Literacy Education: Mobile Eye-Tracking Software and Reading Rate

Recently a few stories have been discussing the Samsung Galaxy S IV’s eye-tracking function that allows users to scroll through pages using their eyes. There was some concern raised about the privacy implications of this technology if it did, indeed, track eye movement. However, it appears that such concerns are somewhat unwarranted. Mashable reports that the eye-scrolling feature relies more on “facial recognition and tilt” and can pause video when your head turns away. Eye-tracking this is not–or at least, a very primitive form of eye-tracking.

Eye-Tracking and Reading Research

So it’s a false alarm. But the idea of eye-tracking software is not too far-fetched, as it appears Swedish Tobii may be developing other forms of the technology. The issue of eye tracking could have multiple uses, and at some point someone is going to suggest it can cure reading problems. Eye movement studies in reading date at least back to Huey, almost a hundred years, although thankfully we’ve moved on from the “dark ages” form of reading research. Huey tracked eye movement by placing a “cup” made of plaster of Paris on the cornea (numbing the eye with cocaine to alleviate discomfort) and attaching a thin aluminum “pointer” to the cup, which then transferred the movements to paper. Samsung’s limited eye movement technology just takes your picture.

Reading Rate and Comprehension

Yet even if/when eye tracking can actually do more, its implications for literacy need to be considered in the context of research. Eye tracking should be able to determine reading rate, but there is no one single optimal rate of reading, especially silent reading, for all students and all texts and all tasks. As Hiebert, Samuels, & Rasinski explain, if we define silent reading as comprehension (as opposed to only the movement of the eye across the page), “rate and comprehension are inseparable” (p. 4) . If future eye-tracking programs are developed to help parents and teachers measure student reading rates, those rates need to consider comprehension factors and not just words per minute. Reading rate needs to be considered in relation to the complexity of the text and the purpose for reading. And this isn’t just a good idea, it’s now been institutionalized by the Common Core State Standards. The CCSS recognize that text complexity needs to be a part of the conversation we are having about reading, and their model of complexity takes into account qualitative, quantitative, reader-related, and task-related factors. If eye-tracking software tells us our student reading rates, we need to be able to use the information responsibly, taking into consideration the variables that affect such a measurement.

How Digital Technology Can Help

Yet I’m not just advocating caution. Samsung’s move towards eye-tracking and future eye-tracking software can be a good thing for education. Hiebert et al. explain in one of their studies that student participation in a sustained digital program for literacy education can improve student silent reading performance because the digital environment  has the “ability to instantaneously change the difficulty of the text in response to comprehension performances [which] allow[s] for precision in scaffolding” (p. 15). In other words, the digital component can approximate the student’s zone of proximal development (ZPD) for silent reading, which can guide the student’s development in a measured fashion.This can improve the learning experience for many students, especially, according to Hiebert et al., low achievers in reading (p. 17).

Wherever we are headed in education, technology will play a role–but that role should be based on what we’ve learned from research. Otherwise, we risk falling prey to the greed of others, proffering software with no empirical basis and potential damaging effects for our children’s education.

I am indebted to Dr. Carol Hopkins of Purdue University for the majority of the ideas in this post. Our discussions pushed me to consider  the possible commercial ramifications of the eye-tracking software and to review Hiebert et al.’s work on comprehension and rate.

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