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Enhancing Chemistry Learning with ChatGPT and Bing Chat as Agents-to-Think-With: A Comparative Case Study

Date
Publisher
arXiv
This study explores the potential of Generative AI chatbots (GenAIbots) such as ChatGPT and Bing Chat, in Chemistry education, within a constructionist theoretical framework. A single-case study methodology was used to analyse extensive interaction logs between students and both AI systems in simulated Chemistry learning experiences. The results highlight the ability of ChatGPT and Bing Chat to act as 'agents-to-think-with', fostering critical thinking, problem-solving, concept comprehension, creativity, and personalised learning experiences. By employing a Socratic-like questioning approach, GenAIbots nurture students' curiosity and promote active learning. The study emphasises the significance of prompt crafting, a technique to elicit desired responses from GenAIbots, fostering iterative reflections and interactions. It underlines the need for comprehensive educator training to effectively integrate these tools into classrooms. The study concludes that while ChatGPT and Bing Chat as agents-to-think-with offer promising avenues to revolutionise STEM education through a constructionist lens, fostering a more interactive, inclusive learning environment and promoting deeper comprehension and critical thinking in students across diverse Chemistry topics, ChatGPT consistently outperformed Bing Chat, providing more comprehensive, detailed, and accurate responses and skillfully addressing nuances and context.
Study at a glance
  • Question: How effectively can ChatGPT and Bing Chat enhance chemistry learning when used as conversational agents-to-think-with?
  • Setting and data: Simulated interactions by a Brazilian university STEM teacher roleplaying as a student, May 2023, two chat sessions.
  • Method: Exploratory holistic single-case study and content analysis of interaction logs and reflective journals
Why it matters

High failure rates and low achievement among chemistry students are significant concerns, driven by abstract concepts, misconceptions, and complex technical language.

Key findings
  • ChatGPT consistently outperformed Bing Chat by providing more comprehensive, accurate, and detailed responses that addressed nuances and context.
  • ChatGPT offered relatable analogies and everyday examples to explain chemical reactions and states of matter, whereas Bing Chat provided shorter, more technical answers.
  • Both chatbots successfully adopted Socratic-like questioning and positive reinforcement, helping to connect existing knowledge to new scientific concepts.

Summary drafted with AI from the full paper and may contain errors. See the full paper for details.

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