In most academic writing programs worldwide, instruction aims to develop students' awareness of essay types, written language use, and test-taking strategies. However, teachers' instructional practice is often dictated by their knowledge base, perception, and the intuitions they have about language use (Borg, 2006). Such intuitions are not always correct (Cobb & Boulton, 2015) and may not fully reflect how language is used in a particular genre of academic writing by native speakers. Thus, the grammatical structures they teach may not correspond well to what is frequently used in that genre. On the part of students, because of their limited knowledge of writing conventions, they might end up using various grammatical forms while not considering how appropriate these are. Thus, it is imperative for writing teachers to allow for "data-driven learning" (Johns, 1991) whereby students explore language constructions through consulting a purpose-built corpus. Such a corpus exposes students to language features peculiar to a particular genre, but it can also help them identify which is frequently and appropriately used in the genre. In this presentation, we will describe how to identify frequently used complex sentence forms in a corpus of 162 IELTS essays (49,102 words) written by IELTS examiners and experts by using AntConc, a software created by Anthony (2019) for analyzing written corpora. We will then give some pedagogical suggestions for how to design and implement teaching material based on our findings as well as for how the findings can be practically applied in developing classroom activities.