Prof. Dr. Walt Detmar Meurers
On the Automatic Analysis of Learner Language. Introduction to the Special Issue


Detmar Meurers


CALICO Journal 26 (3). 2009.


Natural language processing (NLP) has long been used to automatically analyze language produced by language learners, typically aimed at providing individualized feedback and learner modeling in Intelligent Computer-Assisted Language Learning systems (cf. Heift & Schulze 2007). While much interesting research has been reported, it is difficult to determine the state of the art for the automatic analysis of learner language. Which error types and other learner language properties can be detected and diagnosed automatically? How reliably can this be done, for which kind of learner language, resulting from which types of tasks? For sustainable progress on the automatic analysis of learner language it arguably is crucial to answer these questions, to discuss and compare the performance of different analysis methods on real-life learner data sets.


As an essential prerequisite for addressing these issues, it is necessary to determine which learner language properties are useful or important to analyze in order to provide feedback and model language acquisition ­ a question which highlights the need for an intensive interdisciplinary dialogue between the fields of Intelligent Computer-Assisted Language Learning (ICALL), Second Language Acquisition (SLA), and Foreign Language Teaching (FLT).


Relatedly, the questions arising for the automatic analysis of learner language in ICALL intersect in important ways with research on learner corpora. Feedback and learner modeling in ICALL systems and the annotation of learner corpora for SLA and FLT research are both dependent on consistently identifiable learner language properties, their systematization in annotation schemes, and the development of NLP tools for automating such analysis as part of ICALL systems or to make the annotation of large learner corpora feasible. The papers collected in this special issue explore these issues further, by discussing the analysis of relevant aspects of written and spoken learner language, by defining and evaluating novel computational approaches, and by presenting systems integrating the analysis of learner language.



Electronically available file formats:


Note: The electronic versions of the publications linked on this page are the last versions I had the copyright for. Where a publisher copyedited and/or typeset the papers, the electronic copies linked here are NOT identical to the officially published version, which should be used for any quotes, references to page numbers, etc.



Bibtex entry:

   author = 	 {Detmar Meurers},
   title = 	 {On the Automatic Analysis of Learner Language. 
                  Introduction to the Special Issue},
   journal = 	 {CALICO Journal},
   volume =      {26},
   number =      {3},
   year = 	 {2009},
   pages =       {469--473},
   url =         {}