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<p>Improving EFL students’ impromptu speaking ability is a challenge for English language instruction. The development of AI technology has brought new opportunities for impromptu speaking instruction. Therefore, this study proposes an AI-supported interleaved training strategy that focuses on the effects on students’ impromptu speaking performance, learning engagement, technology acceptance, and epistemic network structure. A quasi-experimental study was conducted at a university in southern China to assess the effectiveness of this strategy. The experimental group (EG, <i>N</i> = 26) used the AI-supported interleaved training strategy, whereas the control group (CG, <i>N</i> = 26) used the Teacher-supported interleaved training strategy. The results of the study showed that students in EG not only improved their impromptu speaking performance but also improved their learning engagement. The results also found that students’ learning engagement could effectively predict impromptu speaking performance, while technology acceptance could produce a mediating effect on impromptu speaking performance. Meanwhile, the results of the ENA indicated that the connection relation in the epistemic network of EG was better than that of CG overall. This result illustrates the effectiveness of AI technology in aiding impromptu speaking instruction.</p>

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An Empirical Study of AI-Supported Interleaved Training Strategy to Improve EFL Students’ English Impromptu Speaking Performance, Learning Engagement, Technology Acceptance and Epistemic Network Structure

  • 期刊论文

  • 发表日期：

    2025年1月5日

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  • Gang Yang,
  • Yali Wang,
  • Youyou Zhang,
  • Manna Yang,
  • Qunfang Zeng,
  • Zhanmei Song

摘要

Improving EFL students’ impromptu speaking ability is a challenge for English language instruction. The development of AI technology has brought new opportunities for impromptu speaking instruction. Therefore, this study proposes an AI-supported interleaved training strategy that focuses on the effects on students’ impromptu speaking performance, learning engagement, technology acceptance, and epistemic network structure. A quasi-experimental study was conducted at a university in southern China to assess the effectiveness of this strategy. The experimental group (EG, N = 26) used the AI-supported interleaved training strategy, whereas the control group (CG, N = 26) used the Teacher-supported interleaved training strategy. The results of the study showed that students in EG not only improved their impromptu speaking performance but also improved their learning engagement. The results also found that students’ learning engagement could effectively predict impromptu speaking performance, while technology acceptance could produce a mediating effect on impromptu speaking performance. Meanwhile, the results of the ENA indicated that the connection relation in the epistemic network of EG was better than that of CG overall. This result illustrates the effectiveness of AI technology in aiding impromptu speaking instruction.