Rights statement: 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.
Accepted author manuscript, 592 KB, PDF document
Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License
Rights statement: 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.
Accepted author manuscript, 1.59 MB, Word document
Rights statement: 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.
Accepted author manuscript, 40.9 KB, Word document
Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Task effects on linguistic complexity and accuracy
T2 - a large-scale learner corpus analysis employing Natural Language Processing techniques
AU - Alexopoulou, Theodora
AU - Michel, Marije Cornelie
AU - Murakami, Akira
AU - Detmar, Meurers
N1 - 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.
PY - 2017/6
Y1 - 2017/6
N2 - 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.
AB - 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.
U2 - 10.1111/lang.12232
DO - 10.1111/lang.12232
M3 - Journal article
VL - 67
SP - 180
EP - 208
JO - Language Learning
JF - Language Learning
SN - 0023-8333
IS - Suppl. 1
ER -