Uncertainty is inherent to scientific methods and practices, yet is it rarely explicitly discussed in science classrooms. Ironically, science is often equated with "certainty" in these contexts. Uncertainties that arise in science deserve special attention, as they are increasingly a part of public discussions and are susceptible to manipulation. Clarifying what is meant by scientific uncertainty would include identifying sources of uncertainty in scientific practice, and would help provide an instructional framework for understanding how scientists use methods, data, and models to justify claims about the natural world. This research introduces both a general typology of scientific uncertainty informed by a review of literature from a variety of perspectives, and two additional typologies that emerged from qualitative studies examining student essays about scientific uncertainty in two disciplinary contexts: biological evolution and global climate change. These typologies aim to provide leverage for curricular discussions about scientific knowledge and practices, and to help instructors interested in integrating scientific uncertainty into teaching these subjects. In particular, a focus on uncertainties in data and models can illustrate their integral relationship and can spark critical discussions about methods used to collect empirical data and the models used to explain them and make predictions. This research builds a case for integrating scientific uncertainty into science teaching and emphasizing its importance for understanding the practice of science within particular disciplinary contexts. [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.]