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Exploring the Potential of Online Webcam-based Eye Tracking in Decision-Making Research and Influence Factors on Data Quality

Schneegans, Tim; Bachman, Matthew D.; Huettel, Scott A.; Heekeren, Hauke

Abstract (englisch):

Recent developments of open-source online eye-tracking algorithms suggests that they may be ready for use in online studies, thereby overcoming the limitations of in-lab eye-tracking studies. However, to date there have been limited tests of the efficacy of online eye-tracking for decision-making and cognitive psychology. In this online study, we explore the potential and the limitations of online eye-tracking tools for decision-making research using the webcam-based open-source library Webgazer (Papoutsaki et al., 2016). Our study had two aims. For our first aim we assessed different variables that might affect the quality of eye-tracking data. In our experiment (N = 210) we measured a within-subjects variable of adding a provisional chin rest and a between-subjects variable of corrected vs uncorrected vision. Contrary to our hypotheses, we found that the chin rest had a negative effect on data quality. In accordance with out hypotheses, we found lower quality data in participants who wore glasses. Other influence factors are discussed, such as the frame rate. For our second aim (N = 44) we attempted to replicate a decision-making paradigm where eye-tracking data was acquired using offline means (Amasino et al., 2019). ... mehr

DOI: 10.31234/
Zitationen: 3
Zugehörige Institution(en) am KIT Institut für Telematik (TM)
Institut für Wirtschaftsinformatik und Marketing (IISM)
Publikationstyp Forschungsbericht/Preprint
Publikationsdatum 04.10.2021
Sprache Englisch
Identifikator KITopen-ID: 1000140318
Schlagwörter data quality, human-computer-interaction, intertemporal discounting, multi-attribute choice, online-studies, research methods
Nachgewiesen in Dimensions
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