arXiv subjects

Alison Olechowski

Publications and source records attributed to Alison Olechowski.

9 recordsLinked to original sources

arXiv2026

Untangling the Timeline: Challenges and Opportunities in Supporting Version Control in Modern Computer-Aided Design

Version control is critical in mechanical computer-aided design (CAD) to enable traceability, manage product variation, and support collaboration. Yet, its implementation in modern CAD software as an essential information infrastructure for product development remains plagued by issues due to the complexity and interdependence of design data. This paper presents a systematic review of user-reported challenges with version control in modern CAD tools. Analyzing 170 online forum threads, we identify recurring socio-technical issues that span the management, continuity, scope, and distribution of versions. Our findings inform a broader reflection on how version control should be designed and improved for CAD and motivate opportunities for tools and mechanisms that better support articulation work, facilitate cross-boundary collaboration, and operate with infrastructural reflexivity. This study offers actionable insights for CAD software providers and highlights opportunities for researchers to rethink version control.

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arXiv2025

Two Sides to Every Story: Exploring Hybrid Design Teams' Perceptions of Psychological Safety on Slack

While the unique challenges of hybrid work can compromise collaboration and team dynamics, hybrid teams can thrive with well-informed strategies and tools that nurture interpersonal engagements. To inform future supports, we pursue a mixed-methods study of hybrid engineering design capstone teams' Psychological Safety (PS) (i.e., their climate of interpersonal risk-taking and mutual respect) to understand how the construct manifests in teams engaged in innovation. Using interviews, we study six teams' perceptions of PS indicators and how they present differently on Slack (when compared to in-person interactions). We then leverage the interview insights to design Slack-based PS indicators. We present five broad facets of PS in hybrid teams, four perceived differences of PS on Slack compared to in-person, and 15 Slack-based, PS indicators--the groundwork for future automated PS measurement on instant-messaging platforms. These insights produce three design implications and illustrative design examples for ways instant-messaging platforms can support Psychologically Safe hybrid teams, and best practices for hybrid teams to support interpersonal risk-taking and build mutual respect.

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arXiv2025

It's a Complete Haystack: Understanding Dependency Management Needs in Computer-Aided Design

In today's landscape, hardware development teams face increasing demands for better quality products, greater innovation, and shorter manufacturing lead times. Despite the need for more efficient and effective processes, hardware designers continue to struggle with a lack of awareness of design changes and other collaborators' actions, a persistent issue in decades of CSCW research. One significant and unaddressed challenge is understanding and managing dependencies between 3D CAD (computer-aided design) models, especially when products can contain thousands of interconnected components. In this two-phase formative study, we explore designers' pain points of CAD dependency management through a thematic analysis of 100 online forum discussions and semi-structured interviews with 10 designers. We identify nine key challenges related to the traceability, navigation, and consistency of CAD dependencies, that harm the effective coordination of hardware development teams. To address these challenges, we propose design goals and necessary features to enhance hardware designers' awareness and management of dependencies, ultimately with the goal of improving collaborative workflows.

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arXiv2024

Social Capital and Persistence in Computer Science of Google's Computer Science Summer Institute (CSSI) Students

While a lucrative and growing field, low levels of gender and racial diversity in CS remain prevalent. Education and workforce support programs with the intention to promote underrepresented students' persistence in CS exist, which teach skills, inform of career options, and grow students' network in CS. Studies demonstrate these programs' effectiveness as it relates to changes in affective outcomes, such as participants' confidence in CS skills and attitudes towards CS jobs. However, programs' longitudinal impact on participants' build-up of social capital in CS, and the resulting social capital's influence on their persistence in CS, remain unexplored. Motivated by the literature that associates demographic identifiers with access to social capital, and students' access to developmental relationships and career resources (social capital) in CS with their persistence, this study explores a CS support program's impact on persistence through capital building. We focus on Google's CSSI, which provided graduating high school students with a 3-week-long introduction to CS. We use interviews with participants who are now 2-5 years out of the program to study CSSI's impact on their social capital and long-term CS persistence. Thematic analysis reveals three program elements that influenced students' build-up of social capital, and that the resulting persistence was realized through students' progress towards internships and goals for paying-it-forward in CS. These findings inform our recommendations that future support programs and educational settings consider mentorship centered on socioemotional support, opportunities for collaboration, and time for fun social activities. Additional suggestions center on engaging socially-oriented individuals with CS support programs. These insights inform CS educators on design choices that can encourage the persistence of underrepresented students in CS.

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arXiv2024

"A Lot of Moving Parts": A Case Study of Open-Source Hardware Design Collaboration in the Thingiverse Community

Open-source is a decentralized and collaborative method of development that encourages open contribution from an extensive and undefined network of individuals. Although commonly associated with software development (OSS), the open-source model extends to hardware development, forming the basis of open-source hardware development (OSH). Compared to OSS, OSH is relatively nascent, lacking adequate tooling support from existing platforms and best practices for efficient collaboration. Taking a necessary step towards improving OSH collaboration, we conduct a detailed case study of DrawBot, a successful OSH project that remarkably fostered a long-term collaboration on Thingiverse - a platform not explicitly intended for complex collaborative design. Through analyzing comment threads and design changes over the course of the project, we found how collaboration occurred, the challenges faced, and how the DrawBot community managed to overcome these obstacles. Beyond offering a detailed account of collaboration practices and challenges, our work contributes best practices, design implications, and practical implications for OSH project maintainers, platform builders, and researchers, respectively. With these insights and our publicly available dataset, we aim to foster more effective and efficient collaborative design in OSH projects.

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arXiv2024

No Risk, No Reward: Towards An Automated Measure of Psychological Safety from Online Communication

The data created from virtual communication platforms presents the opportunity to explore automated measures for monitoring team performance. In this work, we explore one important characteristic of successful teams - Psychological Safety - or the belief that a team is safe for interpersonal risk-taking. To move towards an automated measure of this phenomenon, we derive virtual communication characteristics and message keywords related to elements of Psychological Safety from the literature. Using a mixed methods approach, we investigate whether these characteristics are present in the Slack messages from two design teams - one high in Psychological Safety, and one low. We find that some usage characteristics, such as replies, reactions, and user mentions, might be promising metrics to indicate higher levels of Psychological Safety, while simple keyword searches may not be nuanced enough. We present the first step towards the automated detection of this important, yet complex, team characteristic.

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arXiv2023

Advancing a Model of Students' Intentional Persistence in Machine Learning and Artificial Intelligence

Machine Learning (ML) and Artificial Intelligence (AI) are powering the applications we use, the decisions we make, and the decisions made about us. We have seen numerous examples of non-equitable outcomes, from facial recognition algorithms to recidivism algorithms, when they are designed without diversity in mind. Thus, we must take action to promote diversity among those in this field. A critical step in this work is understanding why some students who choose to study ML/AI later leave the field. While the persistence of diverse populations has been studied in engineering, there is a lack of research investigating factors that influence persistence in ML/AI. In this work, we present the advancement of a model of intentional persistence in ML/AI by surveying students in ML/AI courses. We examine persistence across demographic groups, such as gender, international student status, student loan status, and visible minority status. We investigate independent variables that distinguish ML/AI from other STEM fields, such as the varying emphasis on non-technical skills, the ambiguous ethical implications of the work, and the highly competitive and lucrative nature of the field. Our findings suggest that short-term intentional persistence is associated with academic enrollment factors such as major and level of study. Long-term intentional persistence is correlated with measures of professional role confidence. Unique to our study, we show that wanting your work to have a positive social benefit is a negative predictor of long-term intentional persistence, and women generally care more about this. We provide recommendations to educators to meaningfully discuss ML/AI ethics in classes and encourage the development of interpersonal skills to help increase diversity in the field.

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arXiv2023

"Just a little bit on the outside for the whole time": Social belonging confidence and the persistence of Machine Learning and Artificial Intelligence students

The growing field of machine learning (ML) and artificial intelligence (AI) presents a unique and unexplored case within persistence research, meaning it is unclear how past findings from engineering will apply to this developing field. We conduct an exploratory study to gain an initial understanding of persistence in this field and identify fruitful directions for future work. One factor that has been shown to predict persistence in engineering is belonging; we study belonging through the lens of confidence, and discuss how attention to social belonging confidence may help to increase diversity in the profession. In this research paper, we conduct a small set of interviews with students in ML/AI courses. Thematic analysis of these interviews revealed initial differences in how students see a career in ML/AI, which diverge based on interest and programming confidence. We identified how exposure and initiation, the interpretation of ML and AI field boundaries, and beliefs of the skills required to succeed might influence students' intentions to persist. We discuss differences in how students describe being motivated by social belonging and the importance of close mentorship. We motivate further persistence research in ML/AI with particular focus on social belonging and close mentorship, the role of intersectional identity, and introductory ML/AI courses.

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arXiv2023

User Perspectives on Branching in Computer-Aided Design

Branching is a feature of distributed version control systems that facilitates the ``divide and conquer'' strategy present in complex and collaborative work domains. Branching has revolutionized modern software development and has the potential to similarly transform hardware product development via CAD (computer-aided design). Yet, contrasting with its status in software, branching as a feature of commercial CAD systems is in its infancy, and little research exists to investigate its use in the digital design and development of physical products. To address this knowledge gap, in this paper, we mine and analyze 719 user-generated posts from online CAD forums to qualitatively study designers' intentions for and preliminary use of branching in CAD. Our work contributes a taxonomy of CAD branching use cases, an identification of deficiencies of existing branching capabilities in CAD, and a discussion of the untapped potential of CAD branching to support a new paradigm of collaborative mechanical design. The insights gained from this study may help CAD tool developers address design shortcomings in CAD branching tools and assist CAD practitioners by raising their awareness of CAD branching to improve design efficiency and collaborative workflows in hardware development teams.

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