158 resultados para Dutch language


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Background
Parent ratings on questionnaires may provide valid and cost-effective tools for screening cognitive development of children at risk of developmental delay.

Aims
In this study, we examined the convergent validity of combining parent-based reports of non-verbal cognitive abilities (PARCA3) and verbal abilities (CDI-III) in relation to the Bayley-III cognitive scale in 3-year-olds born late pre-term.

Methods
Mothers of 185 late-preterm children were asked to complete the PARCA3 and the CDI-III shortly before children reached age three; children were then assessed using the Bayley-III close to their third birthday.

Results
The two maternal questionnaires were significantly and moderately correlated with the Bayley-III cognitive scores. Together the maternal ratings accounted for 15% of the variance in the Bayley-III cognitive scores, after controlling for other covariates in regression analysis. In particular, the PARCA3 contributed significantly to explain variance in the Bayley-III cognitive scores when controlling for the CDI-III. However, the CDI-III was also independently associated with the Bayley-III cognitive scores.

Conclusions
Parent ratings of child cognition and language together may provide cost-effective screening of development in “at risk” preschoolers.

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Using fMRI, we conducted two types of property generation task that involved language switching, with early bilingual speakers of Korean and Chinese. The first is a more conventional task in which a single language (L1 or L2) was used within each trial, but switched randomly from trial to trial. The other consists of a novel experimental design where language switching happens within each trial, alternating in the direction of the L1/L2 translation required. Our findings support a recently introduced cognitive model, the 'hodological' view of language switching proposed by Moritz-Gasser and Duffau. The nodes of a distributed neural network that this model proposes are consistent with the informative regions that we extracted in this study, using both GLM methods and Multivariate Pattern Analyses: the supplementary motor area, caudate, supramarginal gyrus and fusiform gyrus and other cortical areas. 

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This paper presents a machine learning approach to sarcasm detection on Twitter in two languages – English and Czech. Although there has been some research in sarcasm detection in languages other than English (e.g., Dutch, Italian, and Brazilian Portuguese), our work is the first attempt at sarcasm detection in the Czech language. We created a large Czech Twitter corpus consisting of 7,000 manually-labeled tweets and provide it to the community. We evaluate two classifiers with various combinations of features on both the Czech and English datasets. Furthermore, we tackle the issues of rich Czech morphology by examining different preprocessing techniques. Experiments show that our language-independent approach significantly outperforms adapted state-of-the-art methods in English (F-measure 0.947) and also represents a strong baseline for further research in Czech (F-measure 0.582).

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This chapter discusses English Language Education at university and highlights a number of trends and their associated challenges in teaching and learning academic discourse. Academic discourse refers to the ways in which language is used by participants in academia. It encompasses written discourse, from article and book publishing, PhD theses to course assignments; spoken discourse, from study groups, tutorials, conference presentations to inaugural lectures; and more recently, computer-mediated discourse, from asynchronous text-based conferencing to academic blogs. The role of English language educators in preparing students and academics for successful participation in these academic events, or the academy, in English is not to be underestimated. Academic communication is not only vital to an individual’s success at university, but to the maintenance and creation of academic communities and to scientific progress itself (Hyland, 2009). This chapter presents an overview of academic discourse and discusses recent issues which have an impact on teaching and learning English at university and discusses their associated challenges: first, the increasing internationalisation of universities. Second, the emergence of a mobile academe in its broadest sense, in which students and academics move across traditional geopolitical, institutional and disciplinary boundaries, is discussed. Third, the growth of UK transnational higher education is examined as a trend which sees academics and students vicariously or otherwise involved in English language teaching and learning. Fourth, the chapter delves into the rapid and ongoing development in technology assisted and online learning. While responding to trends can be difficult, they can also inspire ingenuity. Furthermore, such trends and challenges will not emerge in the same manner in different contexts. The discussion in this chapter is illustrated with examples from a UK context but the implications of the trends and challenges are such that they reach beyond borders.

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Since the beginning of the Northern Ireland conflict in the late 1960s, Irish nationalism has been identified as a prominent force in the political culture of the state. Recent studies have suggested, however, that the ‘Nationalist’ population has become increasingly content within the new political framework created by the peace process and the aspiration for Irish unity diminished. In placing the Northern Ireland situation within the theoretical framework of nationalism, this paper will analyse how these changing priorities have been possible. Through an analysis of Irish language study in Northern Ireland's schools, the paper will examine how the political ideals espoused by the nationalist Sinn Féin Party reflected the priorities of the ‘nationalist community’. It will be contended that the relationship between the ideology and ‘the people’ is much more complex than is often allowed for and that educational inequalities are a significant contributing factor to this.