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<p>The role of generative artificial intelligence (GenAI) affordance in specific task teaching, particularly the continuation writing task, remains insufficiently theorized and empirically underexplored. To bridge this research gap, a repeated-measures intervention study was conducted within the framework of Dynamic Systems Theory (DST) to investigate the implementation of GenAI-assisted continuation task instruction and its associations with the development of English as a Foreign Language (EFL) students’ writing performance. Twenty-five Chinese EFL high school students participated in this 9-week intervention with five longitudinal measurement points. Five tasks were implemented at two-week intervals, eventually yielding 125 writing samples. Through generalized estimating equation (GEE) analysis, this study statistically identified the model effects. A significant main effect of Time was found, and the model estimates suggested a three-phase trajectory in writing performance during the GenAI-mediated instruction period. Furthermore, the nonlinear progressions of complexity, accuracy, and fluency (CAF) exhibited distinct patterns under this particular instructional condition. These findings document the patterns of writing development observable under GenAI-assisted instruction, suggest the role of GenAI affordance in continuation task teaching, and offer practical implications for optimizing GenAI-integrated L2 writing pedagogy.</p>

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Exploring GenAI affordance in EFL continuation task instruction for developing Chinese high school students’ writing complexity, accuracy and fluency

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月23日

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  • Yongliang Wang,
  • Han Shi

摘要

The role of generative artificial intelligence (GenAI) affordance in specific task teaching, particularly the continuation writing task, remains insufficiently theorized and empirically underexplored. To bridge this research gap, a repeated-measures intervention study was conducted within the framework of Dynamic Systems Theory (DST) to investigate the implementation of GenAI-assisted continuation task instruction and its associations with the development of English as a Foreign Language (EFL) students’ writing performance. Twenty-five Chinese EFL high school students participated in this 9-week intervention with five longitudinal measurement points. Five tasks were implemented at two-week intervals, eventually yielding 125 writing samples. Through generalized estimating equation (GEE) analysis, this study statistically identified the model effects. A significant main effect of Time was found, and the model estimates suggested a three-phase trajectory in writing performance during the GenAI-mediated instruction period. Furthermore, the nonlinear progressions of complexity, accuracy, and fluency (CAF) exhibited distinct patterns under this particular instructional condition. These findings document the patterns of writing development observable under GenAI-assisted instruction, suggest the role of GenAI affordance in continuation task teaching, and offer practical implications for optimizing GenAI-integrated L2 writing pedagogy.