Affiliation:
1. University for Foreigners of Perugia
Abstract
Abstract
In this position paper, I argue that proficiency-rated learner corpora should gain a more prominent role in
data-driven learning (DDL). With specific reference to DDL, proficiency-rated learner corpora can provide typical, atypical and
erroneous target language data at different levels of proficiency, which can be meaningfully used in the design of learning
activities. This makes them pivotal in expanding the scope of DDL to include mid- and lower-level proficiency learners more
extensively. Although the field of learner corpus research has been promoting learner corpus use in DDL for a long time, only a
small fraction of DDL studies make use of a learner corpus. As a contribution to overcome this hiatus, I will demonstrate how
using a specific proficiency-rated learner corpus (i.e., the CELI corpus; Spina et al., 2022, 2023) can enrich the design of DDL activities, making
them more adaptable to a wider range of learner needs.
Publisher
John Benjamins Publishing Company
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