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Despite the elevated importance of Data Science in Statistics, there exists limited research investigating how students learn the computing concepts and skills necessary for carrying out data science tasks. Computer Science educators have investigated how students debug their own code and how students reason through foreign code. While these studies illuminate different aspects of students’ programming behavior or conceptual understanding, a method has yet to be employed that can shed light on students’ learning processes. This type of inquiry necessitates qualitative methods, which allow for a holistic description of the skills a student uses throughout the computing code they produce, the organization of these descriptions into themes, and a comparison of the emergent themes across students or across time. In this article we share how to conceptualize and carry out the qualitative coding process with students’ computing code. Drawing on the Block Model to frame our analysis, we explore two types of research questions which could be posed about students’ learning. Supplementary materials for this article are available online. 

Exposure to science, technology, engineering, and mathematics (STEM) at a young age is key to inspiring students to pursue careers in these fields. Thus, many institutions of higher education offer events to engage youth in STEM activities. These events are most effective when they are adapted to the specific audience. In Montana, a large percentage of the K-12 student population is from rural communities, where the ability to participate in such events is limited due to travel logistics and a shortage of relatable materials. We have developed a computer science outreach module that targets these populations through the use of storytelling and the Alice programming environment, thus drawing a parallel between storytelling and building algorithms. We describe the module's implementation, report and analyze feedback, and provide lessons learned from the module's implementation at outreach events. 

Research suggests that introducing students to computational concepts at a young age improves the likelihood that they will become interested in computer science later on in life (Super, 1953). As such, it is becoming increasingly important to develop lessons for K-12 students that include computational thinking (Barr, 2011). The storytelling project at Montana State University integrates computational thinking skills into the Indian Education for All (IEFA) curriculum for middle school students in Montana. 1. Identify an object not in Alice and needed for a lesson. 2. Develop rough draft and provide to the model developer. 3. Develop model in 3Ds max. 4. Add model to world, and add methods as needed. References Plateau Indian Beaded Bags 5. Gather feedback from students and instructors. Barr, V., & Stephenson, C. (2011). Bringing computational thinking to K-12: what is Involved and what is the role of the computer science education community? Acm Inroads, 2(1), 48-54. Cooper, J. (n.d.). Plateau beaded bag, ca. 1930 [Photograph found in Fred Mitchell, Montana Historical Society, Helena]. Retrieved from http://mhs.mt.gov/ Portals/11/education/ABeautifulTradition/tradition%20design%20color% 20brochure.pdf Super, D. E. (1953). A theory of vocational development. American Psychologist, 8(5), 185-190. We work to develop lesson plans, plan outreach events, and find relevant literature to satisfy the content standard requirements as well as the essential understandings associated with IEFA. Furthermore, we strive to integrate basic computer science concepts into these lessons to help pique student interest in programming and computational thinking. This is done using the Alice software, a drag-and-drop programming environment that allows students to use computational thinking in a beginner-friendly interface to create animations.