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1. An Empirical Evaluation of Active Live Coding in CS1

   https://doi.org/10.1145/3743686  

   Shah, Anshul; Rexin, Thomas; Alhumrani, Fatimah; Griswold, William G; Porter, Leo; Soosai_Raj, Gerald (June 2025, ACM Transactions on Computing Education)

   Objectives The traditional, instructor-led form of live coding has been extensively studied, with findings showing that this form of live coding imparts similar learning to static-code examples. However, a concern with Traditional Live Coding is that it can turn into a passive learning activity for students as they simply observe the instructor program. Therefore, this study compares Active Live Coding—a form of live coding that leverages in-class coding activities and peer discussion—to Traditional Live Coding on three outcomes: 1) students’ adherence to effective programming processes, 2) students’ performance on exams and in-lecture questions, and 3) students’ lecture experience. Participants Roughly 530 students were enrolled in an advanced, CS1 course taught in Java at a large, public university in North America. The students were primarily first- and second-year undergraduate students with some prior programming experience. The student population was spread across two lecture sections—348 students in the Active Live Coding (ALC) lecture and 185 students in the Traditional Live Coding (TLC) lecture. Study Methods We used a mixed-methods approach to answer our‘ research questions. To compare students’ programming processes, we applied process-oriented metrics related to incremental development and error frequencies. To measure students’ learning outcomes, we compared students’ performance on major course components and used pre- and post-lecture questionnaires to compare students’ learning gain during lectures. Finally, to understand students’ lecture experience, we used a classroom observation protocol to measure and compare students’ behavioral engagement during the two lectures. We also inductively coded open-ended survey questions to understand students’ perceptions of live coding. Findings We did not find a statistically significant effect of ALC on students’ programming processes or learning outcomes. It seems that both ALC and TLC impart similar programming processes and result in similar student learning. However, our findings related to students’ lecture experience shows a persistent engagement effect of ALC, where students’ behavioral engagement peaks andremains elevatedafter the in-class coding activity and peer discussion. Finally, we discuss the unique affordances and drawbacks of the lecture technique as well as students’ perceptions of ALC. Conclusions Despite being motivated by well-established learning theories, Active Live Coding did not result in improved student learning or programming processes. This study is preceded by several prior works that showed that Traditional Live Coding imparts similar student learning and programming skills as static-code examples. Though potential reasons for the lack of observed learning benefits are discussed in this work, multiple future analyses to further investigate Active Live Coding may help the community understand the impacts (or lack thereof) of the instructional technique. 

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2. Achievement Goals in CS1-LLM

   https://doi.org/10.1145/3716640.3716656  

   Vadaparty, Annapurna; Geng, Francis; Smith, David H; Benario, Jamie Gorson; Zingaro, Daniel; Porter, Leo (February 2025, ACM)

   Introduction: The emergence and widespread adoption of generative AI (GenAI) chatbots such as ChatGPT, and programming assistants such as GitHub Copilot, have radically redefined the landscape of programming education. This calls for replication of studies and reexamination of findings from pre-GenAI CS contexts to understand the impact on students. Objectives: Achievement Goals are well studied in computing education and can be predictive of student interest and exam performance. The objective in this study is to compare findings from prior achievement goal studies in CS1 courses with new CS1 courses that emphasize the use of human-GenAI collaborative coding. Methods: In a CS1 course that integrates GenAI, we use linear regression to explore the relationship between achievement goals and prior experience on student interest, exam performance, and perceptions of GenAI. Results: As with prior findings in traditional CS1 classes, Mastery goals are correlated with interest in computing. Contradicting prior CS1 findings, normative goals are correlated with exam scores. Normative and mastery goals correlate with students’ perceptions of learning with GenAI. Mastery goals weakly correlate with reading and testing code output from GenAI. 

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3. Early Career Engineers’ Views of Ethics and Social Responsibility: Study Overview

   Claussen, S.; Jesiek, B. K.; Zoltowski, C. B.; Howland, S. (July 2021, Proceedings of the 2021 American Society of Engineering Education Virtual Annual Conference)

   null (Ed.)

   Amidst growing concerns about a lack of attention to ethics in engineering education and professional practice, a variety of formal course-based interventions and informal or extracurricular programs have been created to improve the social and ethical commitments of engineering graduates. To supplement the formal and informal ethics education received as undergraduate students, engineering professionals often also participate in workplace training and professional development activities on ethics, compliance, and related topics. Despite this preparation, there is growing evidence to suggest that technical professionals are often challenged to navigate ethical situations and dilemmas. Some prior research has focused on assessing the impacts of a variety of learning experiences on students’ understandings of ethics and social responsibility, including the PIs’ prior NSF-funded CCE STEM study which followed engineering students through the four years of their undergraduate studies using both quantitative and qualitative research methods. This prior project explored how the students’ views on these topics changed across demographic groups, over time, between institutions, and due to specific interventions. Yet, there has been little longitudinal research on how these views and perceptions change (or do not change) among engineers during the school-to-work transition. Furthermore, there has been little exploration of how these views are influenced by the professional contexts in which these engineers work, including cultures and norms prevalent in different technical fields, organizations, and industry sectors. This NSF-supported Ethical and Responsible Research (ER2) study responds to these gaps in the literature by asking: RQ1) How do perceptions of ethics and social responsibility change in the transition from undergraduate engineering degree programs to the workplace (or graduate studies), and how are these perceptions shaped or influenced?, and RQ2) How do perceptions of ethics and social responsibility vary depending on a given individual’s engineering discipline/background and current professional setting? This paper gives an overview of the research project, describing in particular the longitudinal, mixed-methods study design which will involve collecting and analyzing data from a large sample of early career engineers. More specifically, we will present the proposed study contexts, timeline, target subject populations, and procedures for quantitative and qualitative data collection and analysis. We will also describe how this study leverages our prior project, thereby allowing unique longitudinal comparisons that span participants’ years as an engineering undergraduate student to their time as an early-career professional. Through this project, we aim to better understand how early career engineers’ perceptions of social and ethical responsibility are shaped by their prior experiences and current professional contexts. This paper will likely be of particular interest to scholars who teach or research engineering ethics, social responsibility, and professional practice. 

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4. Temporal shifts in Americans’ risk perceptions of the Zika outbreak

   https://doi.org/10.1080/10807039.2020.1820852  

   Johnson, Branden B.; Mayorga, Marcus (September 2020, Human and Ecological Risk Assessment: An International Journal)

   Cross-sectional surveys, despite their value, are unable to probe dynamics of risk perceptions over time. An earlier longitudinal panel study of Americans’ views on Ebola risk inspired this partial replication on Americans’ views of Zika risks, using multilevel modeling to assess temporal changes in these views and inter-individual factors affecting them, and to determine if similar factors were influential for both non-epidemics in the USA. Baseline Zika risk scores – as in the Ebola study – were influenced by dread of the Zika virus, perceptions of a near-miss outbreak, and perceived likelihood of an outbreak. Judgments of both personal risk and national risk from Zika declined significantly, and individual rates of news following predicted slower decline of perceived national risk in both cases. However, few other factors affected changes in Zika risk judgments, which did not replicate in a validation half-sample, whereas several factors slowed or increased the rate of decline in Ebola judgments of the U.S. risk. These differences might reflect differences in the diseases caused by these two viruses – e.g., Ebola’s much greater lethality – but more longitudinal studies across multiple diseases will be needed to test that speculation. Benefits of such studies to health risk analysis outweigh the difficulties they pose. 

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5. When Literacies Collide: The Role of Translation in Music+Coding Activities

   https://doi.org/10.1145/3594781.3594795  

   Roberts, Cameron; Horn, Michael (June 2023, Symposium on Learning, Design, and Techology)

   The integration of computer programming and music-making has a rich history dating back to the 1950s. While there has been substantial prior work on the creative and cognitive affordances of programming languages for engaging in musical tasks, there is less work that attempts to understand the theoretical implications of music and code as literacies in collision. In this paper, we report on a study in which five undergraduate students with experience in both music and coding completed two creative musical tasks: one using conventional instruments and tools and one using Python code in an online music-coding environment. In combining representational infrastructures from music and code, both undergo transformations. We introduce semiotic theories of translation and transcription to make sense of the music-coding process and describe strategies that participants devised in their creative process. 

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