Knowledge-producing practices in sciences and engineering increasingly use computational means for modeling and working with data. Despite consensus regarding the importance of computational thinking in science and engineering, scholars differ in conceptualization of the primary purposes and role of its integration in K-12 science (Kafai & Proctor, 2022; NRC, 2010). In this dissertation, I define computational thinking (CT) as using, constructing or assessing computational tools to understand or describe a phenomenon. In science education, CT practices range from coding and computational problem solving to utilizing or constructing simulations or models and data practices (Sengupta et al., 2013; Weintrop et al., 2016). Additionally, CT practices involve unplugged forms such as formulating rules for an imagined computational agent to execute (Yadav et al., 2014). Given that one of the primary objectives of recent science education reform is aligning science learning more closely with the practices of scientists (Penuel, 2016), it is not surprising that "using mathematics and computational thinking" was included among the eight science and engineering practices of the Framework for K12 Science Education (NRC, 2012) and recent standards documents, including the Next Generation Science Standards (NGSS) and the Pennsylvania Science, Technology & Engineering, Environmental Literacy & Sustainability (STEELS) Standards. However, standards document for what students should know and be able to do are relatively silent on pedagogy (Larkin, 2019). The need to articulate what it means to support students' ongoing changes in thinking through scientific practice has led to a robust literature on science teaching practices (Windschitl et al., 2020; Windschitl & Calabrese Barton, 2016; Thompson, et al., 2019) and preparing science teachers (Stroupe et al., 2020). For example, science education scholars have well-articulated teaching practices for supporting scientific modeling (e.g., Windschitl et al., 2020) and supporting students' argumentation (e.g., ZembalSaul et al., 2013). However, how and why to teach computational thinking practice in science remains an under-theorized area. Unlike other science and engineering practices, definitions of computational thinking have been unsettled. Many teachers feel uncertain about how to integrate computational thinking practices in science classrooms (Kang et al., 2018), since they themselves did not engage in these practices as students. Overall, existing studies of science teachers learning about CT practices demonstrate that teachers generally feel unprepared to incorporate computational thinking into their science classrooms (Haag & Megowan, 2015; Kang et al., 2018). The literature concerning science teacher education demonstrates that preservice teachers (PSTs) face similar challenges in integrating computational thinking in science. Even after substantial course emphasis on the integration of CT practices in science, PSTs continue to make superficial connections between components of CT and science curriculum (Walton et al., 2020) and they were largely unable to create curriculum materials that meaningfully integrated CT with disciplinary content (Mouza et al., 2017; Vasconcelos & Kim, 2020). Therefore, there is a growing need to support teachers and incoming teachers' computational thinking. In my dissertation, I tackle this issue through three studies designed to support preservice teachers' computational thinking as an epistemic practice. Competing conceptions of the role of computational thinking practices in science learning In order for teachers and preservice teachers to meaningfully integrate CT in science, a well articulated and epistemically-oriented rationale for the roles and purposes of computational thinking practices in science is necessary. [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.]