[UPCOMING] AI-Powered Academic Research: From Literature Review to Data-Driven Writing

Course introduction

This LexData course introduces a practical workflow for AI-assisted academic research. Participants will learn how to use modern AI tools responsibly and effectively across the research process, from topic development and literature review to data preparation, analysis planning, academic writing, and presentation. The course is designed for students, early-career researchers, teachers, and professionals who want to improve their research productivity without losing academic rigor. Instead of treating AI as a shortcut, the course shows how AI can support structured thinking, better organization, clearer writing, and more transparent research workflows. What you will learn: 1. How to use AI tools for research topic development Participants will learn how to turn a broad idea into focused research questions, identify possible research gaps, and refine academic arguments. 2. How to organize literature review work The course demonstrates how to summarize sources, compare studies, build thematic categories, and prepare a literature review structure. 3. How to support corpus and data-driven research Participants will learn how AI can assist with data cleaning, text organization, coding preparation, keyword extraction, and basic corpus-based interpretation. 4. How to improve academic writing The course introduces practical strategies for improving clarity, coherence, paragraph structure, academic tone, and argument flow. 5. How to use AI responsibly Participants will learn the limits of AI tools, how to avoid over-reliance, how to check outputs critically, and how to maintain academic integrity. 6. How to build a personal research workflow By the end of the course, participants will be able to create their own AI-supported workflow for reading, note-taking, drafting, revising, and presenting research. Who this course is for: - Undergraduate and postgraduate students - PhD candidates - Early-career researchers - University teachers - Language and translation researchers - Social science researchers - Anyone interested in AI-supported academic work Course outcome: By the end of the course, participants will have a practical framework for using AI tools to support academic research, literature review, data work, and writing. They will also understand how to use AI critically, ethically, and productively in real research contexts.