Data coding is a critical aspect across all areas of second language acquisition (SLA) 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. For some research, coding is quite straightforward and unambiguous. In other research, coding may be a more complex endeavor, constituting one of the most time-consuming activities in the research project. Regardless of the nature of classification, a central goal is to retain validity and reliability in the coding procedure. The aims of this chapter are to consider the concepts of validity and reliability in relation to coding, to review the various steps involved in coding, and to discuss strategies that can help to increase its validity and reliability. The focus here will be on relatively top-down, theory- and instrument-driven coding methods; qualitative coding, which emerges bottom-up from the data, is the topic of chapter 12.