Predictors of L2 word learning accuracy: A big data investigation.
- Elise Hopman, Department of Psychology , University of Wisconsin - Madison, Madison, Wisconsin, United States
- Bill Thompson, Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands
- Joseph Austerweil, Psychology, University of Wisconsin - Madison, Madison, Wisconsin, United States
- Gary Lupyan, Department of Psychology, University of Wisconsin - Madison, Madison, Wisconsin, United States
AbstractWhat makes some words harder to learn than others in a second language? Although some robust factors have been identified based on small scale experimental studies, many relevant factors are difficult to study in such experiments due to the amount of data necessary to test them. Here, we investigate what factors affect the ease of learning of a word in a second language using a large data set of users learning English as a second language through the Duolingo mobile app. In a regression analysis, we test and confirm the well-studied effect of cognate status on word learning accuracy. Furthermore, we find significant effects for both cross-linguistic semantic alignment and English semantic density, two novel predictors derived from large scale distributional models of lexical semantics. Finally, we provide data on several other psycholinguistically plausible word level predictors. We conclude with a discussion of the limits, benefits and future research potential of using big data for investigating second language learning.
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