Smith, DAVID KELHAM orcid.org/0000-0002-9881-2714 (2026) Creating a Podcast Using Generative Artificial Intelligence to Support Student Learning of Organic Reaction Mechanisms. JOURNAL OF CHEMICAL EDUCATION. ISSN: 0021-9584
Abstract
A podcast was created by Google NotebookLM artificial intelligence and applied to support learning in a Year 1 university organic chemistry course. The Generative AI (GenAI) was trained using an open access article presenting priority and selectivity rules for organic reaction mechanisms. The software performed very well in terms of background material, showing creativity. Coherent explanations of organic chemistry were also given, although some technical errors were made in chemical detail and there was some pedagogic confusion. The source material was edited and two further podcast versions created. All three podcast outputs were combined with academic curation to create a final output with minimal errors. The podcast was released to students, being advertised as AI-generated support material. Students who listened to the podcast reported it helped reinforce learning and was worth listening to. However, a number of students were concerned about ethical, societal, and sustainability concerns of using AI, and some actively chose not to engage with it. In summary, with academic curation, Google NotebookLM can make engaging scientific podcasts with limited workload. However, student attitudes to the use of AI in education must be carefully considered.
Metadata
| Item Type: | Article |
|---|---|
| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © 2026 The Author. Published by American Chemical Society and Division of Chemical Education, Inc. |
| Dates: |
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| Institution: | The University of York |
| Academic Units: | The University of York > Faculty of Sciences (York) > Chemistry (York) |
| Date Deposited: | 30 Mar 2026 15:00 |
| Last Modified: | 31 Mar 2026 23:08 |
| Published Version: | https://doi.org/10.1021/acs.jchemed.5c01652 |
| Status: | Published |
| Refereed: | Yes |
| Identification Number: | 10.1021/acs.jchemed.5c01652 |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:239640 |
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