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Updated: Aug 13, 2026
06:48
Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment
Published on: June 25, 2019
Letter transpositions within and across morphemes
Kiel Christianson1, Rebecca L Johnson, Keith Rayner
1Department of Educational Psychology, University of Illinois at Urbana-Champaign, Champaign, IL 61820-6990, USA. kiel@uiuc.edu
Summary
Morpheme boundaries impact visual word recognition. Transpositions within morphemes aid naming, while those across morphemes do not, suggesting morphemes are key units in processing.
Area of Science:
- Psycholinguistics
- Cognitive Psychology
- Computational Linguistics
Background:
- Letter transposition errors are common in language.
- Understanding how readers process word structures, like morphemes, is crucial for explaining visual word recognition.
- Morpheme boundaries may influence how visual word recognition systems handle errors.
Purpose of the Study:
- To investigate the role of morpheme boundaries in visual word recognition.
- To determine if letter transpositions within or across morpheme boundaries affect naming latency differently.
- To examine the generalizability of these effects across different word types (compounds, pseudocompounds, derived words).
Main Methods:
- Conducted three masked-prime naming experiments.
- Compared priming effects of correctly spelled primes, primes with within-morpheme transpositions, and primes with across-morpheme transpositions.
- Used compound words, pseudocompounds, and derived words as targets.
Main Results:
- Primes with within-morpheme transpositions facilitated naming similarly to correctly spelled primes.
- Primes with across-morpheme transpositions did not facilitate naming more than primes with letter substitutions.
- These effects were consistent across compound words, pseudocompounds, and derived words.
Conclusions:
- Morpheme boundaries play a significant role in visual word recognition.
- The integrity of morphemes as processing units is important for efficient word recognition.
- Findings support models of visual word recognition that incorporate morphological structure.
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