Eliane Stampfer Wiese

Code structure, an important aspect of code quality, involves stylistic and structural decisions within individual functions, such as selecting appropriate control flow structures for a specific task. Despite over 40 years of research on student performance in various code structure topics, a comprehensive overview of these studies remains absent. Therefore, we conducted a systematic literature review to understand which function-level code structure topics were considered essential for student learning and what assessment practices were used to evaluate students’ knowledge of code structure. Our review identified approximately 70 code-structure topics, which we classified into 7 categories: expressions, variables and parameters, Boolean expressions, conditionals, loops, functions, and others. We created a catalog of these topics that includes their definitions, an example defect for each topic, and a corresponding solution. This catalog can serve as a resource for instructors seeking to incorporate code structure into introductory programming courses, as well as for researchers developing educational tools or investigating the extent and causes of code-structure violations. Regarding assessment practices in prior studies, we found that various assessment tasks and student artifacts were utilized, with half of the studies examining students’ code-writing submissions for the occurrence of violations. While this approach is scalable through the use of automated detectors, it provides limited insight into the underlying causes of these violations or into students’ performance on non-writing skills such as code refactoring. Additionally, we found very little research that focuses on specific assessment tasks such as code recall and code editing (i.e., refactoring others’ code). Moreover, while many studies suggested that student code structure defects stem from knowledge gaps in programming concepts, only a few empirically tested this hypothesis. Finally, we conclude this study by highlighting open areas for future research on code structure.

While there have been many calls for teaching ethics and responsible computing, it is unclear how responsible computing instruction and technical learning interact. Some instructors even hesitate to include ethics in their courses, fearing it might distract students from learning technical computing content. An approach called micro-insertion offers a path to teaching responsible computing while teaching technical content. Micro-insertion situates technical problems in real-world contexts, with frequent, minimally invasive discussions of potential harms of a computing professional’s technical choices. We conducted a between-subjects laboratory study where 82 post-secondary student participants were randomly assigned to one of two instructional conditions to learn a computing topic. The technical-only condition received traditional instruction, while the micro-insertion condition learned the same technical material contextualized within a real-world scenario with potential broader ethical or social impacts. Our study design included a pre-test, instruction intervention, immediate post-test, and a 2-week delayed post-test. Each test included both technical and contextualized questions, and the instructional time was the same across both conditions. The study revealed no statistically significant differences in learning outcomes between the two conditions. Participants in both conditions improved in solving problems presented both abstractly and contextualized with a real-world narrative. Thus, we did not find evidence that our responsible computing intervention distracted participants from learning the technical topics. Further, participants in the technical-only condition could correctly respond to contextualized questions, suggesting that students might be able to engage with responsible computing micro-insertions without targeted instruction. To more deeply understand students’ reasoning, we conducted follow-up interviews with 13 of the participants. The interviews revealed that participants in both conditions perceived to have learned about responsible computing from the study. However, the depth and quality of participants’ engagement with real-world issues varied significantly, with many only superficially addressing the context and many relying on their own personal experiences as their source of knowledge. We, therefore, encourage future studies to investigate other approaches to responsible computing education to determine which approach results in more meaningful consideration of social and ethical issues and whether that detracts from or supports technical learning.

The challenge of student retention in introductory-level computing classes is a key contributor to the lack of diversity in computing fields. While teaching assistants (TAs) play a critical role in these classes, their role in supporting student retention is yet to be explored. We employed a special TA, a retention TA (RTA), who focuses exclusively on supporting students who are at risk of failing the course. RTAs target students who are retaking the class or underperforming in exams or assignments. This contrasts with regular TAs, who focus on grading and other standard duties. In Spring 2024, four RTAs were assigned to four different introductory-level computing CS1 and CS2 classes. At the end of the semester, we analyzed student attendance records and compared the performance of students who sought help from RTAs to the overall class performance. In two of the four classes, students who engaged with RTAs performed better than the class average. We share experiences from one of those classes, including specific RTA strategies that may have contributed to student success, such as personalized communication, reviewing course content, and helping students get started on assignments.

The task of decomposing a problem into sub-problems to build a solution, also formalized as planning in prior work, is a key skill for programming expertise. Improving the decomposition and planning skills of novices is shown to be a challenging goal for educators. Moreover, decomposing complex projects into smaller subtasks is an increasingly relevant skill with rapid developments in tools like large language models (LLMs). While there are many aspects of planning, one skill consistently observed in studies with experts is the ability to identify subtasks that can be solved via common code patterns. To support students in acquiring these skills, many researchers have explored explicit instruction about a set of common patterns in programs (i.e. programming plans). However, recent work implies that students may need additional support to fully benefit from such interventions. This panel aims to bring computing education researchers together to discuss the main challenges around teaching decomposition and planning using common patterns, the crucial factors for designing instruction for teaching these concepts, and the impact evolving technology like LLMs can have on these developments.

Design empathy is a core HCI concept for understanding user perspectives in design processes. Although researchers advocate for leveraging design empathy in the design of assistive technology, educating novice designers about this is challenging; this is especially true in HCI classrooms when the target population includes people with disabilities, and students who do not have a disability are less aware of the diversity of disability. To help students better understand disability experiences, HCI education often adopts “be-like” (mimicking disabled-experience) approaches. However, accessibility researchers advocate adopting the “be-with” approach—learning about other’s experiences through companionship. To mitigate the logistical challenges of being-with in a classroom setting, we developed a “be-connected” approach, which facilitates learning about the disability experience through the narratives of real individuals. Using social media posts from a spinal cord injury subreddit, we developed and deployed an activity aiming to develop design empathy. Our qualitative evaluation showed a notable transformation in students’ design thinking process, suggesting an opportunity to leverage social media data to learn about disabled perspectives and develop design empathy.

How does students' knowledge of code structure improve as they progress through their degree, and where do students struggle? We conducted a comparative study between introductory (CS1) and intermediate CS students (CS2) to explore these questions. Using an online survey with several tasks, including identification of expert patterns, judgment of readable structure, code comprehension, code writing, and editing, we focused on two important code structures: (S1) returning boolean expressions directly and (S2) unique vs. repeated code within if and else. Student performance varied based on structure and task: in both S1 and S2, CS2 students demonstrated higher performance in identifying patterns, judgment of readable structure, and editing. However, evidence of improvement in code writing was only found for S1, and improvement in code comprehension was only found for S2. Therefore, students may need different supports across different code structures. With the exception of comprehension of S1, student performance was far below ceiling, suggesting a need for more support. Additionally, we examined how student performance in different tasks was related to their writing structure. Overall, there were limited and varying relationships between performance in other tasks and writing: code editing predicted writing performance for both structures. For S1, student judgment of readability was also associated with writing structure, and for S2, comprehension predicted writing structure.

The computing education research community now has at least 40 years of published research on teaching ethics in higher education. To examine the state of our field, we present a systematic literature review of papers in the Association for Computing Machinery computing education venues that describe teaching ethics in higher-education computing courses. Our review spans all papers published to SIGCSE, ICER, ITiCSE, CompEd, Koli Calling, and TOCE venues through 2022, with 100 papers fulfilling our inclusion criteria. Overall, we found a wide variety in content, teaching strategies, challenges, and recommendations. The majority of the papers did not articulate a conception of “ethics,” and those that did used many different conceptions, from broadly applicable ethical theories to social impact to specific computing application areas (e.g., data privacy and hacking). Instructors used many different pedagogical strategies (e.g., discussions, lectures, assignments) and formats (e.g., stand-alone courses, incorporated within a technical course). Many papers identified measuring student knowledge as a particular challenge, and 59% of papers included mention of assessments or grading. Of the 69% of papers that evaluated their ethics instruction, most used student self-report surveys, course evaluations, and instructor reflections. While many papers included calls for more ethics content in computing, specific recommendations were rarely broadly applicable, preventing a synthesis of guidelines. To continue building on the last 40 years of research and move toward a set of best practices for teaching ethics in computing, our community should delineate our varied conceptions of ethics, examine which teaching strategies are best suited for each, and explore how to measure student learning.

While the CS education community has successfully incorporated tech-ethics assignments and modules into computing courses, we lack a defined process for instructional design to create these materials from scratch across the curriculum. To enable the development of such a process, we explore two research questions: (1) What specific instructional design challenges emerge when creating ethically-integrated assignments for CS courses? And (2) what strategies might overcome them? We address these questions using Research through Design, a method for critically examining design processes. Applying this method to our own process of creating ethics-integrated CS assignments yielded four key challenges: identifying an ethical context, maintaining a technical focus, eliciting both ethical and technical thinking from students, and making the assignment practical for the classroom. Further, the Research through Design approach revealed process-level insights for addressing these challenges, which can apply across the computing curriculum. This paper also serves as a case study of Research through Design for CS education, highlighting the importance of the instructional design process and the behind-the-scenes challenges and design decisions that go into tech-ethics materials.

How can we assess the quality of students’ Contextual Inquiries (CIs) when we cannot observe them? We present a structured self-evaluation to assess students’ use of CI techniques, where students use pre-defined categories to identify their own successful and unsuccessful instances of following CI principles. In addition to giving the course staff a window into the inquiry, these self-evaluations also illustrate common student misconceptions and missteps such as: missing the overall purpose of a CI, gathering summary rather than concrete data, and struggling to effectively communicate their results. Anticipating these misconceptions can support rubric creation, efficient feedback, and targeted activities for instructors who include CIs in their HCI courses.

Human-Computer Interaction (HCI) education research strives to integrate inclusion and diversity in classroom teaching. We focus on a key demographic that has been historically underrepresented in design: people with multiple disabilities and/or severe motor disabilities. Since engaging directly with these populations is rarely feasible, we need other ways of teaching students how to consider the challenges, emotions, and lived experiences of these target users. While current approaches in HCI education do engage students in thinking about accessibility through curated disabled experiences (e.g., simulation or personas), these methods do not fully reflect the holistic experience of people with disabilities. We propose a new way of teaching design empathy: immersing students in the real-world experiences of people with disabilities through a curated set of their public social media posts.