Article published in:
The Mental Lexicon
Vol. 14:3 (2019) ► pp. 333–356

Predictors of second language English lexical recognition

Further insights from a large database of second language lexical decision times

| Victoria University of Wellington
| Georgia State University
| Duolingo
In this study we analyze a large database of lexical decision times for English content words made by speakers of English as an additional language residing in the United States. Our first goal was to test whether the use of statistical measures better able to model variation associated with participants and items would replicate findings of a previous analysis of this data (Berger, Crossley, & Skalicky, 2019). Our second goal was to determine whether variables related to experiences using and learning English would interact with linguistic features of the target words. Results from our statistical analysis suggest affirmative answers to both of these questions. First, our results included significant effects for linguistic features related to contextual diversity and contextual distinctiveness, providing a replication of findings from the original study in that words appearing in more textual and lexical contexts were responded to quicker. Second, a measure of length of English learning and a measure of daily English use interacted with a measure of orthographic similarity. Our study provides further evidence regarding how a large, crowdsourced database can be used to obtain a better understanding of second language lexical recognition behavior and provides suggestions for further research.
Keywords: second language, crowdsource, lexical decision task, lexical recognition, linguistic features, lexical semantics
Article outline
  • L2 lexical processing and development
  • Linguistic features and L2 lexical processing
    • Contextual diversity and distinctiveness
    • Neighborhoods
    • Word concreteness
  • The Berger at al. (2019) Study
  • Research questions
  • Method
    • Online data collection
    • Language use survey
    • Data preparation and variable selection
      • Linguistic features
      • Language use survey answers
      • Coefficient of variation
      • Accuracy and reaction time outliers
      • Multicollinearity
    • Statistical analysis
  • Results
    • Participant data
    • Lexical decision time data
    • Linear mixed effects regression model: Reaction times
  • Discussion
    • Significant interactions with OLD20
  • Conclusion
  • Notes
  • References
Published online: 13 May 2020
https://doi.org/10.1075/ml.19028.ska
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