{"title":"Patterns in Explanations of Organic Chemistry Reaction Mechanisms: A Text Analysis by Level of Explanation Sophistication","authors":"Caroline J. Crowder, and , Jeffrey R. Raker*, ","doi":"10.1021/acs.jchemed.4c0104210.1021/acs.jchemed.4c01042","DOIUrl":null,"url":null,"abstract":"<p >Learning the language of organic chemistry, i.e., how to describe reaction mechanisms, is crucial to success in any postsecondary organic chemistry course. However, it is well-known that learners struggle with reasoning about and explaining reaction mechanisms beyond surface-level features. Multiple studies have sought to aid learners in developing these skills. Investigating the connections that learners make regarding reaction mechanisms through their explanations provides insight into how we can better promote the development of learners’ reasoning skills. In this study, we evaluate 20,000+ learner explanations of 90 reaction mechanisms. We use network analysis to explore patterns in keywords used by learners and visualize the word connections between them, based on their co-occurrence, within our entire data set, by reaction type, and by levels of explanation sophistication. Our results indicate that learners consistently rely on explicit surface-level features in their explanations with expected contextual variance by reaction type. This trend persists across the levels of sophistication, however, with improvements in the use of vocabulary and coherency as sophistication progresses. We hypothesize that this is evidence of learners actively working toward constructing understanding as they experiment with and refine their vocabulary until they are able to pare down their explanations in a coherent manner. This work offers insights for instructors seeking to promote the development of learners’ reasoning skills and for researchers interested in the development of machine-learning models to assist in evaluating learner explanations of reaction mechanisms.</p>","PeriodicalId":43,"journal":{"name":"Journal of Chemical Education","volume":"101 12","pages":"5203–5220 5203–5220"},"PeriodicalIF":2.5000,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Chemical Education","FirstCategoryId":"92","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acs.jchemed.4c01042","RegionNum":3,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Learning the language of organic chemistry, i.e., how to describe reaction mechanisms, is crucial to success in any postsecondary organic chemistry course. However, it is well-known that learners struggle with reasoning about and explaining reaction mechanisms beyond surface-level features. Multiple studies have sought to aid learners in developing these skills. Investigating the connections that learners make regarding reaction mechanisms through their explanations provides insight into how we can better promote the development of learners’ reasoning skills. In this study, we evaluate 20,000+ learner explanations of 90 reaction mechanisms. We use network analysis to explore patterns in keywords used by learners and visualize the word connections between them, based on their co-occurrence, within our entire data set, by reaction type, and by levels of explanation sophistication. Our results indicate that learners consistently rely on explicit surface-level features in their explanations with expected contextual variance by reaction type. This trend persists across the levels of sophistication, however, with improvements in the use of vocabulary and coherency as sophistication progresses. We hypothesize that this is evidence of learners actively working toward constructing understanding as they experiment with and refine their vocabulary until they are able to pare down their explanations in a coherent manner. This work offers insights for instructors seeking to promote the development of learners’ reasoning skills and for researchers interested in the development of machine-learning models to assist in evaluating learner explanations of reaction mechanisms.
期刊介绍:
The Journal of Chemical Education is the official journal of the Division of Chemical Education of the American Chemical Society, co-published with the American Chemical Society Publications Division. Launched in 1924, the Journal of Chemical Education is the world’s premier chemical education journal. The Journal publishes peer-reviewed articles and related information as a resource to those in the field of chemical education and to those institutions that serve them. JCE typically addresses chemical content, activities, laboratory experiments, instructional methods, and pedagogies. The Journal serves as a means of communication among people across the world who are interested in the teaching and learning of chemistry. This includes instructors of chemistry from middle school through graduate school, professional staff who support these teaching activities, as well as some scientists in commerce, industry, and government.