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 ...

One application of corpora involves language learning through direct contact with language corpora, often referred to as data-driven learning (DDL). It is often assumed that the approach is unsuitable for lower level learners, but this has rarely been empirically tested. This paper describes a simple experiment on phrasal verbs with 113 lower intermediate learners of English. They were tested o...

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...

D-alanine:D-alanine ligase (EC 6.3.2.4; Ddl) catalyzes the ATP-driven ligation of two D-alanine (D-Ala) molecules to form the D-alanyl:D-alanine dipeptide. This molecule is a key building block in peptidoglycan biosynthesis, making Ddl an attractive target for drug development. D-Cycloserine (DCS), an analog of D-Ala and a prototype Ddl inhibitor, has shown promise for the treatment of tubercul...

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 ...

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...

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...

As an implementation of compressive sensing (CS), dual-dictionary learning (DDL) method provides an ideal access to restore signals of two related dictionaries and sparse representation. It has been proven that this method performs well in medical image reconstruction with highly undersampled data, especially for multimodality imaging like CT-MRI hybrid reconstruction. Because of its outstandin...