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<p>Recognizing the evolution of generative artificial intelligence (GenAI) from simple text-generation chatbots to sophisticated multimodal content-creation tools, this study examines the effectiveness of <i>Sora</i>, a multimodal GenAI software, in shaping students’ motivation, attitude, and interest in learning Chinese vocabulary. Drawing on proactive language learning theory, we employed a mixed-methods quasi-experimental design with 74 beginner-level New Zealand university students (Control Group/CG: <i>n</i> = 34; Experimental Group/EG: <i>n</i> = 40) over a six-week period. Data were collected through questionnaires, reflective journals, stimulated recall, and semi-structured interviews (<i>n</i> = 13). The MANCOVA and ANCOVA results indicated a significant difference between the EG and CG in learners’ post-test motivation and attitudes toward Chinese learning, though not in learning interest. By contrast, the qualitative findings demonstrated that the integration of <i>Sora</i> substantially shaped students’ learning attitudes, motivation, and interest, attributable to three primary affordances: (1) its immediacy and adaptability in creating multimodal learning artifacts; (2) its capacity to foster an enjoyable and engaging learning experience; and (3) its visualization functions that supported vocabulary comprehension and memorization through multimodal reinforcement. This paper highlights the pedagogical implications for integrating multimodal GenAI tools into L2 Chinese instruction.</p>

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Innovating Chinese Vocabulary Learning through Multimodal GenAI: The Motivational, Interest, and Attitudinal Shifts among CSL Learners

  • 期刊论文

  • 发表日期：

    2026年3月13日

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  • Xian Zhao,
  • Danping Wang,
  • Guangxiang Leon Liu

摘要

Recognizing the evolution of generative artificial intelligence (GenAI) from simple text-generation chatbots to sophisticated multimodal content-creation tools, this study examines the effectiveness of Sora, a multimodal GenAI software, in shaping students’ motivation, attitude, and interest in learning Chinese vocabulary. Drawing on proactive language learning theory, we employed a mixed-methods quasi-experimental design with 74 beginner-level New Zealand university students (Control Group/CG: n = 34; Experimental Group/EG: n = 40) over a six-week period. Data were collected through questionnaires, reflective journals, stimulated recall, and semi-structured interviews (n = 13). The MANCOVA and ANCOVA results indicated a significant difference between the EG and CG in learners’ post-test motivation and attitudes toward Chinese learning, though not in learning interest. By contrast, the qualitative findings demonstrated that the integration of Sora substantially shaped students’ learning attitudes, motivation, and interest, attributable to three primary affordances: (1) its immediacy and adaptability in creating multimodal learning artifacts; (2) its capacity to foster an enjoyable and engaging learning experience; and (3) its visualization functions that supported vocabulary comprehension and memorization through multimodal reinforcement. This paper highlights the pedagogical implications for integrating multimodal GenAI tools into L2 Chinese instruction.