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On the Computational Reproducibility of Human-Computer Interaction

OpenAlex
Authors: Olga Iarygina, Kasper Anders Søren Hornbæk, Aske ; id_orcid 0000-0003-1827-8513 Mottelson

Year

2026

Paper ID

29962

Status

Peer-reviewed

Abstract Read

~2 min

Abstract Words

140

Citations

1

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.

Why This Paper Matters

  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2026 reference point for readers tracking recent quantum research.
  • An increasing number of HCI researchers have embraced open science ideas, such as sharing data and analysis code.

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External citation index: OpenAlex citation signal • updated 2026-10-22 06:46:25

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