de estudio, implementar talleres que presenten sus aplicaciones como implicaciones éticas, y efectuar estudios ampliados a otras facultades para una mayor comprensión. | |
| dc.description.abstract | The implementation of artificial intelligence (AI) in education is becoming an essential tool for teaching methods. The understanding and perception of AI among students from the Faculty of Science and Humanities at Universidad del Valle de Guatemala were determined in the present study. The main objective was to explore students’ perceptions and concerns regarding the use of AI in their educational experience. This study explored students’ self-perception of knowledge and expectations about the implementation of AI in the educational system through electronic surveys. A study was conducted to evaluate the perception of 84 students from the Faculty of Science and Humanities at Universidad del Valle de Guatemala regarding the use of AI in higher education. The sample included students from nine academic programs within the faculty. A total of 62% of the students reported having a basic or intermediate knowledge of AI, while only 7% considered their knowledge advanced, and 1% stated they had no knowledge of AI. Despite this, 92.8% reported using AI in their daily lives—particularly in navigation applications among Physics students (32%), streaming applications among Pharmaceutical Chemistry students (27.7%), and translation tools among Applied Mathematics students (31.6%). However, 83% indicated that they had not received any workshop or course related to AI within the university, including programs such as Strategic Communication, Molecular Biotechnology, Physics, and Pharmaceutical Chemistry. In conclusion, the study revealed a predominantly positive attitude toward the implementation of AI in education, while also highlighting a lack of formal training and legitimate concerns about ethical and technical risks. Therefore, it is recommended to incorporate AI-related content into academic curricula, implement workshops that address both applications and ethical implications, and conduct broader studies across other faculties for a more comprehensive understanding. Regarding improvements in higher education, 73.8% of students agreed or strongly agreed that AI enhances university education. Furthermore, 58.3% identified educational data analysis as the main benefit, followed by the personalization of the learning experience (up to 57.1% among Physics students). Only 9.3% selected automated testing as a benefit. The most frequent concerns reported by students regarding the implementation of AI were: the possibility of AI errors (40.5%), ethical dilemmas (26.4%), privacy issues (19.2%), and teacher replacement (17.3%). These concerns were repeatedly mentioned, particularly in responses from students in the Communication program. | |
| dc.description.degreelevel | Pregrado | |
| dc.description.degreename | Licenciado en Química Farmacéutica | |
| dc.format.extent | 68 p. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | https://repositorio.uvg.edu.gt/handle/123456789/6169 | |
| dc.language.iso | spa | |
| dc.publisher | Universidad del Valle de Guatemala | |
| dc.publisher.branch | Campus Central | |
| dc.publisher.faculty | Facultad de Ciencias y Humanidades | |
| dc.publisher.place | Guatemala | |
| dc.publisher.program | Licenciatura en Química Farmacéutica | |
| dc.relation.references | Australian Government. (2024). Australia’s AI Ethics Principles. Department of Industry, Science and Resources. https://www.industry.gov.au/publications/australias artificial-intelligence-ethics-framework/australias-ai-ethics-principles. Avid Open Access. (2024). AI and the 4 Cs: Communication. Avid Open Access. openaccess.org/resource/ai-and-the-4-cs-communication/#1712783523038- e7a02b5a- a154 | |
| dc.relation.references | Bernardi, J., Mukobi, G., Greaves, H., Heim, L., & Anderljung, M. (2024). Societal Adaptation to Advanced AI. arXiv (Cornell University). https://doi.org/10.48550/arxiv.2405.10295 | |
| dc.relation.references | Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(1). https://doi.org/10.1186/s41239-023- 00411-8 | |
| dc.relation.references | Darbinyan, R. (2023). How AI transforms social media. Forbes Technology Council. Forbes. https://www.forbes.com/councils/forbestechcouncil/2023/03/16/how-ai transforms-social-media/ | |
| dc.relation.references | Elliott, D. (2024). Artificial intelligence in education: A teachers' union perspective. World Economic Forum. https://www.weforum.org/stories/2024/07/artificial intelligence-education-teachers-union/ Gates, B. (2023). The Age of AI has begun. GatesNotes. https://www.gatesnotes.com/The-Age-of-AI-Has-Begun | |
| dc.relation.references | Ghafouri, V., Agarwal, V., Zhang, Y., Sastry, N., Such, J., & Suarez-Tangil, G. (2023). AI in the Gray: Exploring Moderation Policies in Dialogic Large Language Models vs. Human Answers in Controversial Topics. Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 556- 565. https://doi.org/10.1145/3583780.3614777. | |
| dc.relation.references | Harrer, S. (2023). Attention is not all you need: the complicated case of ethically using large language models in healthcare and medicine. EBioMedicine, 90, 104512. https://doi.org/10.1016/j.ebiom.2023.104512 | |
| dc.relation.references | ISO. (2024).What is artificial intelligence (AI)? ISO Organization. https://www.iso.org/artificial-intelligence/what-is-ai | |
| dc.relation.references | Johannessen, J. (2020). Artificial Intelligence, Automation and the Future of Competence at Work. https://doi.org/10.4324/9781003121923 | |
| dc.relation.references | Kahraman, H. T., Sagiroglu, S., & Colak, I. (2010). Development of adaptive and intelligent web-based educational systems. Int. Conf. Appl. Inf. Commun. Technol. https://doi.org/10.1109/icaict.2010.5612054 | |
| dc.relation.references | Lubowitz, J. H. (2023). ChatGPT, an artificial intelligence chatbot, is impacting medical literature. Arthroscopy, 39(5), 1121–1122. https://doi.org/10.1016/j.arthro.2023.01.015 | |
| dc.relation.references | Mhlanga, D. (2023). Open AI in Education, the Responsible and Ethical Use of ChatGPT Towards Lifelong Learning. En Sustainable development goals series (pp. 387- 409). https://doi.org/10.1007/978-3-031-37776-1_17 | |
| dc.relation.references | Naughton, J. (2023). ChatGPT is the AI world’s ‘Pearl Harbor moment’ – and the tech giants are terrified. The Guardian. https://www.theguardian.com/commentisfree/2023/dec/09/chatgpt-ai-pearl harbor- moment-sam-altman | |
| dc.relation.references | Ortiz, G. (2016). Sobre la distinción entre ética y moral. Isonomía, (45), 113-139. https://www.redalyc.org/pdf/3636/363648284005.pdf | |
| dc.relation.references | Parsons, L., & Parsons, L. (2024). Great promise but potential for peril. Harvard Gazette. https://news.harvard.edu/gazette/story/2020/10/ethical-concerns-mount-as-ai | |
| dc.relation.references | Rus, V., D’Mello, S. K., Hu, X., & Graesser, A. C. (2013). Recent Advances in Conversational Intelligent Tutoring Systems. AI Magazine, 34(3), 42-54. https://doi.org/10.1609/aimag.v34i3.2485. | |
| dc.relation.references | Selvam, A. (2024). Exploring the impact of artificial intelligence on transforming physics, chemistry, and biology education. TheCuvette, 2, 1–31. 10.21428/a70c814c.747297aa | |
| dc.relation.references | Timms, M. J. (2016). Letting Artificial Intelligence in Education Out of the Box: Educational Cobots and Smart Classrooms. International Journal Of Artificial Intelligence In Education, 26(2), 701-712. https://doi.org/10.1007/s40593-016-0095-y. | |
| dc.relation.references | United Nations Educational, Scientific and Cultural Organization [UNESCO]. (2024). Artificial intelligence in education. https://www.unesco.org/en/digital education/artificial-intelligence. Universidad del Valle de Guatemala [UVG]. (2024). Para UVG, la investigación es una prioridad. https://www.uvg.edu.gt/impacto/investigacion/. | |
| dc.relation.references | Wang, C., Li, Z., & Bonk, C. (2024). Understanding Self-Directed Learning in AI- Assisted Writing: A Mixed Methods Study of Postsecondary Learners. Computers And Education Artificial Intelligence, 6, 100247. https://doi.org/10.1016/j.caeai.2024.100247 | |
| dc.rights.accessrights | info:eu-repo/semantics/openAccess | |
| dc.rights.coar | http://purl.org/coar/access_right/c_abf2 | |
| dc.rights.license | Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0) | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject.armarc | Artificial intelligence | |
| dc.subject.armarc | Inteligencia artificial | |
| dc.subject.armarc | Tecnología educativa | |
| dc.subject.armarc | Educación superior | |
| dc.subject.armarc | Innovaciones educativas | |
| dc.subject.armarc | Education, Higher – Guatemala | |
| dc.subject.ddc | 300 - Ciencias sociales::303 - Procesos sociales | |
| dc.subject.ocde | 2. Ingeniería y Tecnología | |
| dc.subject.ods | ODS 4: Educación de calidad. Garantizar una educación inclusiva y equitativa de calidad y promover oportunidades de aprendizaje permanente para todos | |
| dc.title | Evaluación de la percepción de estudiantes de la Facultad de Ciencias y Humanidades de la Universidad del Valle de Guatemala respecto al uso de la inteligencia artificial | |
| dc.title.translated | Evaluation of the perception of students from the Faculty of Science and Humanities at Universidad del Valle de Guatemala regarding the use of artificial intelligence | |
| dc.type | Trabajo de grado - Pregrado | |
| dc.type.coar | http://purl.org/coar/resource_type/c_7a1f | |
| dc.type.coarversion | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |
| dc.type.content | Text | |
| dc.type.driver | info:eu-repo/semantics/bachelorThesis | |
| dc.type.version | info:eu-repo/semantics/publishedVersion | |
| dc.type.visibility | Public Thesis | |
| dspace.entity.type | Publication |
