AN EXTENSION OF SOLOVYEVA AND DEKEYSER (2018)
Published online by Cambridge University Press: 22 November 2019
I investigated the trajectory of processing variability, as measured by coefficient of variation (CV), using an intentional word learning experiment and reanalyzing published eye-tracking data of an incidental word learning study (Elgort et al., 2018). In the word learning experiment, native English speakers (N = 35) studied Swahili-English word pairs (k = 16) before performing 10 blocks of animacy judgment tasks. Results replicated the initial CV increase reported in Solovyeva and DeKeyser (2018) and, importantly, captured a roughly inverted U-shaped development in CV. In the reanalysis of eye-tracking data, I computed CVs based on reading times on the target and control words. Results did not reveal a similar inverted U-shaped development over time but suggested more stable processing of the high-frequency control words. Taken together, these results uncovered a fuller trajectory in CV development, differences in processing demands for different aspects of word knowledge, and the potential use of CV with eye-tracking research.
This piece of research is supported by the Second Language Studies PhD Program at Michigan State University. I would like to thank the two anonymous reviewers for their insightful feedback that has helped strengthened the paper. I would also like to thank Drs. Aline Godfroid, Shawn Loewen, and Patti Spinner for their constructive comments on earlier drafts of this manuscript. I must also thank Lizz Huntley and my peers on LLT 864 Second Language Psycholinguistics for their ideas. Audience members in my talk at SLRF 2018 in Montreal and members in our Daily Writing Slacker group offered very useful comments as well. All errors, however, remain my own. Finally, I am very grateful for the sharing of published data by Dr. Irina Elgort and colleagues.
The experiment in this article earned Open Data and Open Materials badges for transparent practices. The materials are available at https://osf.io/2ta7m/.