Un panorama de usos de la inteligencia artificial en la educación en estadística.
| dc.contributor.advisor | Rendón Mayorga, César Guillermo | spa |
| dc.contributor.author | Barreto Pinilla, Michael | spa |
| dc.coverage.temporal | 2020-2025 | |
| dc.date.accessioned | 2026-09-03T17:40:23Z | |
| dc.date.available | 2026-09-03T17:40:23Z | |
| dc.date.issued | 2026 | |
| dc.description.abstract | En este trabajo se analiza el papel de la inteligencia artificial (IA) en la enseñanza y el aprendizaje de la estadística a partir de una revisión de alcance (scoping review). En un contexto educativo mediado cada vez más por tecnologías digitales emergentes, resulta fundamental comprender cómo estas herramientas se incorporan a los procesos formativos en educación estadística y cuáles son sus principales aportes, limitaciones y desafíos. Metodológicamente, la investigación se desarrolló bajo un enfoque documental, siguiendo los lineamientos para revisiones de alcance propuestos por Mak y Thomas (2022). El análisis de los documentos seleccionados evidenció una tendencia creciente en el uso de herramientas basadas en IA en la educación estadística, con un predominio de modelos de lenguaje de gran tamaño (LLM) y una concentración de las experiencias en el nivel universitario, en contraste con una menor presencia en la educación básica y media. Como limitaciones recurrentes, se identifican la falta de precisión en las respuestas de la IA, los sesgos algorítmicos, la brecha digital, la dependencia tecnológica y la insuficiente formación docente para una integración pedagógica significativa. Se concluye que la IA representa una oportunidad significativa para transformar la enseñanza de la estadística, siempre que su incorporación esté mediada por criterios pedagógicos claros, una postura crítica y reflexiva, y un sentido ético por parte del profesor. Finalmente, se reconocen vacíos relevantes en la literatura, particularmente en contextos escolares y en los procesos de formación inicial de futuros profesores de matemáticas. | spa |
| dc.description.abstractenglish | This study aims to analyze the role of artificial intelligence (AI) in the teaching and learning of statistics through a scoping review. In an educational context increasingly mediated by emerging digital technologies, it is essential to understand how these tools are being incorporated into educational processes in statistics education and what their main contributions, limitations, and challenges are. Methodologically, the research was conducted using a documentary approach, following the scoping review guidelines proposed by Mak and Thomas (2022). The analysis of the selected documents revealed a growing trend in the use of AI based tools in statistics education, with a predominance of large language models and a concentration of experiences at the university level, compared to a lower presence in primary and secondary education. Recurring limitations include the accuracy of AI generated responses, algorithmic bias, the digital divide, technological dependence, and insufficient teacher training for meaningful pedagogical integration. It is concluded that AI represents a significant opportunity to transform the teaching of statistics, provided that its use is guided by clear pedagogical criteria, a critical and reflective perspective, and an ethical awareness on the part of teachers. Relevant gaps in literature are identified, particularly in school contexts and in the initial training of future mathematics or statistics teachers. | eng |
| dc.description.degreelevel | Pregrado | spa |
| dc.description.degreename | Licenciado en Matemáticas | spa |
| dc.format.mimetype | application/pdf | spa |
| dc.identifier.instname | instname:Universidad Pedagógica Nacional | spa |
| dc.identifier.reponame | reponame: Repositorio Institucional UPN | spa |
| dc.identifier.repourl | repourl: http://repositorio.pedagogica.edu.co/ | |
| dc.identifier.uri | http://hdl.handle.net/20.500.12209/22905 | |
| dc.language.iso | es | |
| dc.publisher | Universidad Pedagógica Nacional | spa |
| dc.publisher.faculty | Facultad de Ciencia y Tecnología | spa |
| dc.publisher.program | Licenciatura en Matemáticas | spa |
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| dc.rights.accessrights | info:eu-repo/semantics/openAccess | |
| dc.rights.accessrights | http://purl.org/coar/access_right/c_abf2 | |
| dc.rights.creativecommons | Attribution-NonCommercial-NoDerivatives 4.0 International | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | Inteligencia artificial | spa |
| dc.subject | Educación estadística | spa |
| dc.subject | Revisión de alcance | spa |
| dc.subject.keywords | Artificial intelligence | eng |
| dc.subject.keywords | Statistics education | eng |
| dc.subject.keywords | Scoping review | eng |
| dc.title | Un panorama de usos de la inteligencia artificial en la educación en estadística. | spa |
| dc.type.coar | http://purl.org/coar/resource_type/c_7a1f | eng |
| dc.type.driver | info:eu-repo/semantics/bachelorThesis | eng |
| dc.type.hasVersion | info:eu-repo/semantics/acceptedVersion | |
| dc.type.local | Tesis/Trabajo de grado - Monografía - Pregrado | spa |
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