Maze Made Easy: Better and easier measurement of incremental processing difficulty
Name
BoyceFutrellLevy2019.pdf
Description
Submitted version
Size
650.77 KB
Format
Adobe PDF
Checksum (MD5)
4f177f6f9ea3bf43b4e35090c70cb397
Author(s)
Boyce, Veronica
Futrell, Richard
Levy, Roger P
Date Issued
2020
Journal
Journal of Memory and Language
Publisher
Elsevier BV
Citation
Boyce, Veronica, Futrell, Richard and Levy, Roger P. 2020. "Maze Made Easy: Better and easier measurement of incremental processing difficulty." Journal of Memory and Language, 111.
Version
Original manuscript
Abstract
© 2019 Elsevier Inc. Behavioral measures of incremental language comprehension difficulty form a crucial part of the empirical basis of psycholinguistics. The two most common methods for obtaining these measures have significant limitations: eye tracking studies are resource-intensive, and self-paced reading can yield noisy data with poor localization. These limitations are even more severe for web-based crowdsourcing studies, where eye tracking is infeasible and self-paced reading is vulnerable to inattentive participants. Here we make a case for broader adoption of the Maze task, involving sequential forced choice between each successive word in a sentence and a contextually inappropriate distractor. We leverage natural language processing technology to automate the most researcher-laborious part of Maze – generating distractor materials – and show that the resulting A(uto)-Maze method has dramatically superior statistical power and localization for well-established syntactic ambiguity resolution phenomena. We make our code freely available online for widespread adoption of A-maze by the psycholinguistics community.
MIT Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/J.JML.2019.104082
