From prompt engineering to modeling: secondary science teachers' use of generative AI to engineer sweetener molecules.

Yun M, Crippen KJ, Xie C, Bulseco D

DOI: 10.1039/d6rp00064a
Published: 2026 Jul 17
Container: Chemistry education research and practice : CERP
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1039/d6rp00064a,
  title = {From prompt engineering to modeling: secondary science teachers' use of generative AI to engineer sweetener molecules.},
  author = {Yun M and Crippen KJ and Xie C and Bulseco D},
  year = {2026},
  journal = {Chemistry education research and practice : CERP},
  doi = {10.1039/d6rp00064a},
  url = {https://doi.org/10.1039/d6rp00064a}
}

RIS

TY  - JOUR
TI  - From prompt engineering to modeling: secondary science teachers' use of generative AI to engineer sweetener molecules.
AU  - Yun M
AU  - Crippen KJ
AU  - Xie C
AU  - Bulseco D
PY  - 2026
JO  - Chemistry education research and practice : CERP
DO  - 10.1039/d6rp00064a
UR  - https://doi.org/10.1039/d6rp00064a
ER  -

APA

M, Y., KJ, C., C, X., & D, B. (2026). From prompt engineering to modeling: secondary science teachers' use of generative AI to engineer sweetener molecules.. Chemistry education research and practice : CERP. https://doi.org/10.1039/d6rp00064a

Source records

pubmed · retrieved 2026-09-25T02:18:06.215Z