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Data coding is a critical aspect across all areas of second language acquisition research. Once data have been collected, it is the first major step in the measurement process. It involves organizing and classifying raw data into categories for the purpose of further analysis and interpretation. This chapter considers the concepts of validity and reliability in relation to coding, reviews the various steps involved in coding, and discusses strategies that can help to increase its validity and reliability. It focuses on relatively top‐down, theory‐ and instrument‐driven coding methods. There are two major threats that can jeopardize validity in coding: construct underrepresentation and construct‐irrelevant variance. One of the first decisions to be made is how much of the data will need to be coded. In some research, it may be necessary to code the entire dataset, but in other research, it may be …