In this primer we briefly describe our perspective and experience in using data logging to support measurement of student learning in a game testbed ("Save Patch") we developed for research purposes. The goal of data logging is to support the derivation of cognitively meaningful measures and affectively meaningful measures from a combination of player behaviors, game events, and game states. Key best practices we have developed are to record data that reflects behavior rather than inferences about the behavior, specify the behavior to log ahead of time, log in-game behaviors that map directly to targeted knowledge, skills, and attitudes, encode sufficient information so that the data elements are unambiguous at the desired grain size, capture context to allowing linking of the data element to an individual's specific game experience (e.g., school, teacher, period, stage, level, game event, game state), and use a structured and delimited record format. The capturing of behavioral events that presumably is a manifestation of cognitive and affective processes allows for the investigation of numerous research questions that connect game play to students' background, strategy use, knowledge, and cognitive processes. Appended are: (1) Brief Summary of Save Patch; and (2) Data Code Definition for Save Patch. (Contains 5 tables and 3 footnotes.) [This paper was supported under the Educational Research and Development Centers Program.]