Plyer Louis, Marcou Gilles, Perves Céline, Bonachera Fanny, Varnek Alexander
Faculté de Chimie, University of Strasbourg, Strasbourg, France.
Laboratory of Chemoinformatics-UMR7140, University of Strasbourg, Strasbourg, France.
J Cheminform. 2024 Aug 1;16(1):90. doi: 10.1186/s13321-024-00889-y.
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.
在此,我们提出一种在远程教育背景下评估化学反应问题的新方法。当二元评分不够充分,因为某些容差是可以接受的时,就可以使用这种方法。为了确定成绩,所开发的工作流程使用两个考虑的反应的成对相似性评估,每个反应都借助反应凝聚图(CGR)方法由单个分子图编码。此工作流程是ChemMoodle项目的一部分,并作为Moodle插件实现。它使用Chemdoodle引擎进行反应绘制和可视化,并与使用ISIDA片段描述符计算相似性分数的REST服务器通信。该插件是开源的,可在GitHub(https://github.com/Laboratoire-de-Chemoinformatique/moodle-qtype_reacsimilarity)和Moodle插件商店(https://moodle.org/plugins/qtype_reacsimilarity?lang=en)上获取。相似性度量和碎片化都可以进行配置。科学贡献 这项工作引入了一种使用CGR方法在Moodle中评估化学反应问题的开源方法。我们的贡献提供了一种细致入微的评分机制,该机制在反应评估中考虑了可接受的容差,提高了评分过程的准确性和灵活性。