Data-driven learning is a critical pedagogical approach for using corpora in language teaching and learning. It gives direct access to the learners to access data. The learners can take part in building up their ‘own’ profiles of meaning and uses. Through Corpus-aided discovery learning (CADL), learners learn ‘how to learn?’ through observation, analysis, interpretation, and presentation of language use patterns in corpus data. Learning about language use is driven by a process of enquiry that works towards understanding (or) problem solving, and corpora are used as mediational tools (Vygotsky and Cole in Mind in society: Development of higher psychological processes. Harvard university press [1]). Students develop more autonomy when they receive guidance about ‘how to observe’ language and make generalizations. Rather than just reading and learning, these activities promote noticing and grammatical consciousness-raising, enhancing second language learning (SLL) and development (Schmidt in Appl Linguis 11:129–158 [2]). This study aims to understand how incorporating corpus linguistics tools and resources can enhance students’ grasp of academic discourses and language precision, which contributes to developing effective writing strategies among English as Second Language (ESL) learners. The research follows a mixed methods research design. The qualitative aspects involve analysing authentic academic texts and finding patterns, collocations, and lexical choices in academic writing. They are followed by quantitative assessments to measure the student’s academic writing skills, thus allowing a comprehensive evaluation of the effectiveness of the corpus-informed approach in academic writing.