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Eye Tracking in the Wild: the Good, the Bad and the Ugly
Author(s) -
Otto Lappi
Publication year - 2015
Publication title -
journal of eye movement research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.25
H-Index - 20
ISSN - 1995-8692
DOI - 10.16910/jemr.8.5.1
Subject(s) - naturalness , computer science , terminology , fidelity , naturalism , point (geometry) , human–computer interaction , eye tracking , tacit knowledge , spurious relationship , cognitive science , artificial intelligence , psychology , epistemology , machine learning , knowledge management , linguistics , physics , geometry , mathematics , quantum mechanics , telecommunications , philosophy
Modelling human cognition and behaviour in rich naturalistic settings and under conditions of free movement of the head and body is a major goal of visual science. Eye tracking has turned out to be an excellent physiological means to investigate how we visually interact with complex 3D environments, real and virtual. This review begins with a philosophical look at the advantages (the Good) and the disadvantages (the Bad) in approaches with different levels of ecological naturalness (traditional tightly controlled laboratory tasks, low- and high-fidelity simulators, fully naturalistic real-world studies). We then discuss in more technical terms the differences in approach required “in the wild”, compared to “received” lab-based methods. We highlight how the unreflecting application of lab-based analysis methods, terminology, and tacit assumptions can lead to poor experimental design or even spurious results (the Ugly). The aim is not to present a “cookbook” of best practices, but to raise awareness of some of the special concerns that naturalistic research brings about. References to helpful literature are provided along the way. The aim is to provide an overview of the landscape from the point of view of a researcher planning serious basic research on the human mind and behaviour

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