Fusing Corpus-Based Analysis with Content and Language Integrated Learning: Transforming Online Language Proficiency Development

The integration of corpus-based analysis with Content and Language Integrated Learning (CLIL) offers a promising pedagogical framework to enhance online language proficiency development. Against the backdrop of increasing globalization and the need for effective language and content instruction, this study investigates the potential of merging these two methodologies to address gaps in traditional language education. The objective is to explore how corpus-based tools can enhance CLIL curricula by providing authentic, subject-specific language inputs and fostering critical thinking, cultural awareness, and learner autonomy. A mixed-methods approach was adopted, combining quantitative and qualitative methods. Quantitative analysis involved pre-tests and post-tests of vocabulary acquisition, grammar accuracy, and subject-specific terminology comprehension for experimental and control groups. The experimental group utilized corpus-based CLIL tools, while the control group followed traditional CLIL methods. Qualitative data were gathered through surveys, interviews, and case studies to capture learner and educator experiences, engagement, and usability of the proposed approach. Findings revealed that the experimental group demonstrated significantly greater improvements in language proficiency, with 80%-100% gains across metrics compared to 30%-50% gains in the control group. Qualitative