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<p>The integration of artificial intelligence (AI) into second language (L2) writing calls for a deeper understanding of how learners’ AI literacy is associated with language production. Adopting a person-centered approach, this study identified latent AI literacy profiles among Chinese university students based on their conceptual understanding, application ability, ethical awareness, and AI-related self-efficacy. Using ten lexical, syntactic, and discourse-related complexity measures, we examined how these profiles differed in overall linguistic complexity and how genre-based writing tasks (narrative, persuasive, expository, and cause-and-effect) moderated these relationships. Results revealed four distinct AI literacy profiles that differed significantly across multiple linguistic complexity measures. Notably, the profile effects were task-sensitive: narrative writing was associated with reduced lexical diversity and a shifted word-frequency profile for mid-profile learners, persuasive writing highlighted greater nominal elaboration without parallel gains in cohesion-related measures, and expository writing was associated with greater clause-level elaboration and structural diversification for Profile 4. Methodologically, the study demonstrates the value of integrating person-centered profiling with multidimensional complexity measures to capture profile-based, genre-contingent heterogeneity in L2 writing under time pressure, offering a replicable framework for investigating learner differences in the AI era.</p>

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From prompts to profiles: how AI literacy profiles and genre-based writing tasks relate to linguistic complexity in L2 writing

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月17日

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  • Zhanhao Jiang,
  • Zhiyun Huang

摘要

The integration of artificial intelligence (AI) into second language (L2) writing calls for a deeper understanding of how learners’ AI literacy is associated with language production. Adopting a person-centered approach, this study identified latent AI literacy profiles among Chinese university students based on their conceptual understanding, application ability, ethical awareness, and AI-related self-efficacy. Using ten lexical, syntactic, and discourse-related complexity measures, we examined how these profiles differed in overall linguistic complexity and how genre-based writing tasks (narrative, persuasive, expository, and cause-and-effect) moderated these relationships. Results revealed four distinct AI literacy profiles that differed significantly across multiple linguistic complexity measures. Notably, the profile effects were task-sensitive: narrative writing was associated with reduced lexical diversity and a shifted word-frequency profile for mid-profile learners, persuasive writing highlighted greater nominal elaboration without parallel gains in cohesion-related measures, and expository writing was associated with greater clause-level elaboration and structural diversification for Profile 4. Methodologically, the study demonstrates the value of integrating person-centered profiling with multidimensional complexity measures to capture profile-based, genre-contingent heterogeneity in L2 writing under time pressure, offering a replicable framework for investigating learner differences in the AI era.