Using a Free Corpus Tool for Time-efficient Feedback on English as a Foreign Language reports

Abstract

English as a Foreign Language (EFL) learners often struggle with some of the elements and features of text composition, such as conventions, socio-cultural aspects like hedging, degree of formality or synonyms. This paper aims to provide, by way of exemplification, the application of a corpus-aided technique that helps teachers determine whether general task completion has been achieved in order to identify learners’ deficiencies in writing. This method was employed to consider lexical range (i.e. synonyms), cohesive devices and hedging strategies, including modal verbs, in the participants’ written outputs, a total of 93, in a higher education EFL classroom. To this end, the tool LexTutor (Cobb n.d.) was used to explore the corpus. The data gathered have been analysed following a quantitative approach. Findings indicate that, on average, learners’ productions met the indications in the instructions. Nevertheless, there was a tendency to use lower-level or simpler structures and words rather than opting for language exploration, thus prioritising accuracy. The present study raises the possibility that EFL teachers can offer general class feedback on students’ productions promptly and efficiently.

Exploring corpus linguistics via computational tool analysis: key finding review

“…These tools can discern patterns and meanings in a manner like that of human comprehension [30]. Among the most notable NLP tools are Wordify [8], Mlphon [31], morphological analyzer [32], Runyakitara tool [33], LexTutor [34], [35], Coh-Metric [36], [37] linguistic queries and word count (LIWC) [38], UAM corpus tool [39], [40], SketchEngine (SkE) [41], Wmatrix [37] MultiAzterTest [42], sublanguage corpus analysis toolkit (SubCAT) [43], EnvText [44], InLang [45], Berri corpus manager [46], UCREL semantic analysis system (USAS) [47], PyMongo (Mongo DB, Python technology, Flask) [46], LancsBox 5.1.2 [48], LancsBox 4.5 [49], LancsBox [50], NooJ platform [51] and Bi-LSTM [52].…”

The speech act of offer in Jordanian arabic

“…As manifested earlier, offers can be realized (in)directly. Considering the former categorization of offers, the simplest way to present an appropriate taxonomy of the linguistic realization of offers is to divide them according to their continuum between directives and/or commissives (Barron, 2017;Hernández, 2001) into four parts: directive-end, commissive-end, directive-and commissive-end, and directive-nor commissive-end. These four parts are realized by various linguistic patterns.…”