A Missed Opportunity for No-Code Chatbots? Current Challenges in Publicly Available Chemistry GPTs

With the emergence of generative artificial intelligence (GenAI) and ChatGPT, individualization of learning pathways was discussed in the educational context. One way to achieve customization is the use of specialized versions of ChatGPT–so-called GPTs. Those GPTs are publicly available and used daily by thousands of people worldwide. In this work, we analyze the current market of chemistry-specialized GPTs in the OpenAI GPT ‘store’. We identify common shortcomings, such as unnecessary activation of features like DALL-E, overly positive use of terms like ‘expert’ or ‘teacher’ and the inclusion of copyrighted material. To highlight the urgency of well-designed GPTs in chemistry education, we analyze the most used chemistry-specific GPT in more detail to discuss further problems with GPTs. In summary, we advocate a collaborative effort within the chemistry education community to develop robust and publicly available GPTs. Future research might benefit from a focus on creating and refining these GPTs and exploring their impact on learning in both secondary and tertiary educational settings.

Authors

Institutions

Publication Details

Journal
Journal of Chemical Education
Published
2025-04-19
DOI
https://doi.org/10.1021/acs.jchemed.4c01552
Citations
2
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
1.31
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Missed Opportunity for No-Code Chatbots? Current Challenges in Publicly Available Chemistry GPTs

Sebastian Tassoti, Martin Sigot
2 citations
Journal of Chemical Education
Artificial Intelligence in Healthcare and Education
1.31
article

A Missed Opportunity for No-Code Chatbots? Current Challenges in Publicly Available Chemistry GPTs

Sebastian Tassoti, Martin Sigot
article en
2 citations

Abstract

With the emergence of generative artificial intelligence (GenAI) and ChatGPT, individualization of learning pathways was discussed in the educational context. One way to achieve customization is the use of specialized versions of ChatGPT–so-called GPTs. Those GPTs are publicly available and used daily by thousands of people worldwide. In this work, we analyze the current market of chemistry-specialized GPTs in the OpenAI GPT ‘store’. We identify common shortcomings, such as unnecessary activation of features like DALL-E, overly positive use of terms like ‘expert’ or ‘teacher’ and the inclusion of copyrighted material. To highlight the urgency of well-designed GPTs in chemistry education, we analyze the most used chemistry-specific GPT in more detail to discuss further problems with GPTs. In summary, we advocate a collaborative effort within the chemistry education community to develop robust and publicly available GPTs. Future research might benefit from a focus on creating and refining these GPTs and exploring their impact on learning in both secondary and tertiary educational settings.

Journal of Chemical EducationVol. 102(5)
University of Graz (AT), Institute of Chemistry (CN)
Openalex Percentile: Top 17%
Artificial Intelligence in Healthcare and Education
1.31
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.