Prediction and preview strongly affect reading times but not skipping during natural reading

Abstract

In a typical text, readers look much longer at some words than at others and fixate some words multiple times, while skipping others altogether. Historically, researchers explained this variation via low-level visual or oculomotor factors, but today it is primarily explained in terms of cognitive factors, such as how well word identity can be predicted from context or discerned from parafoveal preview. While the existence of these effects has been well established in experiments, the relative importance of prediction, preview and low-level factors for eye movement variation in natural reading is unclear. Here, we address this question in three large datasets (n=104, 1.5 million words), using a deep neural network and Bayesian ideal observer to model linguistic prediction and parafoveal preview from moment to moment in natural reading. Strikingly, neither prediction nor preview was important for explaining word skipping - the vast majority of skipping was explained by a simple oculomotor model. For reading times, by contrast, we found strong but independent contributions of both prediction and preview, with effect sizes matching those from controlled experiments. Together, these results challenge dominant models of eye movements in reading by showing that linguistic prediction and parafoveal preview are not important determinants of word skipping.