Abstract
An increasing number of HCI researchers have embraced open science ideas, such as sharing data and analysis code. However, such practices are only meaningful when the shared data and code enable other researchers to reproduce and reuse the reported findings. To investigate the reproducibility of HCI research, we identified all CHI papers that have shared study data and analysis code, and attempted to reproduce the results. We were able to fully reproduce 49\% of the papers. We surveyed and interviewed authors, asking them to assess the reproducibility of their own work and to reflect on their motivations and obstacles in doing open science. We discuss what improves and hinders reproducibility and provide recommendations on how to increase reproducibility rates in HCI. While the value of replicability remains contested in HCI, we argue that the more modest goal of reproducibility is desirable.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems |
| Place of Publication | New York, USA |
| Publisher | Association for Computing Machinery |
| Publication date | 13 Apr 2026 |
| Pages | 1-16 |
| ISBN (Electronic) | 979-8-4007-2278-3/2026/04 |
| DOIs | |
| Publication status | Published - 13 Apr 2026 |
| Event | Conference on Human Factors in Computing Systems - Centre de Convencions Internacional de Barcelona., Barcelona, Spain Duration: 13 Apr 2026 → 17 Apr 2026 https://chi2026.acm.org/ |
Conference
| Conference | Conference on Human Factors in Computing Systems |
|---|---|
| Location | Centre de Convencions Internacional de Barcelona. |
| Country/Territory | Spain |
| City | Barcelona |
| Period | 13/04/2026 → 17/04/2026 |
| Internet address |
Keywords
- Reproducibility
- Open Science
- Metascience
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Honorable Mention CHI'26
Iarygina, O. (Recipient) & Mottelson, A. (Recipient), Apr 2026
Prize: Prizes, scholarships, distinctions
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