Pupils Dilate More to Harder Vocabulary Words than Easier Ones

Ishanti Gangopadhyay, Daniel Fulford, Kathleen Corriveau, Jessica Mow, Pearl Han Li, Sudha Arunachalam

Research output: Contribution to journalArticlepeer-review


Understanding cognitive effort expended during assessments is essential to improving efficiency, accuracy, and accessibility within these assessments. Pupil dilation is commonly used as a psychophysiological measure of cognitive effort, yet research on its relationship with effort expended specifically during language processing is limited. The present study adds to and expands on this literature by investigating the relationships among pupil dilation, trial difficulty, and accuracy during a vocabulary test. Participants (n = 63, Mage = 19.25) completed a subset of trials from the Peabody Picture Vocabulary Test while seated at an eye-tracker monitor. During each trial, four colored images were presented on the monitor while a word was presented via audio recording. Participants verbally indicated which image they thought represented the target word. Words were categorized into Easy, Medium, and Hard difficulty. Pupil dilation during the Medium and Hard trials was significantly greater than during the Easy trials, though the Medium and Hard trials did not significantly differ from each other. Pupil dilation in comparison to trial accuracy presented a more complex pattern, with comparisons between accurate and inaccurate trials differing depending on the timing of the stimulus presentation. These results present further evidence that pupil dilation increases with cognitive effort associated with vocabulary tests, providing insights that could help refine vocabulary assessments and other related tests of language processing.

Original languageEnglish (US)
Article numbere13446
JournalCognitive Science
Issue number4
StatePublished - Apr 2024


  • Eye-tracking
  • Task-evoked Pupillary response
  • Vocabulary

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Cognitive Neuroscience
  • Artificial Intelligence


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