Comparing concordances of language patterns and words by ESL intermediate learners: a preliminary experiment with two mobile concordancers

Abstract

As a corpus-assisted method for language pedagogy, DDL (data-driven learning) may have the potential to enhance language exposure and promote active learner engagement. Concordancing, or KWIC (Key Words in Context), has been the traditional method used in DDL to retrieve numerous language examples, while the method has limitations with overreliance on individual words to search. This paper aims to propose and promote concordancing alternatively based on grammar patterns, a multi-word concept in corpus linguistics. The conceptualised method is named as PIC (Patterns in Context), an extended form of KWIC. An empirical study was conducted to investigate whether the PIC method has any advantages over the traditional KWIC method, using two custom-built Android apps. The research involved 18 pre-university intermediate learners (and six pilot study participants), who used the apps in a self-directed way for two weeks. Then the assessment of the two apps and methods was conducted based on data from automatic logs and responses from questionnaires and interviews. The results suggest that, compared to KWIC, PIC could be slightly advantageous in efficiently helping learners find the target language use, while this approach seems not strong in user engagement and perceived effectiveness. The implications for DDL are discussed, and further investigation is also planned.

Keywords:

• Data-driven learning
• grammar patterns
• concordancing
• mobile learning
• corpus linguistics

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 The number of concordances for each node word is reduced to five to adapt to limited space.

2 The number of selected examples is reduced to four for each pattern to adapt to limited space.

3 From http://www.someya-net.com/concordancer/, underlined by the authors.

4 A ‘session’ refers to the time when a user completed entry and exit of the apps, suggesting the apps were used once.

Additional information

Notes on contributors

Zhi Quan

Dr. Zhi Quan (preferably Bill) is an Assistant Professor of Southwestern University of Finance and Economics in Chengdu, China. He receives his PhD from Auckland University of Technology (AUT) in New Zealand. His research interests include corpus linguistics, mobile learning, English for academic purposes (EAP) and translation studies. He has been devoted to promoting and enhancing self-directed and autonomous learning experience of learners via emerging technologies.

Lynn Grant

Dr. Lynn Grant is a Senior Lecturer of Auckland University of Technology (AUT) in New Zealand. For three decades, she teaches writing and other courses in the university and supervises graduate students. Her primary research areas include applied linguistics and sociolinguistics, covering topics on corpus linguistics, discourse analysis and pedagogy.

Darryl Hocking

Dr. Darryl Hocking is a Senior Lecturer of Auckland University of Technology (AUT) in New Zealand. His primary research areas are discourse, genre, metaphor, and corpus analysis with a particular focus on the interactional genres and communicative practices in art and design settings and how these impact on creative activity. On this subject, he has authored the book Communicating Creativity: The Discursive Facilitation of Creative Activity in Arts (Palgrave Macmillan).