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022 _a0021-9584
100 _aClark, Ted M.
245 _aComparing the Performance of College Chemistry Students with ChatGPT for Calculations Involving Acids and Bases
_b(Journal Article)
260 _aWashington DC
_b: American Chemical Society
_c, 2023
300 _a3934–3944p.
440 _aJournal of Chemical Society
_v, Volume 100: Number 10, October 2023
505 _a***______{For Hard Copy, Please visit Library.}________***
520 _aAbstract: Student performance on open-response calculations involving acid and base solutions before and after instruction in general chemistry and analytical chemistry courses was compared with the output from the artificial intelligence chatbot ChatGPT. Applying a theoretical model of expertise for problem solving that includes problem conceptualization, problem strategy, and solution, it is found that students errors following instruction primarily involved problem conceptualization and the misapplication of heuristics like the Henderson–Hasselbalch equation When the same problems were used as input to ChatGPT the responses were comparable to worked examples found in general chemistry textbooks in terms of length and detail and usually displayed strong problem conceptualization. Response accuracy of the chatbot varied greatly for different topics, being best for calculations of pH for a strong acid or strong base and much lower for more complex problems involving titrations or aqueous salts. Chatbot and student errors differed in that the chatbot did not misapply heuristics but did make mathematical errors uncommon for students. The variability in the correctness of ChatGPT’s responses and the nature of its errors vis-à-vis students will influence its potential use as an instructional resource for calculations involving acids and bases.
650 _aInternet/Web-Based Learning| Misconceptions| Problem-Solving| Decision Making| Testing| Assessment Acids/Bases| pH
700 _aAnderson, Ellie | Dickson-Karn, Nicole M. | Soltanirad, Comelia | Tafini, Nicolas
856 _uhttps://doi.org/10.1021/acs.jchemed.3c00500
942 _cPER
999 _c45338
_d45337