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Prior work on novice programmers' self-regulation have shown it to be inconsistent and shallow, but trainable through direct instruction. However, prior work has primarily studied self-regulation retrospectively, which relies on students to remember how they regulated their process, or in laboratory settings, limiting the ecological validity of findings. To address these limitations, we investigated 31 novice programmers' self-regulation in situ over 10 weeks. We had them to keep journals about their work and later had them to reflect on their journaling. Through a series of qualitative analyses of journals and survey responses, we found that all participants monitored their process and evaluated their work, that few interpreted the problems they were solving or adapted prior solutions. We also found that some students self-regulated their programming in many ways, while others in almost none. Students reported many difficulties integrating reflection into their work; some were completely unaware of their process, some struggled to integrate reflection into their process, and others found reflection conflicted with their work. These results suggest that self-regulation during programming is highly variable in practice, and that teaching self-regulation skills to improve programming outcomes may require differentiated instruction based on students self-awareness and existing programming practices. 

About half of recent computer and information science graduates attended community college at some point. Prior work on transfer students in general suggests that the transfer process can engage people from underrepresented communities, but can also be academically and socially "shocking". However, we know little about the experiences of transfer students in computer science in particular. We used the Laanan-Transfer Student Questionnaire (L-TSQ) to survey 25 transfer students and 135 native (non-transfer) students and conducted follow-up interviews with 8 transfer students attending a large public 4-year university in a city with significant technology industry presence. We found that while transfer students were more diverse demographically, the support of the university for transfer student orientation tended to mitigate social shocks of transferring. This did not, however, eliminate gaps in academic performance. These findings suggest that there are other non-social factors that influence academic performance that CS programs must support to equitably engage students who transfer.