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Reading in digital environments can be very distracting. Using eye-tracking technology, we investigate if text readability affects distraction rate, eye movements, and reading comprehension in a visually distracting digital environment. We compared an easy-to-read text and a hard-to-read text on both first language English (L1) readers and second language English (L2) readers. Text readability was measured using the standard readability formulas such as the Flesch-Kincaid Grade level. Results show that text readability does cause different eye movements and produce reading comprehension results that deviate from what is normally expected. Readers are affected more by the distractions when reading easy-to-read text compared to when reading hard-to-read text. Furthermore, L2 readers are affected more than L1 readers. These findings can be used in the design of eLearning materials when distractions cannot be overcome

We construct fuzzy signature neural networks where fuzzy signatures replace hidden neurons in a neural network similar to a radial basis function neural network. We investigated the properties of a naïve and a principled approach to fuzzy signature const

We investigate factors affecting reading and overall comprehension of the underlying meaning and concepts within a piece of text using eye movements. Our objective is to identify eye movement measures that will predict reading comprehension, and intend to

We investigate eye movement measures and methods for predicting reading comprehension. This builds on previous work on factors affecting reading comprehension, namely perceived familiarity with the text content. We further investigate answer-seeking behav