Corpora as open educational resources for language teaching

Corpora, large electronic collections of texts, have been used in language teaching for several decades. Also known as Data‐Driven Learning (DDL), this method has been gaining popularity because empirical research has consistently shown its effectiveness for learning. However, corpora are still underutilized, especially with learners of languages other than English, at lower proficiency levels, and in non‐university contexts. This is regrettable because DDL has a great potential for developing modular flipped content, especially for hybrid, remote, and online courses. This article first provides an overview of DDL applications and findings of empirical research. Next, it outlines obstacles to wider DDL implementation as well as available and possible solutions. Corpus user guides and exercise collections tied to specific corpora are discussed as one promising direction, and an example of such new open educational resources for teaching German is presented. The article concludes with a discussion of implications and future directions

Evaluating and Automating the Annotation of a Learner Corpus

The paper describes a corpus of texts produced by non-native speakersof Czech. We discuss its annotation scheme, consisting of three interlinked tiers,designed to handle a wide range of error types present in the input. Each tier correctsdifferent types of errors; links between the tiers allow capturing errors in word orderand complex discontinuous expressions. Errors are not only corrected, but alsoclassified. The annotation scheme is tested on a data set including approx. 175,000words with fair inter-annotator agreement results. We also explore the possibility ofapplying automated linguistic annotation tools (taggers, spell checkers and grammarcheckers) to the learner text to support or even substitute manual annotation