Research

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Reading and Eye Movements 

On the outside, the reader has rotated his eyes only a few millimeters… But on the inside, there has been a rapid succession of intricate events. Clearly, the succession could only be the product of a complex information processing system… It contains components that are asked to perform amazing feats with amazing rapidity, and precisely in concert.

[Gough, P. B. (1972). One second of reading. In J. F. Kavanagh & I. G. Mattingly (Eds.), Reading by ear and eye (pp. 331-358). Cambridge, MA: MIT Press.]

Reading is a complex skill that provides a rich domain for studying language, attention, vision and memory. I hope to understand how ongoing cognitive processes influence when and where we move our eyes during reading (i.e., the “eye-mind link”), and I am using eye tracking, computational modeling, EEG/ERPs, and distributional analyses to understand eye movement control and reading expertise. To extend this line of research, I have been exploring a variety of related phenomena, including individual differences in reading, lexical ambiguity resolution, rereading, bilingualism and differences across writing systems, word frequency and contextual predictability effects, and the impact of visual aspects of the text (i.e., typography, inter-word spacing). A current goal of the lab is to further explore these topics via the co-registration of eye movements and EEG/ERPs.

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Perception and Problem-Solving in chess (and other domains of expertise)

“When you see a good move, look for a better one” [Grandmaster Emanuel Lasker]

Chess is similar to reading because it involves complex cognitive processing that is perfected over thousands of hours of experience with familiar visual configurations. It is an excellent domain for studying how visual expertise develops, and for discovering domain-general characteristics of visual expertise (Reingold & Sheridan, 2011). For example, chess experts (but not novices) are able to rapidly focus on task-relevant features of a chessboard while ignoring irrelevant features (Sheridan & Reingold, 2014). In addition, building on prior work on problem-solving in chess (e.g., Bilalić, McLeod, & Gobet, 2008), my work has explored implicit biases in decision-making, with the goal of understanding why the presence of a familiar good solution can prevent chess players from discovering an even better solution (Sheridan & Reingold, 2013). A future goal of the lab is to further explore these topics in the context of other domains of expertise (proofreading, music reading, medical expertise, etc.).

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Learning, Memory & Awareness

“We can know more than we can tell” [Michael Polanyi]

Skilled performance can reflect implicit knowledge that experts are not aware of or not able to verbalize (Reingold & Sheridan, 2011). My own work has used a combination of eye-movement monitoring and behavioural tasks to study learning, memory and awareness in the context of reading (e.g., Sheridan & Reingold, 2012) and recognition memory (e.g., Sheridan & Reingold, 2011).

[Sample stimuli from  Sheridan & Reingold (2012)’s study of perceptual specificity effects during reading.]

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