Webcam-based online eye-tracking for behavioral research
Experiments are increasingly moving online. This poses a major challenge for researchers who rely on in-lab techniques such as eye-tracking. Researchers in computer science have developed web-based eye-tracking applications (WebGazer; Papoutsaki et al., 2016) but they have yet to see them used in be...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Cambridge University Press
2021-11-01
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| Series: | Judgment and Decision Making |
| Subjects: | |
| Online Access: | http://journal.sjdm.org/21/210525/jdm210525.pdf |
| _version_ | 1797722620565651456 |
|---|---|
| author | Xiaozhi Yang Ian Krajbich |
| author_facet | Xiaozhi Yang Ian Krajbich |
| author_sort | Xiaozhi Yang |
| collection | DOAJ |
| description | Experiments are
increasingly moving online. This poses a major challenge for researchers who
rely on in-lab techniques such as eye-tracking. Researchers in computer science
have developed web-based eye-tracking applications (WebGazer; Papoutsaki et
al., 2016) but they have yet to see them used in behavioral research. This is
likely due to the extensive calibration and validation procedure, inconsistent
temporal resolution (Semmelmann and Weigelt, 2018), and the challenge of
integrating it into experimental software. Here, we incorporate WebGazer into
a JavaScript library widely used by behavioral researchers (jsPsych) and adjust
the procedure and code to reduce calibration/validation and improve the
temporal resolution (from 100-1000 ms to 20-30 ms). We test this procedure
with a decision-making study on Amazon MTurk, replicating previous in-lab
findings on the relationship between gaze and choice, with little degradation
in spatial or temporal resolution. This provides evidence that online
web-based eye-tracking is feasible in behavioral research. |
| first_indexed | 2024-03-12T09:51:09Z |
| format | Article |
| id | doaj.art-4df8599f5c77405c858dca35b8ca4f97 |
| institution | Directory Open Access Journal |
| issn | 1930-2975 |
| language | English |
| last_indexed | 2024-03-12T09:51:09Z |
| publishDate | 2021-11-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Judgment and Decision Making |
| spelling | doaj.art-4df8599f5c77405c858dca35b8ca4f972023-09-02T12:31:19ZengCambridge University PressJudgment and Decision Making1930-29752021-11-0116614851505Webcam-based online eye-tracking for behavioral researchXiaozhi YangIan KrajbichExperiments are increasingly moving online. This poses a major challenge for researchers who rely on in-lab techniques such as eye-tracking. Researchers in computer science have developed web-based eye-tracking applications (WebGazer; Papoutsaki et al., 2016) but they have yet to see them used in behavioral research. This is likely due to the extensive calibration and validation procedure, inconsistent temporal resolution (Semmelmann and Weigelt, 2018), and the challenge of integrating it into experimental software. Here, we incorporate WebGazer into a JavaScript library widely used by behavioral researchers (jsPsych) and adjust the procedure and code to reduce calibration/validation and improve the temporal resolution (from 100-1000 ms to 20-30 ms). We test this procedure with a decision-making study on Amazon MTurk, replicating previous in-lab findings on the relationship between gaze and choice, with little degradation in spatial or temporal resolution. This provides evidence that online web-based eye-tracking is feasible in behavioral research.http://journal.sjdm.org/21/210525/jdm210525.pdfeye-tracking attention online studies decision-making attentional drift diffusion model preferencesnakeywords |
| spellingShingle | Xiaozhi Yang Ian Krajbich Webcam-based online eye-tracking for behavioral research Judgment and Decision Making eye-tracking attention online studies decision-making attentional drift diffusion model preferencesnakeywords |
| title | Webcam-based online
eye-tracking for behavioral research |
| title_full | Webcam-based online
eye-tracking for behavioral research |
| title_fullStr | Webcam-based online
eye-tracking for behavioral research |
| title_full_unstemmed | Webcam-based online
eye-tracking for behavioral research |
| title_short | Webcam-based online
eye-tracking for behavioral research |
| title_sort | webcam based online eye tracking for behavioral research |
| topic | eye-tracking attention online studies decision-making attentional drift diffusion model preferencesnakeywords |
| url | http://journal.sjdm.org/21/210525/jdm210525.pdf |
| work_keys_str_mv | AT xiaozhiyang webcambasedonlineeyetrackingforbehavioralresearch AT iankrajbich webcambasedonlineeyetrackingforbehavioralresearch |