Transforming postgraduate discourse studies through AI-enhanced Corpus-Based Language Pedagogy

This study examines the integration of AI-enhanced tools within a postgraduate discourse analysis course at a Taiwanese university. Specifically, it explores the effectiveness, student perceptions, and tool affordances in facilitating corpus-based inquiry and enhancing student engagement. Using a qualitative case study approach, the research investigates how students from diverse linguistic and cultural backgrounds employed tools such as Python scripts, Google Sheets API, NoCodeSerpAPI, Voyant Tools, and Notebook LM to collect and analyze digital discourse from sources including YouTube and Google News. Grounded in the principles of Corpus-Based Language Pedagogy (CBLP), students engaged in data-driven learning to explore linguistic patterns related to cultural dynamics, bias, and social issues. The findings reveal that AI-assisted tools supported analytical autonomy, improved data accessibility, and fostered critical digital fluency, while also posing interpretive challenges particularly in recognizing nuanced or context-sensitive meanings. Ultimately, the integration of AI within the CBLP framework proved pedagogically transformative, reshaping traditional corpus-based approaches and equipping students with the competencies to critically navigate language in an increasingly digital and multilingual world.