Software developers frequently switch tasks in their daily work, each involving different artifacts such as code files, websites, and documents. These artifacts accumulate across tasks, cluttering the workspace, and making it cognitively demanding to identify relevant ones during resumption. Existing solutions group artifacts, but do not effectively reduce workspace clutter for better task resumption and often overlook development specific artifacts. This paper introduces TaskSnap, a novel approach that supports the semi-automated creation of snapshots to group task-relevant artifacts. These snapshots are automatically closed at task boundaries to reduce clutter and restored when resuming a previously interrupted task to reconstruct the working context. We evaluated TaskSnap in a controlled lab experiment with 55 software developers who worked on two development tasks and one information-seeking task, switching between them after interruptions or upon completion. Results showed that TaskSnap improved task resumption by significantly reducing edit lags (time to first code edit). Separating task contexts into snapshots reduced perceived cognitive load and fostered focus on the current task by reducing clutter and access to task-unrelated artifacts. We discuss the benefits of leveraging task snapshots for task switching and artifact management, and explore design opportunities for balancing automation and user control in real-world adoption.

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental condition characterized by patterns of inattention and impulsivity, which lead to difficulties maintaining concentration and motivation while completing academic tasks. University settings, characterized by a high student-to-staff ratio, make treatments relying on human monitoring challenging. One potential replacement is Virtual Reality (VR) technology, which has shown potential to enhance learning outcomes and promote flow experience. In this study, we investigate the usage of VR with 27 university students with ADHD in an effort to improve their performance in ctableompleting homework, including an exploration of automated feedback via a technology probe. Quantitative results show significant increases in concentration, motivation, and effort levels during these VR sessions and qualitative data offers insight into considerations like comfort and deployment. Together, the results suggest that VR can be a valuable tool in leveling the playing field for university students with ADHD.

Teaching students complex problem-solving skills using large-scale, real-world problems is challenging for both students and teachers alike. As a result, most courses use small, well-specified, toy-like problems, which are not representative of what students will encounter in the workforce. One approach that allows teachers to use large-scale problems in class is by introducing scaffolding. Scaffolding breaks a larger problem into smaller steps, which students can solve independently, while deemphasizing tangential concepts such as the complex configuration files needed to compile open-source software systems. Strong scaffolding supports student learning, preventing them from getting bogged down with unnecessary tasks or overwhelmed by complexity. This work investigates a scaffolded problem-based-learning module for computing courses, using a realistically-sized project with characteristics representative of the industry. The project was implemented in a computer science course with roughly 100 students, and the results speak to the importance of scaffolding for student success. In fact, there were two student assignments that lacked sufficient scaffolding, compared with other tasks, and the reduction in student scoring and persistence shows that project scaffolding is necessary when implementing these types of assignments. Most students felt the project helped prepare them for a job in their chosen field.

This qualitative research performs a thematic analysis of the learning objectives in existing project-based undergraduate software engineering courses to align them with the competency model defined in the Computing Curricula 2020 reports (CC2020). This study identifies the trends, strengths, and gaps in how the reviewed course learning objectives cover the knowledge, skill, and disposition components of the CC2020 competency model. The learning objectives were categorized according to knowledge elements, skills, and dispositions as defined in the CC2020 competency model. Our analysis shows that 54% of knowledge elements from the reviewed learning objectives do not have any skill level specified and overall, only two out of the eleven dispositions in CC2020 are specified (“Collaboration” and “Professional”). We also find that technical knowledge elements from the software development category (e.g., software process, software design, and software quality, verification & validation) and systems modeling category (e.g., systems analysis & design, and requirements analysis and specification), probably unsurprisingly, are covered the most often. Similarly, collaboration & teamwork, and oral & written communication are unsurprisingly the most common professional & foundational knowledge elements in the reviewed course's learning objectives as they are essential to project-based learning. Although they are essential for the completion of a successful software project, knowledge elements such as time management, security technology & implementation, and user experience design are rarely mentioned. We discuss the implications of our findings on course design.