2020
DOI: 10.30661/afinlavk.89453
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Ensikielen tunnistamisen merkityksestä suullisen kielitaidon arvioinnissa Yleisissä kielitutkinnoissa

Abstract: In this paper, we present a multidisciplinary study addressing fairness in the speaking test in a high-stakes language proficiency test in Finnish, National Certificates of Language Proficiency. The background of the research lies in studies on language assessment and (reversal) linguistic stereotyping and language attitudes. The focus L1 groups were Thai, Estonian, Finland Swedish, Arabic and Russian. Altogether 49 speech samples of test takers of these L1s were rated on a digital platform by 44 raters of the… Show more

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“…Still, I wonder if neurolinguistic research has something to say about this. I think this could be important when not just describing, for example, what happens when raters' highstakes decisions about individuals' language proficiency are based on the accents these individuals have and not only on intelligibility, complexity, accuracy, and fluency (see, e.g., Halonen et al, 2020), but also work towards changing such biases. Having to passively accept that an individual with a strong accent associated with lower proficiency, counter to one's prediction, performs better than our prediction tells us suggests a higher malleability of the model based on such stereotypes.…”
Section: Dmitri Leontjevmentioning
confidence: 99%
“…Still, I wonder if neurolinguistic research has something to say about this. I think this could be important when not just describing, for example, what happens when raters' highstakes decisions about individuals' language proficiency are based on the accents these individuals have and not only on intelligibility, complexity, accuracy, and fluency (see, e.g., Halonen et al, 2020), but also work towards changing such biases. Having to passively accept that an individual with a strong accent associated with lower proficiency, counter to one's prediction, performs better than our prediction tells us suggests a higher malleability of the model based on such stereotypes.…”
Section: Dmitri Leontjevmentioning
confidence: 99%