Hostname: page-component-74656f9884-rngvg Total loading time: 0 Render date: 2026-11-04T05:18:13.787Z Has data issue: false hasContentIssue false

Enhancing writing pedagogy with learner corpus data

Published online by Cambridge University Press:  21 February 2014

Elena Cotos*
Affiliation:
Iowa State University, USA (email: ecotos@iastate.edu)
Rights & Permissions [Opens in a new window]

Abstract

Learner corpora have become prominent in language teaching and learning, enhancing data-driven learning (DDL) pedagogy by promoting ‘learning driven data’ in the classroom. This study explores the potential of a local learner corpus by investigating the effects of two types of DDL activities, one relying on a native-speaker corpus (NSC) and the second combining native-speaker and learner corpora. Both types of activities aimed at improving second language writers’ knowledge of linking adverbials and were based on a preliminary analysis of adverbial use in the local learner corpus produced by 31 study participants. Quantitative and qualitative data, obtained from writing samples, pre/post-tests, and questionnaires, were converged through concurrent triangulation. The results showed an increase in frequency, diversity and accuracy in all participants’ use of adverbials, but more significant improvement was made by the students who were exposed to the corpus containing their own writing. The findings of this study are thus interpreted as suggestive that combining learner and native-speaker data is a feasible and effective practice, which can be readily integrated in DDL-based instruction with positive impact.

Information

Type
Research Article
Copyright
Copyright © European Association for Computer Assisted Language Learning 2014 
Figure 0

Table 1 Local learner corpus design criteria

Figure 1

Table 2 Local learner corpus composition (words and number of papers)

Figure 2

Table 3 Experimental procedure

Figure 3

Table 4 LA frequency in the pre-experiment local learner corpus

Figure 4

Table 5 LAs in the local learner corpus (normalized per 1,000 words)

Figure 5

Table 6 Positional and syntactic realizations of LAs in the local learner corpus

Figure 6

Table 7 Descriptive statistics for pre- and post-tests

Figure 7

Table 8 Frequency of LA semantic categories in the immediate post-experiment component of the local learner corpus

Figure 8

Fig. 1 LA use by the NSC and LDD groups in the immediate and delayed post-intervention local learner corpus