Generative AI for Creative Content Generation in Hindi and Urdu Language Teaching: A Pilot Study

Abstract

This review paper investigates the role of generative artificial intelligence (AI) in the creative content development process for teaching Hindi and Urdu languages. With the rapid evolution of large language models (LLMs) such as GPT, BERT, and their Indic variants, there is growing interest in leveraging AI to enhance the quality, accessibility, and engagement levels in language education. The study explores how generative AI can support teachers and learners by automatically generating stories, poems, dialogues, vocabulary exercises, and grammar correction tasks tailored to the linguistic and cultural context of Hindi and Urdu. Through an in-depth literature review and a pilot study, this paper evaluates the effectiveness of AI-generated content in enhancing students' reading, writing, and conversational skills. It also examines the challenges of adapting LLMs for low-resource languages, particularly issues related to script rendering (Devanagari and Nastaliq), dialectal diversity, cultural accuracy, and pedagogical integration. The findings indicate that generative AI offers a promising supplementary tool in multilingual classrooms, encouraging student creativity and interactive learning. However, careful implementation strategies are required to address its limitations, ensure cultural relevance, and prevent over-reliance on technology in educational settings. This paper concludes with a discussion on future directions for research and practical recommendations for educators and policymakers.