There are many tasks that must be done to keep a computing course running smoothly. In addition to pedagogical work, instructors do a multitude of behind-the-scenes administrative and organizational work themselves or delegate it to Teaching Assistants (TAs). Despite the pervasiveness of this type of work, the explicit details of what kinds of tasks are necessary, the processes to execute these tasks well, and the experiences and feelings of those doing the tasks have not been reported in the literature. Therefore, this experience report surfaces these details by presenting the reflections of a long-time TA who has worked on significant administrative tasks across eight CS courses at our institution over the years. As a representative sample of her experiences, we report on three anecdotes that highlight logistical and internal challenges she faced as a TA for a CS1 course: 1) managing the flow of 600 students coming into a computer lab to take proctored assessments, 2) scanning and uploading thousands of pages of on-paper exams, 3) leading an exam grading session of dozens of TAs. Based on her reflections, we see how much intentional foresight and preparation goes into preventing chaotic situations, as well as many concurrent and overlapping threads to manage in an overarching task. The combination of these factors as well as challenges in team and interpersonal dynamics were the primary sources of stress. Our goal is to bring awareness to this aspect of course delivery that is oftentimes hidden and inspire future research around it.

Undergraduate teaching assistants (tutors) are commonly employed in computing courses to help students with programming assignments. Prior research in computing education has reported the benefits of tutoring both for students and for the tutors' own learning. In contrast, recent research that examined actual tutoring sessions has reported that these sessions may be less productive than one might hope, with tutors often just giving students the answers to their problems without trying to teach the underlying concepts. To better understand why tutors may be employing these suboptimal practices, we interviewed ten tutors across early computing courses in higher education to identify their perceived role in these sessions, what stressors and factors influence their ability to perform their job effectively, and what kinds of best practices they learned in their tutor training course. Tutors reported their roles around student learning, gauging student understanding, identifying or providing solutions to students, and providing socioemotional support. They reported their stressors around environmental factors (e.g., number of students waiting to be helped, preparation time, peer-tutor frustrations), internal influences, student behavior, student skill levels, and feeling the need to ''read a student's mind.'' Regarding their tutor training course, Tutors reported learning about interaction guidelines and procedures and question-based problem solving. We conclude by discussing how these results may contribute to the less-effective behaviors seen in prior research and potential ways to improve tutoring in computing courses.

Recent research in computing has shown that student performance on prerequisite course content varies widely, even when students continue to progress further through the computing curriculum. Our work investigates instructors' perspectives on the purpose of prerequisite courses and whether that purpose is being fulfilled. In order to identify the range of instructor views, we interviewed twenty-one computer science instructors, at two institutions, that teach a variety of courses in their respective departments. We conducted a phenomenographic analysis on the interview transcripts, which revealed a wide variety of views on prerequisite courses. The responses shed light on various issues with prerequisite course knowledge, as well as issues around responsibility and conflicting pressures on instructors. These issues arise at the department level, as well as with individual course offerings.

Many institutions use undergraduate teaching assistants (tutors) in their computing courses to help provide more resources to students. Because of the role tutors play in students' learning experiences, recent work in computing education has begun to explore student-tutor interactions through the tutor's perspective and through direct observation of the interactions. The results suggest that these interactions are cognitively challenging for tutors and may not be as beneficial for students' learning as one might hope. Given that many of these interactions may be unproductive, this work seeks to understand how student expectations of these sessions might be impacting the interactions' effectiveness. We interviewed 15 students in a CS2 course to learn about the expectations and desires that students have when they attend tutoring sessions. Our findings indicate that there is variation in what students consider a desired result from the interaction, that assignment deadlines affect students' expectations and desires for interactions, and that students do not always want what they believe is beneficial for their learning. We discuss implications for instructors and potential guidance for students and tutors to make tutoring sessions more effective.

Now that students in our introductory object-oriented programming course are more familiar with Zoom and screen sharing, we consider novel assessments that leverage these tools. We developed a style of assessment where students submit a recorded screencast of them tracing a submitted program. We describe the design of the assessment and tracing prompts, and we report on an analysis of 59 submitted student videos. Our findings include common mistakes and aspects of student understanding that were expressed in the video but not in the text and code submitted by students. For example, we observed different strategies that yielded the same correct trace of a loop, as well as incorrect traces of students' own correct recursive programs. These guide us towards ways to refine the assessment and prompts in future iterations.

As enrollments in computing courses have surged, the ratio of students to faculty has risen at many institutions. Along with many other large undergraduate programs, our institution has adapted to this challenge by hiring increasing numbers of undergraduate tutors to help students. In early computing courses, their role at our institution is primarily to help students with their programming assignments. Despite our institution offering a training course for tutors, we are concerned about the quality and nature of these student-tutor interactions. As instruction moved online due to COVID-19, this provided the unique opportunity to record all student-tutor interactions (among consenting participants) for research. In order to gain an understanding of the behaviors common in these interactions, we conducted an initial qualitative analysis using open coding followed by a quantitative analysis on those codes. Overall, we found that students are not generally receiving the instruction we might hope or expect from these sessions. Notably, tutors often simply give students the solution to the problem in their code without teaching them about the process of finding and correcting their own errors. These findings highlight the importance of tutoring sessions for learning in introductory courses and motivate remediation to make these sessions more productive.