Marco referencial simbiótico para seleccionar estrategias optimizadas de enseñanza

Authors

  • Pablo Rovarini Díaz Universidad del Norte Santo Tomas de Aquino. Laboratorio de Inteligencia Artificial
  • Maria Laura Rovarini Universidad del Norte Santo Tomas de Aquino. Laboratorio de Inteligencia Artificial
  • Mario Figueroa de la Cruz Universidad del Norte Santo Tomas de Aquino. Laboratorio de Inteligencia Artificial
  • Claudia Solorzano Universidad del Norte Santo Tomas de Aquino. Laboratorio de Inteligencia Artificial

Keywords:

symbiosis, human-machine collaboration, educational strategies, the school of the future, hy bridization of models

Abstract

In a post-pandemic world, we place our hope of guaranteeing knowledge transfer with high levels of excellence, in the efficient selection of teaching strategies that show stability and effectiveness. The use of computers in this task is vital, particularly if we use them collaboratively with tasks performed by humans, enhancing this link with the use of models from Artificial Intelligence. In this work we show our ideas on how to design a module based on usual models in decision-making and prognosis tasks, taking as a basis a platform developed by our group, already successfully completed, with the addition of the current conception of the use of symbiosis possible to achieve between humans and machines.

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References

Saracco. R. et al. (2017). Symbiotic autonomous systems White Paper I. SAS - FDC. Piscataway, NJ: IEEE. (http://digitalreality.ieee.org)

Saracco, R. et al. (2018). Symbiotic autonomous systems White Paper II. SAS - FDC. Piscataway, NJ: IEEE. (http://digitalreality.ieee.org)

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Saracco, R. (2020). Digital Transformation. DRI - FDC. Piscataway, NJ: IEEE. (http://digitalreality. ieee.org)

Figueroa, M.; Rovarini, P.; Rovarini, M.L.; Solorzano, C. (2020). Flexible System Based in Hybrid Algorithms Used in Decision Making - 17th International Confer ence on Remote Engineering and Virtual Instrumen tation, Georgia University, EEUU, February 27.

Rovarini, P. C. (2020). Inteligencia Computacional. Ed. UNSTA, Universidad del Norte Santo Tomas de Aquino. ISBN 978-987-1662-99-9.

Rovarini, P.C.; Figueroa, M.; Rovarini, M.L.; Rico, E. (2021). Nuevo Enfoque para Seleccionar una Estrate gia Optimizada de Enseñanza. RADI, Revista Argentina de Ingeniería), mayo 2021, pp.80-88. https://confedi.org.ar/nuevo-enfoque-para-seleccionar-una-estrategia-optimizada-de-ensenanza/

Rovarini P. C.; Jordan, G; Figueroa, M.; Rovarini, ML. (2021). Decision Making Framework through a Political Rational Model I. Enviado a Science Inter Fluvius SIF (Revista Electrónica bilinge de la Universidad de Entre Ríos. Argentina. En etapa de revisión.

Published

2022-05-30

How to Cite

Rovarini Díaz, P., Rovarini, M. L., Figueroa de la Cruz, M., & Solorzano, C. (2022). Marco referencial simbiótico para seleccionar estrategias optimizadas de enseñanza. Revista Argentina De Ingeniería, 19, 83–88. Retrieved from https://www.radi.org.ar/index.php/radi/article/view/149

Issue

Section

ARTÍCULOS