Many bidialectal children grow up speaking a variety (e.g. a regional dialect) that differs from the variety in which they subsequently acquire literacy. Previous computational simulations and artificial literacy learning experiments with adults demonstrated lower accuracy in reading contrastive words for which dialect variants exist compared to non-contrastive words without dialect variants. At the same time, exposure to multiple varieties did not affect learners’ ability to phonologically decode untrained words; in fact, longer literacy training resulted in a benefit from dialect exposure as competing variants in the input may have increased reliance on grapheme-phoneme conversion. However, these previous experiments interleaved word learning and reading/spelling training, yet children typically acquire substantial oral language knowledge prior to literacy training. Here we used artificial literacy learning with adults to examine whether the previous findings replicate in an ecologically more valid procedure where word learning precedes literacy training. We also manipulated training conditions to explore interventions thought to be beneficial for literacy acquisition, such as providing explicit social cues for variety use and literacy training in both varieties. Our findings replicated the reduced accuracy for reading contrastive words in those learners who had successfully acquired the dialect variants prior to literacy training. This effect was exacerbated when literacy training also included dialect variation. Crucially, although no benefits from the interventions were found, dialect exposure did not affect reading and spelling of untrained words suggesting that phonological decoding skills can remain unaffected by the existence of multiple word form variants in a learner’s lexicon.
|Number of pages||37|
|Journal||Journal of Experimental Psychology: Learning Memory and Cognition|
|Early online date||13 Dec 2021|
|Publication status||E-pub ahead of print - 13 Dec 2021|
- Dialect exposure
- Literacy learning
- Artifical script