Innovation in Language Learning
Approaches to Overcoming Learning Barriers in Chinese Formulaic Language: From Technical Empowerment to Emotional Support
Yinhui Bao, Xi’an Jiaotong-Liverpool University (China)
Abstract
Formulaic language (FL) not only marks native-like proficiency but also serves as a critical indicator of L2 fluency and idiomaticity, and remains a major challenge in L2 acquisition. Theoretically, this study critically reviews two main approaches to lexical conceptualization (item-based and relation-based perspectives) and three major paradigms of technology-assisted language learning (computer-assisted learning, data-driven learning, and generative AI). Drawing on the concept that different technologies offer distinct affordances (i.e., opportunities or potentials) for language learning, the study outlines the affordances of each technological paradigm and their alignment with the two perspectives on FL beyond single words. Empirically, the study adopts a rotational experimental design to investigate the differential effects of the three technology-enhanced modes on the acquisition of FL by beginner-level Chinese learners. A total of 60 beginner-level Chinese learners were recruited and randomly assigned to three experimental groups (n = 15 each) and one control group (n = 15). During a 12-week semester, the experimental groups received explicit instruction on FL through three sequential instructional modes, each lasting four weeks. All groups covered parallel instructional units during each phase. The control group received traditional implicit instruction on FL. Data was collected through immediate post-unit tests, delayed post-tests (measuring both receptive and productive knowledge), and questionnaires.
The findings reveal that the three technology-enhanced modes play complementary roles in FL acquisition: AI facilitates interactive learning and language production; the data-driven corpus method deepens understanding of collocational patterns; and computer-assisted multimedia instruction enhances learning motivation and language comprehension through multimodal input. Based on these results, the study proposes an empirically grounded framework for selecting instructional modes, recommending that teachers intelligently integrate multiple technological approaches according to specific instructional goals to achieve more effective teaching outcomes.
Keywords: Formulaic Language, Teaching Chinese as a Second Language, Technology-enhanced Learning
REFERENCES
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[3] Wray, A. Formulaic sequences in second language teaching: Principle and practice. Applied Linguistics, 2000, 21(4).
