# Implementation of a soft grading system for chemistry in a Moodle plugin: reaction handling

**Authors:** Louis Plyer, Gilles Marcou, Céline Perves, Fanny Bonachera, Alexander Varnek

PMC · DOI: 10.1186/s13321-024-00889-y · Journal of Cheminformatics · 2024-08-01

## TL;DR

This paper introduces a Moodle plugin that grades chemistry reaction questions with tolerance using a graph-based approach, improving remote education assessments.

## Contribution

The work introduces an open-source, configurable grading system for chemical reactions using Condensed Graph of Reaction (CGR) similarity.

## Key findings

- A workflow using pairwise reaction similarity assessment via molecular graphs was developed.
- The plugin integrates with Chemdoodle and a REST server for visualization and similarity scoring.
- The system allows configurable similarity measures and fragmentation for flexible grading.

## Abstract

Here, we present a new method for evaluating questions on chemical reactions in the context of remote education. This method can be used when binary grading is not sufficient as some tolerance may be acceptable. In order to determine a grade, the developed workflow uses the pairwise similarity assessment of two considered reactions, each encoded by a single molecular graph with the help of the Condensed Graph of Reaction (CGR) approach. This workflow is part of the ChemMoodle project and is implemented as a Moodle Plugin. It uses the Chemdoodle engine for reaction drawing and visualization and communicates with a REST server calculating the similarity score using ISIDA fragment descriptors. The plugin is open-source, accessible in GitHub (https://github.com/Laboratoire-de-Chemoinformatique/moodle-qtype_reacsimilarity) and on the Moodle plugin store (https://moodle.org/plugins/qtype_reacsimilarity?lang=en). Both similarity measures and fragmentation can be configured.

Scientific contribution

This work introduces an open-source method for evaluating chemical reaction questions within Moodle using the CGR approach. Our contribution provides a nuanced grading mechanism that accommodates acceptable tolerances in reaction assessments, enhancing the accuracy and flexibility of the grading process.

## Full-text entities

- **Diseases:** AAM (MESH:C535477), deficiencies (MESH:D007153), Covid 19 (MESH:D000086382)
- **Chemicals:** hydrogens (MESH:D006859), butadiene (MESH:C031763), Ammonia (MESH:D000641), Indigo (MESH:D007203), Pentane-2,4-dione (MESH:C008790), ethylene (MESH:C036216), AAM (-)

## Full text

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## Figures

6 figures with captions in the complete paper: https://tomesphere.com/paper/PMC11295431/full.md

## References

8 references — full list in the complete paper: https://tomesphere.com/paper/PMC11295431/full.md

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Source: https://tomesphere.com/paper/PMC11295431