As science becomes increasingly computationally intensive, the need for computational thinking (CT) and computer science (CS) practices in K-12 science education is becoming paramount. Incorporation of CT/CS practices in K-12 education can be seen in national standards and a variety of allied initiatives. One way to build capacity around an emerging educational practice is for a team of researchers to partner with a local school or district in a Research-Practice Partnership (RPP). Over the past four years, our team has worked with a local middle school via a RPP to help support a school-wide STEM ecosystem that aimed to integrate computational thinking concepts throughout all elements of the school day (core curricula, electives, after school activities, etc.). Throughout this partnership, we have worked closely with science teachers to develop and implement computational modeling units that aim to develop both computational thinking skills and scientific knowledge. This research considers the far-reaching impacts of this RPP by examining science teachers' infusion of CT/CS into their science curricula, the development of a scientific computational modeling unit, and students' understanding of both metamodeling and scientific concepts after participating in the implementation of the computational modeling unit. The first paper in this dissertation is written for a practitioner journal. It discusses how the COVID-19 pandemic led to the rapid revision of a previously utilized disease transmission modeling unit in order to reflect the current scientific consensus regarding the behavior of the coronavirus. The paper details what a middle school science computational modeling unit about COVID-19 using the Use-Modify-Create (UMC) instructional strategy looks like in the classroom, and how the pandemic may have impacted student understanding of disease transmission through the use of computational modeling. This work demonstrates the efficacy of engaging in agile curricular revision and instruction to capture salient, emerging real-world events that can help contextualize student learning around what might otherwise be experienced as abstract science concepts. The second study is a qualitative study that utilizes a combination of modeling theoretical frameworks to investigate eighth grade science students' understanding of the nature, purpose, and revisability of the same computational model depicting the spread of COVID-19. Student exit-ticket responses, student interviews, and multiple-choice responses were analyzed to determine students' levels of understanding of metamodeling concepts. This work also compares student descriptions of what they learned using the computational model to student responses from before the pandemic, when students used a more generalized epidemics modeling unit. The results suggest that the unique context of engaging students in SSI-centered scientific modeling that is directly related to a natural phenomenon that they are directly experiencing could increase their level of understanding of metamodeling components, and even add additional complexities to their comprehension rooted in the socio-scientific nature of the content and context. The third paper is a case study that examines the attitudes, beliefs, and experiences of seven middle school science teachers at the magnet middle school engaged in the CT-focused RPP. Through the analysis of semi-structured interviews, a CT self-efficacy survey, and lesson plans, themes regarding the relationship between the variables being studied are presented. [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://bibliotheek.ehb.be:2222/en-US/products/dissertations/individuals.shtml.]