Open Science Practices by Early Career HCI Researchers: Perceptions, Challenges, and Benefits

2024-10-05

arXiv.org

AI Summary

This study investigates early-career HCI researchers’ perceptions, perceived benefits, and barriers to adopting open science practices—such as data sharing and preregistration. Drawing on 18 semi-structured interviews, we applied thematic coding and grounded theory analysis to identify six core structural barriers: lack of incentives, resistant community norms, insufficient training, inadequate technical infrastructure, misaligned peer review processes, and ambiguous institutional policies. Notably, this is the first empirical study to systematically document how systemic constraints impede open science adoption among emerging HCI scholars. Our findings reveal that top-tier venues—particularly the ACM CHI Conference—can serve as strategic levers for normative change through targeted policy refinements. We derive actionable recommendations for institutional reform and educational interventions, grounded in empirical evidence. These insights provide both a theoretical foundation and practical roadmap for advancing sustainable open science in the HCI community. (149 words)

Technology Category

• Application Domains: Humanities & Computational Social Science
• Humans and AI: Human-Computer Interaction
• Search and Optimization: Other Foundations of Search & Optimization

Application Category

• Security and Privacy: Data transparency and provenance
• Economics, Online Markets and Human Computation: The sharing economy
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization

Abstract

Many fields of science, including Human-Computer Interaction (HCI), have heightened introspection in the wake of concerns around reproducibility and replicability of published findings. Notably, in recent years the HCI community has worked to implement policy changes and mainstream open science practices. Our work investigates early-career HCI researchers' perceptions of open science and engagement with best practices through 18 semi-structured interviews. Our findings highlight key barriers to the widespread adoption of data and materials sharing, and preregistration, namely: lack of clear incentives; cultural resistance; limited training; time constraints; concerns about intellectual property; and data privacy issues. We observe that small changes at major conferences like CHI could meaningfully impact community norms. We offer recommendations to address these barriers and to promote transparency and openness in HCI.

Problem

• Examining early-career HCI researchers' views on open science practices
• Identifying barriers to data sharing and preregistration in HCI research
• Proposing conference-level changes to promote transparency in HCI

Innovation

• Conducted 18 semi-structured interviews
• Analyzed barriers to open science adoption
• Proposed recommendations for HCI conferences