Listening and Data-Driven Learning
摘要
Listening, the most used language skill in daily life, remains underrepresented in both instructed second language acquisition (ISLA) and data-driven learning (DDL) research. This entry explores how DDL can enhance listening instruction by granting learners access to spoken or multimodal corpora, enabling engagement with authentic language data. It distinguishes listening as oral comprehension from auditory-phonetic processing; examines challenges such as natural speech features, segmentation difficulties, and instructional limitations; and discusses strategies to facilitate listening instruction with corpora. Additionally, it highlights how multimodal corpora and tools like YouGlish and the TED Corpus Search Engine support listening development through pattern recognition and perceptual training. These corpora feature authentic language data, helping learners process connected speech, recognize discourse functions, and refine pronunciation, making learning more relevant and motivating. The discussion emphasizes the need for further research and corpus development, particularly for languages other than English, and for a more balanced integration of listening in DDL and L2 pedagogy.