Shalini Chakraborty

Isabella Graßl, Christopher Lazik, Shalini Chakraborty et al.

Student engagement is critical for effective learning in software modelling, yet fostering motivation and inclusivity remains a challenge. While existing research has focused on modelling tools, notations, and assessment, little attention has been given to how the choice of problem domains and the diversity, relatability, and cultural perspectives they bring shape students' learning experiences. This study explores how problem domains and teaching methods influence motivation, engagement, inclusiveness, and feedback in modelling education. To investigate these dimensions, we conducted parallel surveys with 90 students and 22 educators. Our findings reveal disconnects between educator assumptions and student preferences: Students show greatest motivation for socially relevant domains and prefer choice in selection, while educators overestimate interest in study-related domains. The study identifies how minor design choices can exclude students. Students perceive feedback as meaningful when visibly acted upon. These findings suggest inclusive domain selection is central to student motivation; thus, we recommend student-centred domain selection.

Ioana Visescu, Shalini Chakraborty

Women in computer science and software engineering continue to face structural and cultural barriers affecting recognition, collaboration, and career progression. Existing environments often reinforce competition, tokenism, and exclusion, particularly in male dominated academic and professional spaces. This extended abstract introduces the 3C framework Competition, Competence, and Collaboration to explore how women experience and navigate networking in computing environments. We discuss how perceptions of competence, access to collaborative networks, and competition for limited opportunities shape womens' participation and sense of belonging. As a call to action, we propose community driven discussions, focus groups, and participatory data collection within the ACM womENcourage community to better understand and address these challenges. Our goal is to foster stronger networks of mentorship, solidarity, and collaboration among women in computing.

Shalini Chakraborty

Networking is central to careers in computer science, where a globally distributed and diverse community increasingly collaborates across institutional and geographic boundaries, often in hybrid and remote settings. However, access to effective networking is shaped by structural and personal factors, including geography, funding, language, identity, personality, and caregiving responsibilities. Building on prior work, this workshop focuses on women in computing to examine lived experiences of networking and the barriers they encounter. Through a community-driven discussion grounded in a factor-based framework, the workshop aims to surface overlooked challenges and foster shared understanding. Ultimately, it seeks to inform more inclusive, equitable, and accessible networking practices within the computer science community.

Shalini Chakraborty, Jan-Philipp Steghöfer

AI coding assistants are reshaping software development by shifting focus from writing code to formulating prompts. In chat-focused approaches such as vibe coding, prompts become the primary arbiter between human intent and executable software. While Requirements Engineering (RE) emphasizes capturing, validating, and evolving requirements, current prompting practices remain informal and adhoc. We argue that prompts should be understood as lightweight, evolving requirement artifacts that blend requirements with solution guidance. We propose a conceptual model decomposing prompts into three interrelated components: Functionality and Quality (the requirement), General Solutions (architectural strategy and technology choices) and Specific Solutions (implementation-level constraints). We assess this model using existing prompts, examining how these components manifest in practice. Based on this model and the initial assessment, we formulate four hypotheses: prompts evolve toward specificity, evolution varies by user characteristics, engineers using prompting engage in increased requirement validation and verification, and progressive prompt refinement yields higher code quality. Our vision is to empirically evaluate these hypotheses through analysis of real-world AI-assisted development, with datasets, corpus analysis, and controlled experiments, ultimately deriving best practices for requirements-aware prompt engineering. By rethinking prompts through the lens of RE, we position prompting not merely as a technical skill, but as a central concern for software engineering's future.

Grischa Liebel, Shalini Chakraborty

Context: Using student subjects in empirical studies has been discussed extensively from a methodological perspective in Software Engineering (SE), but there is a lack of similar discussion surrounding ethical aspects of doing so. As students are in a subordinate relationship to their instructors, such a discussion is needed. Objective: We aim to increase the understanding of practices and perceptions SE researchers have of ethical issues with student participation in empirical studies. Method: We conducted a systematic mapping study of 372 empirical SE studies involving students, following up with a survey answered by 100 SE researchers regarding their current practices and opinions regarding student participation. Results: The mapping study shows that the majority of studies does not report conditions regarding recruitment, voluntariness, compensation, and ethics approval. In contrast, the majority of survey participants supports reporting these conditions. The survey further reveals that less than half of the participants require ethics approval. Additionally, the majority of participants recruit their own students on a voluntary basis, and use informed consent with withdrawal options. There is disagreement among the participants whether course instructors should be involved in research studies and if should know who participates in a study. Conclusions: It is a positive sign that mandatory participation is rare, and that informed consent and withdrawal options are standard. However, we see immediate need for action, as study conditions are under-reported, and as opinions on ethical practices differ widely. In particular, there is little regard in SE on the power relationship between instructors and students.