oUC6: Many Eyes – A many-analysts approach to assessing heterogeneity in eye-tracking analysis pipelines
Amélie Gourdon-Kanhukamwe, Yu Yang Chou
Many-analysts studies (Silberzahn et al., 2018) – whereby multiple analysis teams independently analyse single datasets to test predefined hypotheses – demonstrate the existence and effects of the so-called “garden of forking paths” (Gelman & Loken, 2014). Eye-tracking-based research could greatly benefit from a many-analysts approach, as validity in the field is threatened by the abundance of independent and dependent variables available for hypothesis testing (Orquin & Holmqvist, 2017). We therefore propose a many-analysts study using a visual attention and reading dataset to investigate the heterogeneity in pre-processing and analysing eye-tracking data. In this unconference, we will discuss the progress of the Stage 1 Registered Report being developed for the project, creating opportunities to receive feedback from the community, as well as invite further colleagues to join the project.
Unconference
Track 4 (Thur)