Task effects on linguistic complexity and accuracy : a large-scale learner corpus analysis employing Natural Language Processing techniques

Alexopoulou, Theodora and Michel, Marije Cornelie and Murakami, Akira and Detmar, Meurers (2017) Task effects on linguistic complexity and accuracy : a large-scale learner corpus analysis employing Natural Language Processing techniques. Language Learning, 67 (Suppl.). pp. 180-208. ISSN 0023-8333

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Abstract

Large-scale learner corpora collected from online language learning platforms, such as the EF-Cambridge Open Language Database (EFCAMDAT), provide opportunities to analyze learner data at an unprecedented scale. However, interpreting the learner language in such corpora requires a precise understanding of tasks: Howdoes the prompt and input of a task and its functional requirements influence task-based linguistic performance? This question is vital for making large-scale task-based corpora fruitful for second language acquisition research. We explore the issue through an analysis of selected tasks in EFCAMDAT and the complexity and accuracy of the language they elicit.

Item Type:
Journal Article
Journal or Publication Title:
Language Learning
Additional Information:
This is the peer reviewed version of the following article:Alexopoulou, T., Michel, M., Murakami, A. and Meurers, D. (2017), Task Effects on Linguistic Complexity and Accuracy: A Large-Scale Learner Corpus Analysis Employing Natural Language Processing Techniques. Language Learning, 67: 180–208. doi:10.1111/lang.12232 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/lang.12232/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/3300/3304
Subjects:
?? educationlinguistics and languagelanguage and linguisticsdiscipline-based research ??
ID Code:
83702
Deposited By:
Deposited On:
19 Dec 2016 13:10
Refereed?:
Yes
Published?:
Published
Last Modified:
18 Feb 2024 00:47