Trial reportAttention, perception & psychophysics2021
Examining group differences in between-participant variability in non-native speech sound learning.
Trial report in Attention, perception & psychophysics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Many studies on non-native speech sound learning report a large amount of between-participant variability. This variability allows us to ask interesting questions about non-native speech sound learning, such as whether certain training paradigms give rise to more or less between-participant variability. This study presents a reanalysis of Fuhrmeister and Myers (Attention, Perception, and Psychophysics, 82(4), 2049-2065, 2020) and tests whether different types of phonetic training lead to group differences in between-participant variability. The original study trained participants on a non-native speech sound contrast in two different phonological (vowel) contexts and tested for differences in means between a group that received blocked training (one vowel context at a time) and interleaved training (vowel contexts were randomized). No statistically significant differences in means were found between the two groups in the original study on a discrimination test (a same-different judgment). However, the current reanalysis tested group differences in between-participant variability and found greater variability in the blocked training group immediately after training because this group had a larger proportion of participants with higher-than-average scores. After a period of offline consolidation, this group difference in variability decreased substantially. This suggests that the type and difficulty of phonetic training (blocked vs. interleaved) may initially give rise to differences in between-participant variability, but offline consolidation may attenuate that variability and have an equalizing effect across participants. This reanalysis supports the view that examining between-participant variability in addition to means when analyzing data can give us a more complete picture of the effects being tested.
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