There are a number of novel exercise types that students can utilize while learning Computer Science, each with its own level of complexity and interaction as outlined by the ICAP Framework [10]. Some are "Interactive," like solving coding problems; "Constructive," like explaining code; "Active," like retyping source code; and "Passive," like reviewing slides. To date, there has been little research on how students vary their study and engagement habits by exercise type and when they do so. In this paper, we present our findings on student activity sequences from an online professional development course. We isolated student activities into sessions and then produced activity transition visualizations to compare the behavior of students who complete the course to those who do not. We then used multiple factor analyses to examine how students transition from one type of activity to the next. From this analysis we identified "platform silos" in student's work. We further expand this concept to the presence of "activity silos" grouping by type. We find that this siloing behavior is consistent in both completers and non-completers but is weaker for the latter group. Finally, we discuss our findings and how instructors and researchers may use this information to ensure that students show persistence through practice. [For the full proceedings, see ED615472.]