This entry explores learner’s attitudes, preferences (or styles), strategies and behaviours in data-driven learning (DDL) and the interconnections between them. Attitudes, representing learners’ predispositions towards DDL, significantly influence their engagement and success. While many learners exhibit positive attitudes towards DDL, factors such as anxiety and scepticism also present challenges. Learning preferences, particularly the inductive-deductive spectrum, shape how students interact with corpus-based activities, yet this relationship is nuanced and influenced by task design. Learner strategies, including exploring, cross-checking and synthesizing, are essential for effectively navigating DDL, with their use often determined by both external factors and individual learner attributes. Behaviours, as the observable outcomes of these attitudes, preferences and strategies, provide crucial insights into how learners interact with DDL and its impact on language acquisition.