{"title":"关于 \"比较大学化学学生与 ChatGPT 在涉及酸碱的计算中的表现 \"的评论","authors":"Joshua Schrier*, ","doi":"10.1021/acs.jchemed.4c00058","DOIUrl":null,"url":null,"abstract":"<p >In a recent paper in this <i>Journal</i> ( <cite><i>J. Chem. Educ.</i></cite> <span>2023</span>, <em>100</em>, 3934−3944), Clark et al. evaluated the performance of the GPT-3.5 large language model (LLM) on ten undergraduate pH calculation problems. They reported that GPT-3.5 gave especially poor results for salt and titration problems, returning the correct results only 10% and 0% of the time, respectively, and that, despite a correct application of heuristics, the LLM made mathematical errors and used flawed strategies. However, these problems are <i>partially</i> mitigated using the more advanced GPT-4 model and <i>entirely corrected</i> using simple prompting and calculator tool use patterns demonstrated herein.</p>","PeriodicalId":43,"journal":{"name":"Journal of Chemical Education","volume":"101 5","pages":"1782–1784"},"PeriodicalIF":2.9000,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comment on “Comparing the Performance of College Chemistry Students with ChatGPT for Calculations Involving Acids and Bases”\",\"authors\":\"Joshua Schrier*, \",\"doi\":\"10.1021/acs.jchemed.4c00058\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >In a recent paper in this <i>Journal</i> ( <cite><i>J. Chem. Educ.</i></cite> <span>2023</span>, <em>100</em>, 3934−3944), Clark et al. evaluated the performance of the GPT-3.5 large language model (LLM) on ten undergraduate pH calculation problems. They reported that GPT-3.5 gave especially poor results for salt and titration problems, returning the correct results only 10% and 0% of the time, respectively, and that, despite a correct application of heuristics, the LLM made mathematical errors and used flawed strategies. However, these problems are <i>partially</i> mitigated using the more advanced GPT-4 model and <i>entirely corrected</i> using simple prompting and calculator tool use patterns demonstrated herein.</p>\",\"PeriodicalId\":43,\"journal\":{\"name\":\"Journal of Chemical Education\",\"volume\":\"101 5\",\"pages\":\"1782–1784\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2024-04-11\",\"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.4c00058\",\"RegionNum\":3,\"RegionCategory\":\"教育学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Chemical Education","FirstCategoryId":"92","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acs.jchemed.4c00058","RegionNum":3,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Comment on “Comparing the Performance of College Chemistry Students with ChatGPT for Calculations Involving Acids and Bases”
In a recent paper in this Journal ( J. Chem. Educ.2023, 100, 3934−3944), Clark et al. evaluated the performance of the GPT-3.5 large language model (LLM) on ten undergraduate pH calculation problems. They reported that GPT-3.5 gave especially poor results for salt and titration problems, returning the correct results only 10% and 0% of the time, respectively, and that, despite a correct application of heuristics, the LLM made mathematical errors and used flawed strategies. However, these problems are partially mitigated using the more advanced GPT-4 model and entirely corrected using simple prompting and calculator tool use patterns demonstrated herein.
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.