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<p>Artificial intelligence (AI), especially Generative AI (GenAI), has been integrated into language learning in higher education. However, learners’ intentions to adopt AI tools remain uneven and context-dependent, especially in non-Western educational settings. This study utilized the Diffusion of Innovation (DOI) theory to investigate Vietnamese students’ perceptions of using AI-powered tools in their language learning. Survey data from approximately 800 language major students were analysed using the fuzzy set qualitative comparative analysis (fsQCA) method. The findings revealed that multiple configurations of DOI led to university language students’ intention to adopt AI with observability emerging as a core condition. Relative advantage and trialability also played central roles in several configurations, indicating their importance in shaping adoption. The study extends DOI through a configurational perspective and demonstrates the value of fsQCA in examining complex adoption behaviour. The study also offers practical implications for language educators and practitioners implementing AI-supported language learning in Vietnam.</p>

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Explaining AI adoption in language learning through configurational insights in the Vietnamese context

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月23日

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  • Thach Ngoc Pham,
  • Phuong Lai Hoai,
  • Thu Xuan Dang

摘要

Artificial intelligence (AI), especially Generative AI (GenAI), has been integrated into language learning in higher education. However, learners’ intentions to adopt AI tools remain uneven and context-dependent, especially in non-Western educational settings. This study utilized the Diffusion of Innovation (DOI) theory to investigate Vietnamese students’ perceptions of using AI-powered tools in their language learning. Survey data from approximately 800 language major students were analysed using the fuzzy set qualitative comparative analysis (fsQCA) method. The findings revealed that multiple configurations of DOI led to university language students’ intention to adopt AI with observability emerging as a core condition. Relative advantage and trialability also played central roles in several configurations, indicating their importance in shaping adoption. The study extends DOI through a configurational perspective and demonstrates the value of fsQCA in examining complex adoption behaviour. The study also offers practical implications for language educators and practitioners implementing AI-supported language learning in Vietnam.