“Synthetic Map”: A Graphic Organizer Inspired by Artificial Neural Network Paradigms for Learning Organic Synthesis.

Fecha de publicación

2026-01-14T09:07:36Z

2026-01-14T09:07:36Z

2024-09-09

2026-01-14T09:07:36Z

Resumen

Organic Chemistry is widely recognized as a challenging subject, with the design of syntheses and retrosyntheses identified as particularly difficult tasks. Inspired by the success of artificial neural networks in machine learning, we propose a framework that leverages similar principles to enhance the teaching and learning of organic synthesis. In this paper, we introduce a novel teaching tool, the “Synthetic Map”, that attempts to visually recreate an expert’s mental map and conceptual understanding of organic synthesis built over years of experience. The educational benefits of the Synthetic Map were evaluated through its implementation in an Organic Chemistry course of a Pharmacy degree over two years. The new tool promoted students’ learning by providing a mental organizer fostering a deeper understanding of the subject and empowering students to design and execute effective synthetic strategies.

Tipo de documento

Artículo


Versión publicada

Lengua

Inglés

Publicado por

Division of Chemical Education of the American Chemical Society.

Documentos relacionados

Reproducció del document publicat a: https://doi.org/10.1021/acs.jchemed.4c00592

Journal of Chemical Education, 2024, vol. 101, num.10, p. 4256-4267

https://doi.org/10.1021/acs.jchemed.4c00592

Citación recomendada

Esta citación se ha generado automáticamente.

Derechos

cc-by (c) Carlos Luque Corredera, et al., 2024

https://creativecommons.org/licenses/by/4.0/

Este ítem aparece en la(s) siguiente(s) colección(ones)