Integration of Artificial Intelligence to Strengthen Critical Thinking in Teacher Training
Keywords:
Higher education; English teaching; artificial intelligence; critical thinkingAbstract
Critical thinking is fundamental to higher education, empowering future educators to critically analyze and reflect upon the complex socio-cultural settings that shape their professional practice. However, limited empirical evidence explains how generative AI-supported pedagogical resources contribute to critical thinking development in English as a foreign language (EFL) teacher training, particularly in Latin American higher education contexts. In this context, the purpose of the present research was to determine the impact of generative artificial intelligence (AI) on the development of critical thinking in 163 final-year students of a teaching English as a foreign language program at a private university in Ecuador. A mixed-methods, quasi-experimental approach was used, employing diagnostic and perception questionnaires, pre-tests, post-tests, and a semi-structured interview. A 14-week pedagogical intervention was conducted, integrating AI-supported teaching resources such as ChatGPT, Canva, Copilot, Gemini, Invideo, and Leonardo AI. Simultaneously, activities involving the critical and reflective analysis of texts related to current social issues were developed. The findings indicate that integrating generative AI enhances the critical and reflective competencies of pre-service English teachers, particularly in discourse analysis, sociocultural awareness, and facilitating discussions on socially significant issues. This study concludes that, when pedagogically guided, generative AI can strengthen critical thinking in EFL teacher training by supporting discourse analysis, reflective inquiry, and the interpretation of social matters. Its contribution lies in demonstrating that multiple AI-generated resources can serve as pedagogical supports to strengthen analytical and reflective competencies in EFL teacher training.
https://doi.org/10.26803/ijlter.25.7.24
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