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Welcome to the Journal of Special Education Technology (JSET)
A publication of the Technology and Media Division of the Council for Exceptional Children

JSET Articles Index

Volume 25 Number 3

Using Technology to Support STEM Reading

Matthew H. Schneps, Jamie K. O’Keeffe, Amanda Heffner-Wong, and Gerhard Sonnert
Laboratory for Visual Learning
Harvard-Smithsonian Center for Astrophysics

Tasks in science, technology, engineering, and mathematics (STEM) are unusually varied because they target phenomena occurring in diverse domains and call upon a wide range of abilities to perform them. The fact that STEM tasks cover such a broad spectrum of abilities makes these fields uncharacteristically inclusive: Individuals with disabilities may perform well in STEM even if they face impairments in other academic domains. Despite this fact, people with executive function disorders face numerous challenges carrying out functions critically important for STEM, which often preclude the unique contributions that they could potentially make to these fields. For people with dyslexia, reading is an obvious challenge. In a typical college-level chemistry course, for example, students are assigned texts containing close to 1,000 pages, calling for the mastery of more than 300 specialized terms. Reading STEM content can be especially challenging because the text cannot be glossed over, but instead must be read closely, with attention to detail. Here, we describe how a technique we call Span-Limiting Tactile Reinforcement (SLTR) can help students with reading disabilities manage attention and working memory demands typically invoked in the close reading of text. SLTR facilitates close reading by reformatting the text into a single newsprint-like column with only a few words per line. The column of text is presented through a masking window in which the text is advanced manually as it is read. We implemented SLTR using STEM content on the Apple iPhone/iPod Touch and carried out experiments with eight college students with dyslexia and eight typical readers. Here, we present findings demonstrating the potential of this approach.