This paper outlines the theoretical background of data-driven learning (DDL) and its hands-on application in French Language Teaching, as well didactic potential using text corpora functionalities to extract collocations. The second part focuses on analysis a project conducted among students Romance Philology. Its objective was corpus selected terms their Polish equivalents theme social issues....

The last decades witnessed the significant impact of using corpora on linguistics and language education. Particularly, introduction direct application Data-Driven Learning (DDL) has brought helpful tools in learning teaching languages. This study investigated effect confusing grammatical constructs , gerunds infinitives, to EFL students. Further, explore d students’ perceptions grammar. adopt ...

This paper presents the implementation of a didactic unit based on Singer's proposal for data-driven learning (DDL) within task-based (TB) framework in context Chilean translation education. The intervention has four stages: 1) data collection from students' preferred multimodal consumption order to generate written corpus transcription popular online TV series, 2) design that graduates concord...

Despite the increasing research on benefits of using corpora in language teaching and learning, Data-Driven Learning (henceforth, DDL) has been criticized for its lack contribution to second theories. This paper intends address this gap by examining assumptions Involvement Load Hypothesis (ILH) two DDL tasks with different cognitive loads. Learners were assigned one conditions: reading only or ...

The potential for corpora in language learning has attracted a significant amount of attention in recent years, including in the form of data-driven learning (DDL). Careful not to appear to over-promote the field, enthusiasts have urged caution in its application, in particular with regard to lower-level learners, and have argued that extensive learner-training in corpus techniques is an essent...

The potential for corpora in language learning has attracted a significant amount of attention in recent years, including in the form of data-driven learning (DDL). Careful not to appear to over-promote the field, enthusiasts have urged caution in its application, in particular with regard to lower-level learners, and have argued that extensive learner-training in corpus techniques is an essent...

Although annotation is a widely-researched topic in Corpus Linguistics (CL), its potential role in Data Driven Learning (DDL) has not been addressed in depth by Foreign Language Teaching (FLT) practitioners. Furthermore, most of the research in the use of DDL methods pays little attention to annotation in the design and implementation of corpus-based/driven language teaching. In this paper, we ...

This paper explores deep latent variable models for semi-supervised paraphrase generation, where the missing target pair unlabelled data is modelled as a sequence. We present novel unsupervised model named variational sequence auto-encoding reconstruction (VSAR), which performs inference given an observed text. To leverage information from text pairs, we additionally introduce supervised call d...