This entry explores various types of corpora used in data-driven learning (DDL). It categorises corpora based on size (macro- and micro-corpora), nature (written, spoken and multimodal) and thematic cohesion. The entry highlights the importance of representativeness and practical considerations in corpus design, particularly for educational purposes. The document also discusses the advantages of different corpus types and their applications in enhancing vocabulary, grammar and contextual language understanding. It underscores the flexibility and adaptability of DDL to meet diverse learner needs and teaching goals.