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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.