Theorising in HCI using Causal Models

要旨

Although the literature on Human-Computer Interaction (HCI) catalogues many theories, it offers surprisingly few tools for theorising. This paper critiques dominant approaches to engaging with theory and proposes a working model for theorising in HCI. We then present graphical causal modelling as an effective theorising tool. This includes a step-by-step guide to building causal models and examples of their use in different stages of the research process. We explain how causal models help develop method-agnostic representations of research problems using directed acyclic graphs, identify potential confounders, and construct alternative interpretations of data. Finally, we discuss their limitations and challenges for adoption by the HCI community.

受賞
Honorable Mention
著者
Eduardo Velloso
University of Sydney, Sydney, New South Wales, Australia
Kasper Hornbæk
University of Copenhagen, Copenhagen, Denmark
DOI

10.1145/3706598.3713789

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713789

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: HCI Methods

G416+G417
7 件の発表
2025-04-28 20:10:00
2025-04-28 21:40:00
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