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Students can have widely varying experiences while working on CS2 coding projects. Challenging experiences can lead to lower motivation and less success in completing these assignments. In this paper, we identify the common struggles CS2 students face while working on course projects and examine whether or not there is evidence of improvement in these areas of struggle between projects. While previous work has been conducted on understanding the importance of self-regulated learning to student success, it has not been fully investigated in the scope of CS2 coursework. We share our observations on investigating student struggles while working on coding projects through their self-reported response to a project reflection form. We apply emergent coding to identify student struggles at three points during the course and compare them against student actions in the course, such as project start times and office hours participation, to identify if students were overcoming these struggles. Through our coding and analysis we have found that while a majority of students encounter struggles with time management and debugging of failing tests, students tend to emphasize wanting to improve their time management skills in future coding assignments. 

In Computer Science (CS) education, instructors use office hours for one-on-one help-seeking. Prior work has shown that traditional in-person office hours may be underutilized. In response many instructors are adding or transitioning to virtual office hours. Our research focuses on comparing in-person and online office hours to investigate differences between performance, interaction time, and the characteristics of the students who utilize in-person and virtual office hours. We analyze a rich dataset covering two semesters of a CS2 course which used in-person office hours in Fall 2019 and virtual office hours in Fall 2020. Our data covers students' use of office hours, the nature of their questions, and the time spent receiving help as well as demographic and attitude data. Our results show no relationship between student's attendance in office hours and class performance. However we found that female students attended office hours more frequently, as did students with a fixed mindset in computing, and those with weaker skills in transferring theory to practice. We also found that students with low confidence in or low enjoyment toward CS were more active in virtual office hours. Finally, we observed a significant correlation between students attending virtual office hours and an increased interest in CS study; while students attending in-person office hours tend to show an increase in their growth mindset. 

As enrollment in CS programs have risen, it has become increasingly difficult for teaching staff to provide timely and detailed guidance on student projects. To address this, instructors use automated assessment tools to evaluate students' code and processes as they work. Even with automation, understanding students' progress, and more importantly, if students are making the 'right' progress toward the solution is challenging at scale. To help students manage their time and learn good software engineering processes, instructors may create intermediate deadlines, or milestones, to support progress. However, student's adherence to these processes is opaque and may hinder student success and instructional support. Better understanding of how students follow process guidance in practice is needed to identify the right assignment structures to support development of high-quality process skills. We use data collected from an automated assessment tool, to calculate a set of 15 progress indicators to investigate which types of progress are being made during four stages of two projects in a CS2 course. These stages are split up by milestones to help guide student activities. We show how looking at which progress indicators are triggered significantly more or less during each stage validates whether students are adhering to the goals of each milestone. We also find students trigger some progress indicators earlier on the second project suggesting improving processes over time.