Controlling the spatial dimensions of visual stimuli in online experiments

• Published in: Journal of vision (Charlottesville, Va.) Vol. 21; no. 8; p. 19
• Main Author: Brascamp, Jan W.
• Format: Journal Article
• Language: English
• Published: The Association for Research in Vision and Ophthalmology 19.08.2021
• Subjects: Methods
• ISSN: 1534-7362; 1534-7362
• DOI: 10.1167/jov.21.8.19

There are clear benefits to using an online environment for human subjects' research, for instance, rapid data collection and access to a diverse body of potential participants. One distinct drawback of online environments as compared to laboratory environments is the relative lack of control over experiment conditions. For research into human vision, a specific concern is the relative lack of control over angular stimulus dimension in an online setting. This paper examines three approaches to estimating a participant's viewing distance online, and quantifies the magnitude of the error in angular stimulus size associated with each method. For each method, the average expected error is smaller than 20% of the intended stimulus size, and for the best method it is close to 10%. This paper provides a discussion of the benefits and drawbacks of each of the three methods, as well as parameter values and computer code that will facilitate the use of these methods in future online studies.There are clear benefits to using an online environment for human subjects' research, for instance, rapid data collection and access to a diverse body of potential participants. One distinct drawback of online environments as compared to laboratory environments is the relative lack of control over experiment conditions. For research into human vision, a specific concern is the relative lack of control over angular stimulus dimension in an online setting. This paper examines three approaches to estimating a participant's viewing distance online, and quantifies the magnitude of the error in angular stimulus size associated with each method. For each method, the average expected error is smaller than 20% of the intended stimulus size, and for the best method it is close to 10%. This paper provides a discussion of the benefits and drawbacks of each of the three methods, as well as parameter values and computer code that will facilitate the use of these methods in future online studies.