A bite of China’s language: a case study of data-driven learning of food-related metaphors

Abstract The post-pandemic shift in education has accelerated the integration of digital tools and the emphasis on learner autonomy, creating promising ground for data-driven learning (DDL) to advance language education in the Education 4.0 era. Despite decades of development in corpus-based language pedagogy, its application in Chinese as a second language (CSL) remains limited. The present study empirically explores the feasibility and pedagogical potential of DDL in a transdisciplinary CSL context, focusing on the development of metaphor awareness. Five L2 Chinese learners of varying proficiencies engaged in a self-directed corpus consultation task designed to elicit students’ discoveries of food-related metaphors. Drawing on students’ written assignments, final projects, and post-course interviews, the study employed thematic analysis to trace their learning processes, learning outcomes, cognitive strategies, and attitudinal responses. Findings reveal that learners autonomously utilized a range of cognitive and metacognitive skills, such as induction, hypothesizing, categorization, reasoning, and verification, to uncover metaphorical senses and form–meaning mappings. Participants reported tangible gains in lexical knowledge, metaphor awareness, inferencing skills, and cross-cultural understanding, alongside positive attitudes toward the autonomy and novelty of corpus-based inquiry. The study suggests promising directions for integrating corpus-based pedagogy into the Education 4.0 landscape of autonomous and digitally mediated learning.