Learning language and mathematics: A perspective from Linguistics and Education

Wilkinson, Louise Cherry

doi:10.1016/j.linged.2018.03.005

Cited by 27 publications

(18 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similar observations have been made regarding a number of other disciplines (Schleppergrell, 2007;Nagy & Townsend, 2012;Greene & Coxhead, 2015;Chan, 2015;Wilkinson, 2018Wilkinson, , 2019Yun & Park, 2018). Chan (2015) identifies a category of action verbs including expand, find, give, convert, simplify, evaluate, which are sub-technical in scientific discourse but are polysemous with everyday meanings (p. 308).…”

Section: Polysemy and Academic Lexismentioning

confidence: 55%

“…While each register and sub-register is characterised by different lexical choices and uses, a number of writers believe that there is a core of academic vocabulary that is shared by many disciplines (e.g. Coxhead, 2000Coxhead, , 2018Wilkinson 2018Wilkinson , 2019. This idea is well-known among teachers in English secondary schools.…”

Section: School Academic Language and Levels Of Vocabularymentioning

confidence: 99%

See 1 more Smart Citation

Using corpus methods to identify subject specific uses of polysemous words in English secondary school science materials

Deignan¹,

Love²

2021

Corpora

View full text Add to dashboard Cite

Many education professionals in Britain believe that school pupils have difficulty accessing academic texts because of inadequate knowledge of vocabulary. Previous research has suggested that some high frequency words used in non-specialised contexts have academic meanings that can cause problems for school pupils. We take corpus techniques used in the study of higher education texts and apply them to a corpus of texts designed for school pupils aged 11 to 14, attempting to identify such words automatically. We use the Spoken BNC2014 as a reference corpus. We identify a list of semi-technical words ( Baker, 1988 ), many of which are polysemous, having everyday meanings and related school subject meanings that may not be familiar to pupils. We investigate how semi-technical vocabulary can be identified and distinguished from both specialised and general vocabulary. Some supplementary qualitative analysis was needed, using collocation and concordance analysis. While time-consuming, the potential benefits for pupils struggling with school language make this a worthwhile exercise.

show abstract

Section: Polysemy and Academic Lexismentioning

confidence: 55%

Section: School Academic Language and Levels Of Vocabularymentioning

confidence: 99%

Using corpus methods to identify subject specific uses of polysemous words in English secondary school science materials

Deignan¹,

Love²

2021

Corpora

View full text Add to dashboard Cite

show abstract

“…Some other visual representatives can be used to understand mathematical concepts (Jupri & Drijvers, 2016). In mathematics, the selection of visual representatives depends on what to express (Accurso, Gebhard, Purington, 2017; Weinberg, 2019; Wilkinson, 2019). For exemplify, visual representatives in mathematics, there are two-dimensional figures and solid geometry.…”

Section: Definition and Concept Of The Language Of Mathematicsmentioning

confidence: 99%

“…Mathematics register refers to a specific definition of the basic language of mathematics that includes the understanding of the grammatical rules, vocabularies, and symbols, such as graphs and figures (Wilkinson, 2018). In addition, Wilkinson (2019) emphasizes that mathematics teachers need to alternate their point of view that mathematics education is a study full of language, symbols, and vocabularies; each of which underlies hidden meanings that are different from that of in common language. During mathematics instructions, teachers are to make use of the language of mathematics properly and accurately (Golding, 2017;Hill et al, 2008;Purpura & Reid, 2016).…”

Section: The Teachers' Competence In Understanding the Language Of Mamentioning

confidence: 99%

Teachers' Competence in the Acquisition and Use of the Mathematical Language in Indonesia

Baiduri

Utomo

2020

HSSR

View full text Add to dashboard Cite

The purpose of the study: This paper aimed at describing the teachers' competence in the acquisition and use of the language of mathematics at public and private senior high schools all over Malang City, Malang Regency, and Batu City, Indonesia. Methodology: Qualitative descriptive research design was employed by means of content analysis on the results of the interview and documents of mathematic instructions designed by 30 teachers who also served as the research subjects, spiral analysis on the qualitative data by Creswell was applied to analyze the data, with the support of NVivo 12 plus software. Main Findings: This research has revealed that the teachers have acquired and used the language of mathematics, with some errors and fallacies in the use of mathematics vocabularies, grammar, and the explanation of mathematical symbols. The teachers' competence in the acquisition and use of the language of mathematics was influenced by the knowledge about mathematical concepts, presentations, and instructions. Applications of this study: The findings of this study are expected to add new knowledge about the competency of the mathematics language of the teacher so that it can be used as a reference for colleges producing teacher candidates in developing the curriculum. Theoretically, these results can be used as a reference and contribute to assessing the mathematical language competence of teachers. Novelty/Originality of this study: This current research, is based on their educational qualifications, and to identify factors that influence the teachers' competence in the acquisition and use of the language of mathematics which is less explored by the earlier researcher.

show abstract

“…Metrological linguistics holds that the differences in language styles of translations are caused by the differences in the frequency of language units used. (3,4) In our opinion, since translation is a kind of re-creation and also a kind of literary work, different linguistic styles and linguistic features will appear in different translations. On the basis of this description, we compare the stylistic features and translation styles of different translators to identify the translators of different translations and assess the quality of artificial translations.…”

Section: Introductionmentioning

confidence: 99%

Research on Translation Style in Machine Learning Based on Linguistic Quantitative Characteristics Perception

Qiu¹,

Su²,

Le³

et al. 2021

Sensors and Materials

View full text Add to dashboard Cite

Research on the metrological characteristics of linguistic quantitative characteristics (LQCs) based on corpus and metrological linguistic methods has gained wide attention in artificial and online machine translations. Although a support vector machine (SVM) is one of the most widely used machine learning (ML) algorithms in the field of text analysis, its application in the study of translation style is rare. This study compares the translation styles of Pride and Prejudice with ML using different linguistic measurement features. Firstly, the language measurement features of three translations are obtained with the information gain algorithm. Specifically, the corpus can be achieved through human-machine interaction (HCI), i.e., computers can look, hear, touch, smell, taste, and speak using sensors such as cameras and mathematical algorithms. Then a text classifier, i.e., an SVM, is constructed on the basis of these features to automatically classify the translated texts of the three translations. Finally, the validity of the classifier is verified by the tenfold cross-validation method. It is proved that the SVM algorithm has high classification accuracy and a strong predictive function, which is helpful for judging or predicting the translation or translator's style. Compared with the traditional method, this classification method based on an SVM saves time and effort, the process can be repeated, and the result is accurate and reliable.

show abstract

Learning language and mathematics: A perspective from Linguistics and Education

Cited by 27 publications

References 39 publications

Using corpus methods to identify subject specific uses of polysemous words in English secondary school science materials

Using corpus methods to identify subject specific uses of polysemous words in English secondary school science materials

Teachers' Competence in the Acquisition and Use of the Mathematical Language in Indonesia

Research on Translation Style in Machine Learning Based on Linguistic Quantitative Characteristics Perception

Contact Info

Product

Resources

About