A fundamental component of research on learning is understanding processes of performance. One typical method of studying how and why people perform in particular ways is to record audio or video of those processes. Research methodologies that rely on audio or video data start with recording phenomena (events) researchers are interested in. After recording audio or video data of an event, researchers often transcribe their data. Next, the transcription is annotated or coded. Afterward, the annotated transcript is then further analyzed or modeled in some way, and finally, conclusions or inferences are made based on that model. Unfortunately, as with all human endeavors, analytic methods such as transcription are imperfect, and errors and inconsistencies can erode the validity of the conclusions they produce. This dissertation focuses on the reliability and validity of transcription and coding and ways of assessing their sensitivity to error. Specifically, it will introduce a novel transcription error sensitivity analysis test that measures the impact transcription error has on subsequent coding. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]