Collocations play a significant role in second language acquisition. In order to be able to offer efficient support to learners, an NLP-based CALL environment for learning collocations should be based on a representative collocation error annotated learner corpus. However, so far, no theoretically-motivated collocation error tag set is available. Existing learner corpora tag collocation errors ...

In our paper we present the design and interface of ASK, a language learner corpus of Norwegian as a second language which contains essays collected from language tests on two different proficiency levels as well as personal data from the test takers. In addition, the corpus also contains texts and relevant personal data from native Norwegians as control data. The texts as well as the personal ...

High potential variation in prior knowledge, metacognitive skills, and motivation within learner populations can prompt design strategies that combine explicit structuring and scaffolding with increased learner control. We examine the use of such a strategy—a structured inquiry cycle—in a corpus of online modules (50) for adult informal learners using process mining. We apply process analysis t...

A key issue when mining web information is the labeling problem: data is abundant on the web but is unlabelled. In this thesis, we address this problem by proposing i) a novel theoretical granular model that structures categorical noun phrase instances as well as semantically related noun phrase pairs from a given corpus representing unstructured web pages with a variant of Tolerance Rough Sets...

In this paper we present the design and experimental results of a cloud-based personalized recursive dialogue game system for computer-assisted language learning. A number of tree-structured sub-dialogues are used sequentially and recursively as the script for the game. The dialogue policy at each dialogue turn is optimized to offer the most appropriate training sentence for every individual le...

Corpus studies of native speaker and learner language have been influential in informing syllabus design and course content in foreign or second language (L2) teaching. Corpora can also be explored directly by the learner, in what Johns (1991) has called ―data-driven learning‖ (DDL). Such an approach is alleged to have many advantages, including fostering learner autonomy, increasing language a...

This paper describes a method of detecting grammatical and lexical errors made by Japanese learners of English and other techniques that improve the accuracy of error detection with a limited amount of training data. In this paper, we demonstrate to what extent the proposed methods hold promise by conducting experiments using our learner corpus, which contains information on learners’ errors.

We present an English miscollocation identification system based on dependency relations drawn from the Stanford parser. We test our system against a subset of error-tagged Chinese Learner English Corpus (CLEC)and obtain an overall precision of 0.75. We describe some applications and limitations of our system and suggest directions for future research.

The paper presents a Universal Dependencies (UD) annotation scheme for a learner English corpus. The REALEC dataset consists of essays written in English by Russian-speaking university students in the course of general English. The original corpus is manually annotated for learners’ errors and gives information on the error span, error type, and the possible correction of the mistake provided b...

Arabic diacritics are often missed in Arabic scripts. This feature is a handicap for new learner to read َArabic, text to speech conversion systems, reading and semantic analysis of Arabic texts. The automatic diacritization systems are the best solution to handle this issue. But such automation needs resources as diactritized texts to train and evaluate such systems. In this paper, we describe ...