Since March of 2020, universities around the world have offered remote versions of courses to help limit the spread of COVID-19. Two years later, in the Spring 2022 quarter, the lectures in the CS1 course at our large, public research-intensive university were taught via two modalities---an in-person modality in which students attended traditional, in-person lectures and a blended modality in which students attended a remote lecture on Zoom. Every other course component---labs, discussions, office hours---were held in-person for both groups. The unique setup of the CS1 course allowed us to perform a comparative analysis of the outcomes and attitudes between the two groups. In this paper, we analyze the difference in course outcomes, peer support, competitive feelings in class, and students' sense of belonging between the groups. Our results indicate that students in the blended learning group attended lectures more frequently than their in-person counterparts yet performed 4-7%worse on the midterm and final exams. The blended learning group also experienced significantlyless feelings of competitiveness than their in-person counterparts. Interestingly, we discovered a consistent trend among our results indicating that the gap in grades, peer support, and classroom competitiveness between the blended group and in-person group was more pronounced among first- and second-year undergraduates than third- and four-year students. Despite the two learning groups having different instructors, our results shed light on the potential advantages and drawbacks of a blended learning experience in CS1 that instructors should consider when deciding on the format of their course.

Background and Context. Live coding is a teaching method in which an instructor dynamically writes code in front of students in an effort to impart skills such as incremental development and debugging. By contrast, traditional, static-code examples typically involve an instructor annotating or explaining components of pre-written code. Despite recommendations to use live coding and a wealth of qualitative analyses that identify perceived learning benefits of it, there are a lack of empirical evaluations to confirm those learning benefits, especially with respect to students’ programming processes.

Online discussion boards, designed to facilitate learning from peers and instructors in an accessible space, are a vital part of course design, especially in large scale computer science classes. Previous work has shown that women in computer science tend to use anonymity more often than men on these boards, a trend not found in humanities, social science or business courses. In this work, we build on these findings using an intersectional lens, analyzing both gender and race/ethnicity. We find this combined analysis reveals differences in anonymity that are not apparent when examining gender alone. For example, we find a significantly greater difference in anonymity use between Hispanic men and women than would be expected from analyzing race/ethnicity and gender independently. We additionally analyze type of content (e.g., questions, answers), course, platform, and data source to characterize the many factors at play in measuring students’ choice to participate anonymously. In doing so, we show that different approaches used in prior work for eliciting information on gender — whether using registrar data, a survey, or imputing gender based on name — changes how over of students are classified, particularly affecting nonbinary students and Asian students. Understanding when students participate anonymously can help educators and platform designers to make students’ experience of online discussion boards more welcoming.

Live coding---a pedagogical technique in which an instructor plans, writes, and executes code in front of a class---is generally considered a best practice when teaching programming. However, only a few studies have evaluated the effect of live coding on student learning in a controlled experiment and most of the literature relating to live coding identifies students' perceived benefits of live-coding examples. In order to empirically evaluate the impact of live coding, we designed a controlled experiment in a CS1 course taught in Python at a large public university. In the two remote lecture sections for the course, one was taught using live-coding examples and the other was taught using static-code examples. Throughout the term, we collected code snapshots from students' programming assignments, students' grades, and the questions that they asked during the remote lectures. We then applied a set of process-oriented programming metrics to students' programming data to compare students' adherence to effective programming processes in the two learning groups and categorized each question asked in lectures following an open-coding approach. Our results revealed a general lack of difference between the two groups across programming processes, grades, and lecture questions asked. However, our experiment uncovered minimal effects in favor of the live-coding group indicating improved programming processes but lower performance on assignments and grades. Our results suggest an overall insignificant impact of the style of presenting code examples, though we reflect on the threats to validity in our study that should be addressed in future work.

Previous studies have shown that non-native English speakers (NNES) have lower confidence levels at the beginning of the term and higher academic expectations for themselves throughout the term. Additionally, although non-native English speakers study for longer hours compared to native English speakers (NES), there were not any differences in their grades. To better understand the experiences of NNES learning Computer Science in a U.S university, we examined possible factors that may contribute to differences in stress and sense of belonging between NES and NNES. From our investigation using weekly surveys, we did not find any significant difference in the stress level reported by NES and NNES. However, we found differences in the factors that contribute to the stress level of NES and NNES. Factors such as 'personal life' and 'requirements for other classes' were major factors that contributed towards the stress level of NES, whereas 'embarrassment asking for help' and 'self doubt' were more common among NNES. As for sense of belonging, we found no significant difference between NES and NNES. Additionally, we found that the number of classmates that NES feel comfortable reaching out to is not a factor affecting their sense of belonging in an introductory computer science class. \endabstract