There exists a significant disconnect between linguistic research and pedagogical practice in the Persian classroom. Although theoretical and computational studies of Persian have made substantial advances in recent years in understanding the linguistic patterns of Persian, identifying the characteristics of Persian language learners, and developing the Artificial Intelligence tools for studying authentic Persian language material, these insights have not been integrated within the language teaching curriculum. This chapter introduces Data-Driven Pedagogical Linguistics (DDPL), a collaborative program of practice for the Persian language, which advocates for the integration of linguistic theory, formal language acquisition research, and Artificial Intelligence-driven approaches within the Persian language teaching curriculum.

By focusing on Persian compound verbs as a practical case study, the chapter highlights how research insights and computational approaches can inform language pedagogy, by enabling learners to better understand language patterns and related nuances in meaning that are not typically explained in traditional grammars or taught in language textbooks and utilizing technology to further increase the learners’ exposure to authentic material. DDPL is a collaborative and multidisciplinary practice that establishes a cohesive, linguistically-informed, and student-centered language teaching methodology for the Persian language.