Although technology brings enormous potential for improving educational materials, it also represents an additional challenge for many students. Digital educational material is intended to improve learning by creating a rich and engaging environment for students, but there is evidence that the complex layout of this material is a barrier to some students, especially those with reading disabilities (RD). Thus, there is a vital need to relate what is known about individual learning differences in children to the design of educational materials, so that all children can benefit from them. The objective of this project is to develop a research methodology for understanding how students interact with digital educational materials. The principal investigator's approach will be to use eye movement technology to analyze how students look at "feature-enriched" text, text interspersed with ancillary visual features such as sidebars, photographs, and charts. By studying eye movement patterns during reading of feature-enriched text, thus determining how students look at the material, it should be possible to inform the creation of improved, customized layouts that appropriately match student needs. In addition, this work should help inform how to best instruct students on using these materials. In Phase 1 of the project, the investigators will establish the resources necessary for eye movement data collection and analysis. In Phase 2, they will design controlled, feature-enriched text stimulus materials which vary in reading level, layout complexity, and how features are cued within the text. In Phase 3, the principal investigator will collect eye movement and interview data from a sample of 30 7th-8th grade students with RD, as well as age-matched and reading-level-matched student groups, as they read the stimulus materials. In Phase 4, the investigator will evaluate eye movement patterns and test whether parameters which describe these patterns differ using within-subjects and between-group techniques. Data analysis will focus on validating the research methodology of using eye movement analysis as a means to understand how students read feature-enriched text.