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

# metadata.dc.description.abstract[].value
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.

# metadata.dc.publisher[].value
Division of Chemical Education of the American Chemical Society.

# metadata.dc.rights[].value
cc-by (c) Carlos Luque Corredera, et al., 2024

# metadata.dc.source[].value
Articles publicats en revistes (Farmacologia, Toxicologia i Química Terapèutica)

# metadata.dc.title[].value
“Synthetic Map”: A Graphic Organizer Inspired by Artificial Neural Network Paradigms for Learning Organic Synthesis.