启发式
简单(哲学)
计算器
计算机科学
数学教育
滴定法
化学
管理科学
数学
物理化学
工程类
认识论
哲学
操作系统
标识
DOI:10.1021/acs.jchemed.4c00058
摘要
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.
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