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What are language learners looking for in a collocation consultation system? Identifying collocation look-up patterns with user query data

Published online by Cambridge University Press:  27 April 2021

Shaoqun Wu Open the ORCID record for Shaoqun Wu [Opens in a new window] ,
Alannah Fitzgerald Open the ORCID record for Alannah Fitzgerald [Opens in a new window] ,
Alex Yu Open the ORCID record for Alex Yu [Opens in a new window]  and
Zexuan Chen Open the ORCID record for Zexuan Chen [Opens in a new window]
Shaoqun Wu
Affiliation:
University of Waikato, New Zealand (shaoqun@waikato.ac.nz)
Alannah Fitzgerald
Affiliation:
University of Waikato, New Zealand (alannahfitzgerald@gmail.com)
Alex Yu
Affiliation:
Centre for Business, Information Technology and Enterprise, Wintec, New Zealand (alex.yu@wintec.ac.nz)
Zexuan Chen
Affiliation:
Southern Medical University, China (SerlinaChen@163.com)
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Abstract

Corpus consultation with concordancers has been recognized as a promising way for learners to study and explore language features such as collocations at their own pace and in their own time. This study examined 1.5 million search queries sent to a collocation consultation tool called FlaxCLS (Flexible Language Acquisition Collocation Learning System; http://flax.nzdl.org) over a period of two years to identify learners’ collocation look-up patterns. This paper examines and characterizes learners’ look-up patterns as they entered search queries, clicked on the query formation aids provided by the system, and navigated through the different levels of collocation information returned by the system to support collocation learning. We looked at how learners formulated query terms, and we analyzed the characteristics of query words learners entered, the characteristics of collocations they preferred, and the sample sentences they checked. Our collocation look-up pattern analyses, similar to traditional user query analyses of the web, provide interesting and revealing insights that are hard to obtain from small-scale user studies. The findings provide valuable information and pedagogical implications for data-driven learning (DDL) researchers and language teachers in designing tailored collocation consultation systems and activities. This paper also presents multidimensional analyses of learner query data, which, to the best of our knowledge, have not been explored in DDL research.

Keywords

collocation learningdata analysisdata drivenDDLuser query analysis
Type
Research Article
Information
ReCALL , Volume 33 , Issue 3 , September 2021 , pp. 229 - 247
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Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of European Association for Computer Assisted Language Learning

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