  Predicting a reader's rating of text quality is a challenging task that
involves estimating different subjective aspects of the text, like structure,
clarity, etc. Such subjective aspects are better handled using cognitive
information. One such source of cognitive information is gaze behaviour. In
this paper, we show that gaze behaviour does indeed help in effectively
predicting the rating of text quality. To do this, we first model text quality
as a function of three properties - organization, coherence and cohesion. Then,
we demonstrate how capturing gaze behaviour helps in predicting each of these
properties, and hence the overall quality, by reporting improvements obtained
by adding gaze features to traditional textual features for score prediction.
We also hypothesize that if a reader has fully understood the text, the
corresponding gaze behaviour would give a better indication of the assigned
rating, as opposed to partial understanding. Our experiments validate this
hypothesis by showing greater agreement between the given rating and the
predicted rating when the reader has a full understanding of the text.
