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标题:Task Effects on Linguistic Complexity and Accuracy: A Large-Scale Learner Corpus Analysis Employing Natural Language Processing Techniques
时间:2020-03-26 22:40:05
DOI:10.1111/lang.12232
作者:Alexopoulou, Theodora; Michel, Marije; Murakami, Akira
关键词:Linguistics;Accuracy;Natural Language Processing;Linguistic Performance;Language Proficiency;Difficulty Level;Second Language Learning;Second Language Instruction
出版源: 《Language Learning》
摘要: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.
大小:725 kb
页数:30 PAGES
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