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In:New Frontiers and Connections in Second Language Acquisition: Selected Proceedings of the 17th Generative Approaches to Second Language Acquisition (GASLA-17) Conference
Edited by Tania Ionin and Silvina Montrul
[Language Acquisition and Language Disorders 71] 2026
► pp. 279–301

The importance of individual data in L3 acquisition

A reanalysis of Mitrofanova, Leivada, and Westergaard (2023)

 | Indiana University
 | Indiana University
 | Indiana University
 | University of Hawai‘i
 | Indiana University
This content is being prepared for publication; it may be subject to changes.
Abstract
We re-examine a recent contribution by Mitrofanova, Leivada, and Westergaard (2023) to the debate on wholesale vs. property-by-property transfer in L3 acquisition. They argued that results from their artificial-language experiment support the Linguistic Proximity Model (LPM) because in three of four conditions, the L3-Russian-Norwegian group’s mean acceptance fell ‘between’ those of the L2-Russian and L2-Norwegian groups. Our reanalysis of their original data reveals that those ‘between’ results stem from bimodal/continuous distributions, not from unimodal distributions centering around a ‘between’ result. We next inspected each individual’s cross-conditional response patterns, grouping them into response profiles, to test three logically possible versions of LPM-generated predictions. Qualitative analyses show all three fail. We end with a methodological discussion of testing for transfer in L3 models.
Article outline
  • 1.Introduction
  • 2.Mitrofanova et al. (2023)
    • 2.1Method
    • 2.2Predictions: Distinguishing three versions of LPM-based predictions
    • 2.3Results
  • 3.Reanalysis of Mitrofanova et al. (2023)
    • 3.1Group-level results
    • 3.2Individual-level results
  • 4.General discussion
  • 5.Summary and conclusion
  • Acknowledgments
  • Notes
  • References
References (25)
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