Coding qualitative data: A practical and conceptual guide for bachelor-level research

Coding is often introduced as the act of attaching labels to passages of qualitative material. That description is useful, but incomplete. Coding is also an interpretive practice through which a researcher decides what is analytically relevant, compares instances, develops concepts, and builds an argument. This guide introduces bachelor-level students to the basic language and practice of coding interviews, observations, documents, and open-text responses. It distinguishes codes, categories, themes, memos, and codebooks; explains inductive, deductive, and abductive logics; and presents an eight-step workflow from research question to written analysis. It also clarifies that open, axial, and selective coding are associated mainly with particular grounded theory traditions rather than a universal sequence for all qualitative studies. A worked example from fashion consumption shows how short data extracts can be coded at semantic and interpretive levels and developed into defensible themes. The final sections address quality, team coding, responsible use of generative artificial intelligence, method reporting, and a student exercise. The central claim is straightforward: software and procedures may support analysis, but the researcher remains responsible for every conceptual and ethical decision.