In contextualized instruction, the critical features of a context are considered important for the acquisition and transfer of a skill. Examples of contextualized instruction programs are Functional Context Education (FCE) and Anchored Instruction (AI). FCE involves the teaching of reading and mathematics skills in contexts that are relevant to the learner. AI is called "anchored instruction" because the practice of target skills is anchored to a specific context in which students use target skills in order to solve a series of problems. One of the primary goals of contextualized instruction is to increase the likelihood that what is taught in the training or classroom setting will be used in future applicable settings. Behavior analysts have developed a detailed technology to promote such transfer. Transfer requires that relevant behaviors be taught in relevant contexts. Relevant contexts are characterized by the critical features of target settings. A number of tactics have been developed to introduce and highlight critical features. These include introducing maintaining contingencies, using common stimuli, using sufficient exemplars, training loosely, and promoting precision. In this document, each of the techniques is described in detail. Conditions promoting errors in transfer settings and the development of error patterns are also described. Concluding discussion takes up the issue of whether relevant behaviors are being taught in relevant contexts by FCE and AI. (RH)