Research

At Denison University, I run the Language & Visual Cognition Lab

Research Summary:
The average, college-educated adult reads at a rate of 300-400 wpm, or 5-6 words every second. Reading at this speed is not trivial—it requires careful eye movement planning coupled with rapid visual perception and finely honed linguistic skills. When these processes work together in concert, the product is a highly efficient reader. Understanding how this level of efficiency is achieved is the theme that unites the different branches of my research program. My research seeks to understand the ways in which the cognitive system is flexible and adaptive, and how the processes associated with word identification, reading comprehension, and visual perception more generally can be adjusted to a given person’s individual set of cognitive and linguistic skills, or to specific task demands, to maximize the efficiency of the cognitive system. My research focuses on questions like:

  • Why do skilled readers activate the sounds of their language when reading silently?
  • How do readers maximize efficiency in the face of sometimes massive ambiguity?
  • In what ways does the reading process flexibly adapt to align with a given reader’s specific set of linguistic skills?

To address these questions, I primarily use eye tracking, but also other behavioral paradigms (e.g., reaction time, response accuracy) to measure the effects of specific linguistic and visual manipulations on readers’ ongoing word identification and comprehension, and use distributional analyses (e.g., survival analysis) and machine learning techniques (e.g., cluster analysis) to determine how individual cognitive and linguistic skills or specific task demands shape and alter the reading process. Within this larger framework, the two main branches of my research program investigate the functions of phonological (sound) information during silent reading (including developmental changes) and the cues and strategies readers use to make sense of language that is often massively ambiguous.

 

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