Validation of an open source, remote web-based eye-tracking method (WebGazer) for research in early childhood

Exploration of factors affecting webcam-based automated gaze coding

Online experiments have been transforming the field of behavioral research, enabling researchers to increase sample sizes, access diverse populations, lower the costs of data collection, and promote reproducibility. The field of developmental psychology increasingly exploits such online testing approaches. Since infants cannot give explicit behavioral responses, one key outcome measure is infants' gaze behavior. In the absence of automated eyetrackers in participants' homes, automatic gaze classification from webcam data would make it possible to avoid painstaking manual coding. However, the lack of a controlled experimental environment may lead to various noise factors impeding automatic face detection or gaze classification. We created an adult webcam dataset that systematically reproduced noise factors from infant webcam studies which might affect automated gaze coding accuracy. We varied participants' left-right offset, distance to the camera, facial rotation, and the direction of the lighting source. Running two state-of-the-art classification algorithms (iCatcher+ and OWLET) revealed that facial detection performance was particularly affected by the lighting source, while gaze coding accuracy was consistently affected by the distance to the camera and lighting source. Morphing participants' faces to be unidentifiable did not generally affect the results, suggesting facial anonymization could be used when making online video data publicly available, for purposes of further study and transparency. Our findings will guide improving study design for infant and adult participants during online experiments. Moreover, training algorithms using our dataset will allow researchers to improve robustness and allow developmental psychologists to leverage online testing more efficiently.

False belief understanding in deaf children: what are the difficulties?

Children with cochlear implants (CIs) demonstrate proficiency in verbal-story elicited-response (VS-ER) false-belief tasks, such as the Sally & Ann task, at a similar age as typically developing hearing children. However, they face challenges in non-verbal spontaneous-response (NV-SR) false-belief tasks, measured via looking times, which hearing infants typically pass by around 2 years of age, or earlier. The purpose of the present study was to examine whether these difficulties remain in a non-verbal-story elicited-response (NVS-ER) false-belief task, in which children are offered the opportunity to provide an elicited response to a non-verbal-story task. A total of thirty 4- to 8-year-old children with CI-s and hearing children completed three different kinds of false-belief tasks. The results showed that children with CI-s performed above chance level on the verbal task (i.e., VS-ER task), but not on the two non-verbal tasks, (i.e., NVS-ER and NV-SR tasks). The control group of typically developing hearing children performed above chance on all three kinds of tasks (one-tailed significance level). Our findings highlight the importance of external narrative support for children with CIs in tasks that involve mental perspective-taking, and specifically predicting actions based on false beliefs.