“Synthetic\nMap”: A Graphic Organizer\nInspired by Artificial Neural Network Paradigms for Learning Organic\nSynthesis

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