TEACHING ENGLISH COLLOCATIONS USING CORPUS TOOLS THROUGH AI
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This study examines how corpus tools, when combined with artificial intelligence (AI)-enhanced features, can improve the teaching and learning of English collocations in EFL/ESL settings. Drawing on data from previous empirical research—including quasi experimental studies comparing corpus based/data driven learning (DDL) with traditional methods—this paper analyses outcomes in recognition, production, retention, and learner attitudes. Results show that corpus based instruction, especially when AI assisted (for example, in automatic collocation extraction, contextual feedback, or adaptive tasks), leads to significantly higher gains in collocation production and recognition compared to control groups taught by traditional methods. Learners also report positive attitudes toward corpus tools, citing increased awareness of natural usage, greater autonomy, and improvement in writing accuracy. A comparative table is provided to illustrate effect sizes from selected studies. The paper concludes with pedagogical implications for integrating corpus tools with AI features, and recommendations for teacher training and classroom implementation
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