2026-01-14T09:07:36Z
2026-01-14T09:07:36Z
2024-09-09
2026-01-14T09:07:36Z
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.
Article
Published version
English
Química orgànica; Teories de l'aprenentatge; Síntesi orgànica; Xarxes neuronals (Neurobiologia); Organic chemistry; Learning theories; Organic synthesis; Neural networks (Neurobiology)
Division of Chemical Education of the American Chemical Society.
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
cc-by (c) Carlos Luque Corredera, et al., 2024
https://creativecommons.org/licenses/by/4.0/