We have recently published a new article reporting on eye-tracking as a way to measure differential change in Scientific Reports. The paper is free to download from this link and you can cite the paper as:
Fletcher-Watson, S., & Hampton, S. (2018). The potential of eye-tracking as a sensitive measure of behavioural change in response to intervention. Scientific Reports, doi:
Paper summary: One challenge to the development of effective supports for learning and growth in neurodevelopmental conditions is a lack of suitable outcome measures. Eye-tracking has been used widely to chart child development and detect differences between groups with and without a specific diagnosis. In this study, we investigated whether eye-tracking also has the potential to be used to tell thie difference between groups who did and did not receive an intervention. We tested whether eye-tracking could pick up subtle differences between two gorups of children, after one group had two weeks of access to a new iPad game. The game gives children a reward token when they tap a person, pictured as part of a cartoon scene. We measured how much time children spent looking at images taken from the game, and a selection of matched pictures from other games. We repeated the same eye-movement recording at the start of the study, and two weeks later. Children were either given an iPad to take home and play the game, or not, in the intervening period. The group who played the game looked more at people in pictures taken from the app, and also related photos. This pattern was only apparent though for more “complex” pictures containing people and other things to look at. This means that rewards (gold stars and pingy sounds) for tapping pictures in an iPad game actually change where children are looking too. This means that, if we are careful in choosing the right pictures, we might be able to use eye-tracking in studies which are invesitgating the effects of a new intervention. Eye-movements might be a way to tell if a new kind of support for a child is having a subtle but important effect on their behaviour.
In addition, you can download the dataset which was analysed for this paper from the University of Edinburgh datashare service here.
