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This study investigates how Artificial Intelligence (AI), particularly ChatGPT, can be integrated into the development of Critical and Creative Thinking (CCT) in problem-solving activities. The research was carried out in a 12th grade class, covering the subjects of Portuguese, Geography and Psychology, where the CRAIL Model (Critical, Creativity, AI, Learning) was implemented, structured in stages and roles for ChatGPT, from Mentor (providing feedback) to Simulator (evaluating solutions in realistic scenarios). Data collection, of a qualitative nature, took place through portfolios and research diary entries. The results suggest that ChatGPT stimulates and improves students’ CCT, specifically their ability to interpret, when they already have solid prior knowledge; however, it is less effective at supporting the acquisition of entirely new concepts, pointing to the need for complementary instructional strategies. Although some students showed resistance to learning strategies for interacting with ChatGPT, the majority showed improvements in writing prompts and some capabilities in using question categories when interacting with ChatGPT. These findings corroborate previous studies that point out both the potential and limitations of Large Language Models in education. By elucidating the conditions in which ChatGPT adds value to the learning process—notably by offering feedback based on already consolidated knowledge—this work contributes to the debate on the convergence between teaching practices and AI tools, with a view to strengthening CCT.

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The Integration of Generative Artificial Intelligence and Critical and Creative Thinking in a Learning Model

  • 会议论文

  • 发表日期：

    2026年

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  • R. S. Paiva,
  • A. P. Costa,
  • L. P. Reis,
  • F. Rocha Lourenço,
  • M. Pino-Juste

摘要

This study investigates how Artificial Intelligence (AI), particularly ChatGPT, can be integrated into the development of Critical and Creative Thinking (CCT) in problem-solving activities. The research was carried out in a 12th grade class, covering the subjects of Portuguese, Geography and Psychology, where the CRAIL Model (Critical, Creativity, AI, Learning) was implemented, structured in stages and roles for ChatGPT, from Mentor (providing feedback) to Simulator (evaluating solutions in realistic scenarios). Data collection, of a qualitative nature, took place through portfolios and research diary entries. The results suggest that ChatGPT stimulates and improves students’ CCT, specifically their ability to interpret, when they already have solid prior knowledge; however, it is less effective at supporting the acquisition of entirely new concepts, pointing to the need for complementary instructional strategies. Although some students showed resistance to learning strategies for interacting with ChatGPT, the majority showed improvements in writing prompts and some capabilities in using question categories when interacting with ChatGPT. These findings corroborate previous studies that point out both the potential and limitations of Large Language Models in education. By elucidating the conditions in which ChatGPT adds value to the learning process—notably by offering feedback based on already consolidated knowledge—this work contributes to the debate on the convergence between teaching practices and AI tools, with a view to strengthening CCT.