Inteligencia Artificial Generativa y la Resolución Algorítmica: Análisis Comparativo entre Gemini, Socratic y Photomath en la Educación Matemática Universitaria

Artigo2026

Joshua Guillermo Gómez Dávila ORCID

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Resumo

The advancement of emerging digital technologies has transformed the didactics of exact sciences. The objective of this article is to comparatively analyze the impact of generative artificial intelligence (Gemini) versus algorithmic resolution applications (Photomath and Socratic) in the teaching and learning process of mathematics at the university level. The methodology used under a mixed approach and explanatory sequential design, included a sample of 60 students taking the Mathematics I, II and III courses. In the quantitative phase, the precision and procedural efficacy of the tools in differential and integral calculus problems were measured, while the qualitative phase evaluated the development of the students' heuristic reasoning. The results reveal that, although algorithmic solvers offer high efficacy in procedural numerical assessment, they generate mechanistic dependence. In contrast, Gemini acts as a cognitive orchestrator that, through dialogue, facilitates the epistemological transition from instruction to mathematical self-discovery (PAH Continuum). It is concluded that the integration of Large Language Models (LLM) in higher mathematical education overcomes the paradigm of the simple immediate result, demanding a restructuring of assessment strategies and fostering an analytical, critical learning adapted to contemporary virtual environments.

Dados da obra

Tipo
Artigo
Periódico
REVISTA CIENTIFICA EONLINETECH, v. 5, n. 3, p. 2-18
Ano
2026 (2026-09-25)
Palavras-chave
generative AI; large language models; Gemini; Photomath; Socratics; algorithmic problem solving; university mathematics education; differential and integral calculus; heuristic reasoning; assessment methods
Temas
Avaliação, Cálculo, Resolução de Problemas, Tecnologias Digitais
DOI
10.53485/ret.v5i3.778
ISSN
2771-361X
Licença
cc-by-nc-sa
Acesso
Em verificação
Fontes
OpenAlex
Na Biblioteca desde
01/10/2026 · verificada em 03/10/2026

Como citar

ABNT
DÁVILA, Joshua Guillermo Gómez. Inteligencia Artificial Generativa y la Resolución Algorítmica: Análisis Comparativo entre Gemini, Socratic y Photomath en la Educación Matemática Universitaria. REVISTA CIENTIFICA EONLINETECH, v. 5, n. 3, p. 2-18, 2026. DOI: https://doi.org/10.53485/ret.v5i3.778.

APA

Dávila, J. G. G. (2026). Inteligencia Artificial Generativa y la Resolución Algorítmica: Análisis Comparativo entre Gemini, Socratic y Photomath en la Educación Matemática Universitaria. REVISTA CIENTIFICA EONLINETECH, 5(3), 2-18. https://doi.org/10.53485/ret.v5i3.778

BibTeX
@article{davila2026,
  author = {Dávila, Joshua Guillermo Gómez},
  title = {Inteligencia Artificial Generativa y la Resolución Algorítmica: Análisis Comparativo entre Gemini, Socratic y Photomath en la Educación Matemática Universitaria},
  year = {2026},
  journal = {REVISTA CIENTIFICA EONLINETECH},
  volume = {5},
  number = {3},
  pages = {2-18},
  doi = {10.53485/ret.v5i3.778}
}
RIS
TY  - JOUR
AU  - Dávila, Joshua Guillermo Gómez
TI  - Inteligencia Artificial Generativa y la Resolución Algorítmica: Análisis Comparativo entre Gemini, Socratic y Photomath en la Educación Matemática Universitaria
PY  - 2026
JO  - REVISTA CIENTIFICA EONLINETECH
VL  - 5
IS  - 3
SP  - 2
EP  - 18
DO  - 10.53485/ret.v5i3.778
ER  - 

Referência gerada automaticamente a partir dos metadados das fontes; confira com o documento original. Baixar BibTeX · Baixar RIS

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