ChatGPT Leads the Pack: AI Language Models Elevating Chemistry Educationby@textmodels

ChatGPT Leads the Pack: AI Language Models Elevating Chemistry Education

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In evaluating AI language models for chemistry education, ChatGPT outshines Bing Chat, Bard, and Claude, displaying superior contextual comprehension. These GenAIbots promote critical thinking, problem-solving, creativity, and collaboration, aligning with Papert's Constructionism and enhancing student learning in chemistry and beyond.
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(1) Renato P. dos Santos, CIAGE – Centre for Generative Artificial Intelligence in Cognition and Education.

Abstract and Introduction

Materials And Methods

Results and Analyses

Prompts and generated texts

Conceptualizing chemical reactions

Deepening on understanding of chemical reactions

Question about combustion

Question about a graph of gases turning into water over time

Question about the difference between atoms, molecules, and moles

Deepening on the concept of mole

Question about changing of state

Question about an animated representation of water molecules undergoing phase changes

Question about plasma, a state of matter

Question about chemical bondings

Question about illustration of chemical bonds

Question about the essence of the type of chemical bonding

Further analysis


Limitations of the study and possible future studies

Author Contributions, Conflicts of interest, Acknowledgements, and References


In our study evaluating the proficiency of four AI language models—ChatGPT, Bing Chat, Bard, and Claude—in elucidating chemistry concepts, ChatGPT stood out, decisively surpassing Bing Chat's performance. Bard and Claude trailed closely, with all three showcasing a more in- depth, precise, and nuanced understanding, underscoring ChatGPT's adeptness at contextual comprehension.

Our findings highlight the robustness of GenAIbots like ChatGPT, Bing Chat, Bard, and Claude as agents-to-think-with in Chemistry education. These AI models seem suitable to offer interactivity, customisation, and multidisciplinary knowledge and promote critical thinking, problem-solving, creativity, and collaboration. They facilitate dynamic conversations and tailored content in Chemistry and potentially other domains.

Engaging with GenAIbots might enhance critical thinking, problem-solving, and creativity, fostering collaborative discussions and projects in group settings and deepening understanding of the topics. By integrating GenAIbots into Chemistry education, we're aligning with the principles of Papert's Constructionism. This theory posits that learning is most effective when students actively construct knowledge by creating tangible representations in meaningful contexts. This approach encourages students to engage deeply, fostering their problem-solving, critical thinking, and creative skills.

This paper is available on arxiv under CC BY-SA 4.0 DEED license.