This qualitative study examined the cognitive, behavioral, and emotional engagement of eight Chinese EFL undergraduates using generative AI for digital multimodal composing. Students employed various tools for seven goals, including text generation and translation, and applied four strategies to refine unsatisfactory outputs. Engagement was influenced by L2 proficiency, AI literacy, and contextual factors.
GoEast Mandarin explains the differences between three identically pronounced structural particles in Chinese. The particle 的 connects a modifier to a noun, 地 introduces a manner description before a verb, and 得 attaches a complement after a verb or adjective. The guide provides phrase-building patterns, omission rules, and practice exercises with answers.
A teacher shares a step-by-step approach to practicing the /ʒ/ sound in words like “casual” and “usually.” The method includes checking isolated words, shifting from voiceless /ʃ/ to its voiced counterpart, exaggerated articulation, and slowing down speech. For B2+ students, spelled pronunciation is used instead of IPA symbols.
The author identifies four obstacles preventing learners of Chinese from bypassing translation: insufficient knowledge, slow word retrieval, lack of meaning-focused practice, and low tolerance for ambiguity. Research shows even bilinguals activate both languages, so the goal is removing the native language as a mandatory step. Recommended strategies include word-guessing games, information gaps, and time-pressured tasks.