We begin by showing that the best publicly available, multiple-L1 learner corpus, the International Corpus of Learner English (Granger et al. 2009), has serious issues when used for the task of native language detection (NLD). The topic biases in the corpus are a confounding factor that result in crossvalidated performance that is misleading, for all the feature types which are traditionally us...

We present the Jinan Chinese Learner Corpus, a large collection of L2 Chinese texts produced by learners that can be used for educational tasks. The present work introduces the data and provides a detailed description. Currently, the corpus contains approximately 6 million Chinese characters written by students from over 50 different L1 backgrounds. This is a large-scale corpus of learner Chine...

In learner corpora, as in any corpus, mark-up is an important issue. One aspect of learner corpora so far largely ignored, however, is the specific question of handwriting and in particular how to mark-up handwriting anomalies, especially with learners whose native language uses a different writing system. In this paper we pose some open questions about what aspects of a learner’s handwriting m...

Researchers working with learner corpora promise quantitative results that would be of greater practical value in areas such as CALL than those from small-scale and qualitative studies. However, learner corpus research has not yet had an impact on practices in teaching and assessment. Significant methodological issues need to be examined if results from learner corpus research are going to prov...

This paper describes the creation of a new annotated learner corpus. The aim is to use this corpus to develop an automated system for corrective feedback on students’ writing. With this system, students will be able to receive timely feedback on language errors before they submit their assignments for grading. A corpus of assignments submitted by first year engineering students was compiled, an...

In this paper, we discuss how error annotation for learner corpora should be done by explaining the state of the art of error tagging schemes in learner corpus research. Several learner corpora, including the NICT JLE (Japanese Learner English) Corpus that we have compiled are annotated with error tagsets designed by categorizing “likely” errors implied from the existing canonical grammar rules...

This opinion paper proposes the use of parallel treebank as learner corpus. We show how an L1-L2 parallel treebank — i.e., parse trees of non-native sentences, aligned to the parse trees of their target hypotheses — can facilitate retrieval of sentences with specific learner errors. We argue for its benefits, in terms of corpus reuse and interoperability, over a conventional learner corpus anno...