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<p>While numerous studies have emphasized the risks and challenges in integrating AI into higher education, relatively few studies have considered students’ awareness of such risks. What is even more lacking is empirical evidence of students’ awareness of the risks specifically related to their learning. This article reports a mixed-method study to survey the level of risk awareness among a sample of 977 Chinese tertiary learners, assessed the relationship between risk awareness and the intention to continue using AI, and uncover the factors that propel their continuance intention. The article first reported the creation and validation of a two-factor questionnaire of risk awareness: risk of overreliance (RO) and risk of losing teacher feedback (RLTF). Structural equation modelling showed that RO negatively predicted attitude toward AI but positively predicted continuance intention. RLTF positively predicted attitude toward AI but did not significantly predict continuance intention. Interviews suggest that students may deliberately ignore the potential risks in pursuit of course grades and in face of heavy academic work. They believed that the risks were under their control. Implications for AI integration are discussed.</p>

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Is it drinking poison to quench thirst? Learners’ risk awareness and continuance intention to use GAI in L2 writing

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月12日

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  • Beibei Kong,
  • Elanttamil Maruthai

摘要

While numerous studies have emphasized the risks and challenges in integrating AI into higher education, relatively few studies have considered students’ awareness of such risks. What is even more lacking is empirical evidence of students’ awareness of the risks specifically related to their learning. This article reports a mixed-method study to survey the level of risk awareness among a sample of 977 Chinese tertiary learners, assessed the relationship between risk awareness and the intention to continue using AI, and uncover the factors that propel their continuance intention. The article first reported the creation and validation of a two-factor questionnaire of risk awareness: risk of overreliance (RO) and risk of losing teacher feedback (RLTF). Structural equation modelling showed that RO negatively predicted attitude toward AI but positively predicted continuance intention. RLTF positively predicted attitude toward AI but did not significantly predict continuance intention. Interviews suggest that students may deliberately ignore the potential risks in pursuit of course grades and in face of heavy academic work. They believed that the risks were under their control. Implications for AI integration are discussed.