In this chapter, we describe several intelligent tutoring systems (ITSs) designed to support student literacy through reading comprehension and writing instruction and practice. Although adaptive instruction can be a powerful tool in the literacy domain, developing these technologies poses significant challenges. For example, evaluating the quality of a student's writing can be challenging because of the numerous ways to succeed (or fail) when generating a written work. Throughout our discussion, we focus on the methodologies that ITSs have employed to face these challenges. Natural language processing techniques, for example, can be leveraged to assess students' level of comprehension or writing proficiency and subsequently drive the feedback that students receive. Additional challenges arise in the implementation of these systems in classrooms; we discuss how the features and flexibility offered by ITSs can augment their usefulness in these real-world settings. We conclude the chapter by forecasting how future generations of ITSs for literacy will improve and fit into the educational landscape. [At time of submission to ERIC this chapter was in press with R. Atkinson (Ed.), "Intelligent Tutoring Systems: Structure, Applications and Challenges." Hauppauge, NY: Nova Science Publishers Inc.]