Choosing the Right Research Method for My AI-Based NLI Study
Introduction
Research method selection constitutes a pivotal decision in academic inquiry: it structures how evidence is gathered, the standards by which results are evaluated, and the extent to which conclusions can be generalized and replicated. In the context of my MSc. project, I investigate Native Language Identification (NLI) within user-generated English text by developing a bias-aware, generalizable framework that integrates Large Language Model (LLM) embeddings, topic debiasing, and open-set recognition. This post articulates the justification for adopting a quantitative experimental–comparative design and explains how this approach enables systematic assessment and evaluation of project outcomes including model accuracy, fairness, and robustness.
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