982 resultados para Linguistic support classes


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Les aules d'acollida tenen com a objectiu principal donar suport lingüístic a l'alumnat estranger perquè aquest desenvolupi coneixement de la llengua de l'escola.La tesi presenta els resultats de l'avaluació de les aules d'acollida de primària de tot Catalunya durant el curs 2006-2007. En l'avaluació es van emprar tres instruments: una prova de coneixement de català nivell A2, un qüestionari d'adaptació escolar i un qüestionari individual que recollia variables com el temps d'estada a Catalunya, el nombre d'hores setmanals a l'aula d'acollida, la llengua inicial o l'escolarització prèvia de l'alumnat. Totes les dades van ser introduïdes en el programa SPSS versió 15 i es van aplicar diferents tècniques estadístiques.Els resultats mostren que la variable que descriu millor les diferències de coneixement de català de l'alumnat estranger de les aules d'acollida és la seva adaptació escolar. Aquesta variable es mostra tan potent en la descripció dels resultats que mitiga els efectes reals d'altres variables com el temps d'estada a Catalunya, el nombre d'hores setmanals a l'aula d'acollida o la llengua inicial de l'alumnat.

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OBJECTIVES. Oral foreign language skills are an integral part of one's social, academic and professional competence. This can be problematic for those suffering from foreign language communication apprehension (CA), or a fear of speaking a foreign language. CA manifests itself, for example, through feelings of anxiety and tension, physical arousal and avoidance of foreign language communication situations. According to scholars, foreign language CA may impede the language learning process significantly and have detrimental effects on one's language learning, academic achievement and career prospects. Drawing on upper secondary students' subjective experiences of communication situations in English as a foreign language, this study seeks, first, to describe, analyze and interpret why upper secondary students experience English language communication apprehension in English as a foreign language (EFL) classes. Second, this study seeks to analyse what the most anxiety-arousing oral production tasks in EFL classes are, and which features of different oral production tasks arouse English language communication apprehension and why. The ultimate objectives of the present study are to raise teachers' awareness of foreign language CA and its features, manifestations and impacts in foreign language classes as well as to suggest possible ways to minimize the anxiety-arousing features in foreign language classes. METHODS. The data was collected in two phases by means of six-part Likert-type questionnaires and theme interviews, and analysed using both quantitative and qualitative methods. The questionnaire data was collected in spring 2008. The respondents were 122 first-year upper secondary students, 68 % of whom were girls and 31 % of whom were boys. The data was analysed by statistical methods using SPSS software. The theme interviews were conducted in spring 2009. The interviewees were 11 second-year upper secondary students aged 17 to 19, who were chosen by purposeful selection on the basis of their English language CA level measured in the questionnaires. Six interviewees were classified as high apprehensives and five as low apprehensives according to their score in the foreign language CA scale in the questionnaires. The interview data was coded and thematized using the technique of content analysis. The analysis and interpretation of the data drew on a comparison of the self-reports of the highly apprehensive and low apprehensive upper secondary students. RESULTS. The causes of English language CA in EFL classes as reported by the students were both internal and external in nature. The most notable causes were a low self-assessed English proficiency, a concern over errors, a concern over evaluation, and a concern over the impression made on others. Other causes related to a high English language CA were a lack of authentic oral practise in EFL classes, discouraging teachers and negative experiences of learning English, unrealistic internal demands for oral English performance, high external demands and expectations for oral English performance, the conversation partner's higher English proficiency, and the audience's large size and unfamiliarity. The most anxiety-arousing oral production tasks in EFL classes were presentations or speeches with or without notes in front of the class, acting in front of the class, pair debates with the class as audience, expressing thoughts and ideas to the class, presentations or speeches without notes while seated, group debates with the class as audience, and answering to the teacher's questions involuntarily. The main features affecting the anxiety-arousing potential of an oral production task were a high degree of attention, a large audience, a high degree of evaluation, little time for preparation, little linguistic support, and a long duration.

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A maths support system for first-year engineering students with non-traditional entry qualifications has involved students working through practice questions structured to correspond with the maths module which runs in parallel. The setting was informal and there was significant one-to-one assistance. The non-traditional students (who are known to be less well prepared mathematically) were explicitly contacted in the first week of their university studies regarding the maths support and they generally seemed keen to participate. However, attendance at support classes was relatively low, on average, but varied greatly between students. Students appreciated the personal help and having time to ask questions. It seemed that having a small group of friends within the class promoted attendance – perhaps the mutual support or comfort that they all had similar mathematical difficulties was a factor. The classes helped develop confidence. Attendance was hindered by the class being timetabled too soon after the relevant lecture and students were reluctant to come with no work done beforehand. Although students at risk due to their mathematical unpreparedness can easily be identified at an early stage of their university career, encouraging them to partake of the maths support is an ongoing, major problem.

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This study incorporates many areas of knowledge to the Linguistics field, as it centers the social historicity of Brazilian and autos potiguares on two analytical proposes: the presence of linguistic formulas - in its macrostructure - into the paradigm of discursive traditions, following Kabatek (2006), Koch and Oesterreicher (2007), besides the theory of Speech Acts, in its microstructure, proposed by Austin (1990) and Searle (1995). Under Zumthor (1993; 1997; 2000; 2005; 2010), the idea of textual variability (mouvance) was alluded, highlighting that the text is always modifying, according to the performance and reception of the language uses. Considering this theoretical framework, we focus on the trinomial linguistic formulas, orality and performance, in order to describe the dynamics of stability, variation and change, emphasizing yet how extra-linguistic social-historic cultural relations influence its composition. Such discuss is inherent more precisely to Textual Analysis in enhancing the orality tradition as a linguistic support. The text, in its turn, becomes effective as an evocation, motivated by the transmission, reception and variability from its conservation and reiteration. Naturally, a methodological support based on quali-quantitative research was chosen, based on Flick (2009), who justifies the corpus composed by Brazilian Folias de Reis chants and Bois de Reis potiguares . Thereby Language dynamics, subjacent to tradition which takes effect by the use of a common social memory, are observed from two dimensions: on the first, it evocates the sacralization (religious) in which they stand their devotion to biblical History; secondly, a dissacralization with identified and ideological values, inherent to a people culture. The chant shows, in this ludic impulse, a contextualized activity which results in the following conclusion: the changing and stability processes in textual macro and microstructures occur, at the same time, by the adjustment to the use of the text accomplishing a social-political function and an ethical-pedagogic one; supposedly, social relationships arise the tradition and it, on its turn, evocates the variability and the nomadism in the text

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Tai languages are often described as “lacking” a major lexical class “adjectives”; accordingly, they and other area languages are frequently cited as evidence against adjectival universality. This article brings the putative lack under examination, arguing that a more complete distributional analysis reveals a pattern: overlap is highest among semantically peripheral adjectives and verbs and in constructions prototypically associated to both classes crosslinguistically, and lowest among semantically core adjectives and verbs and in constructions prototypically associated to only one or the other class. Rather than “lacking” adjectives, data from Thai thus in fact support functional-typological characterizations of adjectival universality such as those of Givón (1984), Croft (2001), and Dixon (2004). Finally, while data from Thai would fail to falsify an adaptation of Enfield's (2004) Lao lexical class-taxonomy (in which adjectives are treated as a verbal subclass) on its own terms, this article argues that in absence of both universally-applicable criteria for the evaluation of categorial taxonomies crosslinguistically and evidence for the cognitive reality of categorial taxonomies so stipulated, even this more limited sense of a “lack” of adjectives in Thai is less radical a challenge to adjectival universality than has sometimes been supposed.

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Gender-fair language consists of the symmetric linguistic treatment of women and men instead of using masculine forms as generics. In this study, we examine how the use of gender-fair language affects readers' support for social initiatives in Poland and Austria. While gender-fair language is relatively novel in Poland, it is well established in Austria. This difference may lead to different perceptions of gender-fair usage in these speech communities. Two studies conducted in Poland investigate whether the evaluation of social initiatives (Study 1: quotas for women on election lists; Study 2: support for women students or students from countries troubled by war) is affected by how female proponents (lawyers, psychologists, sociologists, and academics) are referred to, with masculine forms (traditional) or with feminine forms (modern, gender-fair). Study 3 replicates Study 2 in Austria. Our results indicate that in Poland, gender-fair language has negative connotations and therefore, detrimental effects particularly when used in gender-related contexts. Conversely, in Austria, where gender-fair language has been implemented and used for some time, there are no such negative effects. This pattern of results may inform the discussion about formal policies regulating the use of gender-fair language.

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OntoTag - A Linguistic and Ontological Annotation Model Suitable for the Semantic Web 1. INTRODUCTION. LINGUISTIC TOOLS AND ANNOTATIONS: THEIR LIGHTS AND SHADOWS Computational Linguistics is already a consolidated research area. It builds upon the results of other two major ones, namely Linguistics and Computer Science and Engineering, and it aims at developing computational models of human language (or natural language, as it is termed in this area). Possibly, its most well-known applications are the different tools developed so far for processing human language, such as machine translation systems and speech recognizers or dictation programs. These tools for processing human language are commonly referred to as linguistic tools. Apart from the examples mentioned above, there are also other types of linguistic tools that perhaps are not so well-known, but on which most of the other applications of Computational Linguistics are built. These other types of linguistic tools comprise POS taggers, natural language parsers and semantic taggers, amongst others. All of them can be termed linguistic annotation tools. Linguistic annotation tools are important assets. In fact, POS and semantic taggers (and, to a lesser extent, also natural language parsers) have become critical resources for the computer applications that process natural language. Hence, any computer application that has to analyse a text automatically and ‘intelligently’ will include at least a module for POS tagging. The more an application needs to ‘understand’ the meaning of the text it processes, the more linguistic tools and/or modules it will incorporate and integrate. However, linguistic annotation tools have still some limitations, which can be summarised as follows: 1. Normally, they perform annotations only at a certain linguistic level (that is, Morphology, Syntax, Semantics, etc.). 2. They usually introduce a certain rate of errors and ambiguities when tagging. This error rate ranges from 10 percent up to 50 percent of the units annotated for unrestricted, general texts. 3. Their annotations are most frequently formulated in terms of an annotation schema designed and implemented ad hoc. A priori, it seems that the interoperation and the integration of several linguistic tools into an appropriate software architecture could most likely solve the limitations stated in (1). Besides, integrating several linguistic annotation tools and making them interoperate could also minimise the limitation stated in (2). Nevertheless, in the latter case, all these tools should produce annotations for a common level, which would have to be combined in order to correct their corresponding errors and inaccuracies. Yet, the limitation stated in (3) prevents both types of integration and interoperation from being easily achieved. In addition, most high-level annotation tools rely on other lower-level annotation tools and their outputs to generate their own ones. For example, sense-tagging tools (operating at the semantic level) often use POS taggers (operating at a lower level, i.e., the morphosyntactic) to identify the grammatical category of the word or lexical unit they are annotating. Accordingly, if a faulty or inaccurate low-level annotation tool is to be used by other higher-level one in its process, the errors and inaccuracies of the former should be minimised in advance. Otherwise, these errors and inaccuracies would be transferred to (and even magnified in) the annotations of the high-level annotation tool. Therefore, it would be quite useful to find a way to (i) correct or, at least, reduce the errors and the inaccuracies of lower-level linguistic tools; (ii) unify the annotation schemas of different linguistic annotation tools or, more generally speaking, make these tools (as well as their annotations) interoperate. Clearly, solving (i) and (ii) should ease the automatic annotation of web pages by means of linguistic tools, and their transformation into Semantic Web pages (Berners-Lee, Hendler and Lassila, 2001). Yet, as stated above, (ii) is a type of interoperability problem. There again, ontologies (Gruber, 1993; Borst, 1997) have been successfully applied thus far to solve several interoperability problems. Hence, ontologies should help solve also the problems and limitations of linguistic annotation tools aforementioned. Thus, to summarise, the main aim of the present work was to combine somehow these separated approaches, mechanisms and tools for annotation from Linguistics and Ontological Engineering (and the Semantic Web) in a sort of hybrid (linguistic and ontological) annotation model, suitable for both areas. This hybrid (semantic) annotation model should (a) benefit from the advances, models, techniques, mechanisms and tools of these two areas; (b) minimise (and even solve, when possible) some of the problems found in each of them; and (c) be suitable for the Semantic Web. The concrete goals that helped attain this aim are presented in the following section. 2. GOALS OF THE PRESENT WORK As mentioned above, the main goal of this work was to specify a hybrid (that is, linguistically-motivated and ontology-based) model of annotation suitable for the Semantic Web (i.e. it had to produce a semantic annotation of web page contents). This entailed that the tags included in the annotations of the model had to (1) represent linguistic concepts (or linguistic categories, as they are termed in ISO/DCR (2008)), in order for this model to be linguistically-motivated; (2) be ontological terms (i.e., use an ontological vocabulary), in order for the model to be ontology-based; and (3) be structured (linked) as a collection of ontology-based triples, as in the usual Semantic Web languages (namely RDF(S) and OWL), in order for the model to be considered suitable for the Semantic Web. Besides, to be useful for the Semantic Web, this model should provide a way to automate the annotation of web pages. As for the present work, this requirement involved reusing the linguistic annotation tools purchased by the OEG research group (http://www.oeg-upm.net), but solving beforehand (or, at least, minimising) some of their limitations. Therefore, this model had to minimise these limitations by means of the integration of several linguistic annotation tools into a common architecture. Since this integration required the interoperation of tools and their annotations, ontologies were proposed as the main technological component to make them effectively interoperate. From the very beginning, it seemed that the formalisation of the elements and the knowledge underlying linguistic annotations within an appropriate set of ontologies would be a great step forward towards the formulation of such a model (henceforth referred to as OntoTag). Obviously, first, to combine the results of the linguistic annotation tools that operated at the same level, their annotation schemas had to be unified (or, preferably, standardised) in advance. This entailed the unification (id. standardisation) of their tags (both their representation and their meaning), and their format or syntax. Second, to merge the results of the linguistic annotation tools operating at different levels, their respective annotation schemas had to be (a) made interoperable and (b) integrated. And third, in order for the resulting annotations to suit the Semantic Web, they had to be specified by means of an ontology-based vocabulary, and structured by means of ontology-based triples, as hinted above. Therefore, a new annotation scheme had to be devised, based both on ontologies and on this type of triples, which allowed for the combination and the integration of the annotations of any set of linguistic annotation tools. This annotation scheme was considered a fundamental part of the model proposed here, and its development was, accordingly, another major objective of the present work. All these goals, aims and objectives could be re-stated more clearly as follows: Goal 1: Development of a set of ontologies for the formalisation of the linguistic knowledge relating linguistic annotation. Sub-goal 1.1: Ontological formalisation of the EAGLES (1996a; 1996b) de facto standards for morphosyntactic and syntactic annotation, in a way that helps respect the triple structure recommended for annotations in these works (which is isomorphic to the triple structures used in the context of the Semantic Web). Sub-goal 1.2: Incorporation into this preliminary ontological formalisation of other existing standards and standard proposals relating the levels mentioned above, such as those currently under development within ISO/TC 37 (the ISO Technical Committee dealing with Terminology, which deals also with linguistic resources and annotations). Sub-goal 1.3: Generalisation and extension of the recommendations in EAGLES (1996a; 1996b) and ISO/TC 37 to the semantic level, for which no ISO/TC 37 standards have been developed yet. Sub-goal 1.4: Ontological formalisation of the generalisations and/or extensions obtained in the previous sub-goal as generalisations and/or extensions of the corresponding ontology (or ontologies). Sub-goal 1.5: Ontological formalisation of the knowledge required to link, combine and unite the knowledge represented in the previously developed ontology (or ontologies). Goal 2: Development of OntoTag’s annotation scheme, a standard-based abstract scheme for the hybrid (linguistically-motivated and ontological-based) annotation of texts. Sub-goal 2.1: Development of the standard-based morphosyntactic annotation level of OntoTag’s scheme. This level should include, and possibly extend, the recommendations of EAGLES (1996a) and also the recommendations included in the ISO/MAF (2008) standard draft. Sub-goal 2.2: Development of the standard-based syntactic annotation level of the hybrid abstract scheme. This level should include, and possibly extend, the recommendations of EAGLES (1996b) and the ISO/SynAF (2010) standard draft. Sub-goal 2.3: Development of the standard-based semantic annotation level of OntoTag’s (abstract) scheme. Sub-goal 2.4: Development of the mechanisms for a convenient integration of the three annotation levels already mentioned. These mechanisms should take into account the recommendations included in the ISO/LAF (2009) standard draft. Goal 3: Design of OntoTag’s (abstract) annotation architecture, an abstract architecture for the hybrid (semantic) annotation of texts (i) that facilitates the integration and interoperation of different linguistic annotation tools, and (ii) whose results comply with OntoTag’s annotation scheme. Sub-goal 3.1: Specification of the decanting processes that allow for the classification and separation, according to their corresponding levels, of the results of the linguistic tools annotating at several different levels. Sub-goal 3.2: Specification of the standardisation processes that allow (a) complying with the standardisation requirements of OntoTag’s annotation scheme, as well as (b) combining the results of those linguistic tools that share some level of annotation. Sub-goal 3.3: Specification of the merging processes that allow for the combination of the output annotations and the interoperation of those linguistic tools that share some level of annotation. Sub-goal 3.4: Specification of the merge processes that allow for the integration of the results and the interoperation of those tools performing their annotations at different levels. Goal 4: Generation of OntoTagger’s schema, a concrete instance of OntoTag’s abstract scheme for a concrete set of linguistic annotations. These linguistic annotations result from the tools and the resources available in the research group, namely • Bitext’s DataLexica (http://www.bitext.com/EN/datalexica.asp), • LACELL’s (POS) tagger (http://www.um.es/grupos/grupo-lacell/quees.php), • Connexor’s FDG (http://www.connexor.eu/technology/machinese/glossary/fdg/), and • EuroWordNet (Vossen et al., 1998). This schema should help evaluate OntoTag’s underlying hypotheses, stated below. Consequently, it should implement, at least, those levels of the abstract scheme dealing with the annotations of the set of tools considered in this implementation. This includes the morphosyntactic, the syntactic and the semantic levels. Goal 5: Implementation of OntoTagger’s configuration, a concrete instance of OntoTag’s abstract architecture for this set of linguistic tools and annotations. This configuration (1) had to use the schema generated in the previous goal; and (2) should help support or refute the hypotheses of this work as well (see the next section). Sub-goal 5.1: Implementation of the decanting processes that facilitate the classification and separation of the results of those linguistic resources that provide annotations at several different levels (on the one hand, LACELL’s tagger operates at the morphosyntactic level and, minimally, also at the semantic level; on the other hand, FDG operates at the morphosyntactic and the syntactic levels and, minimally, at the semantic level as well). Sub-goal 5.2: Implementation of the standardisation processes that allow (i) specifying the results of those linguistic tools that share some level of annotation according to the requirements of OntoTagger’s schema, as well as (ii) combining these shared level results. In particular, all the tools selected perform morphosyntactic annotations and they had to be conveniently combined by means of these processes. Sub-goal 5.3: Implementation of the merging processes that allow for the combination (and possibly the improvement) of the annotations and the interoperation of the tools that share some level of annotation (in particular, those relating the morphosyntactic level, as in the previous sub-goal). Sub-goal 5.4: Implementation of the merging processes that allow for the integration of the different standardised and combined annotations aforementioned, relating all the levels considered. Sub-goal 5.5: Improvement of the semantic level of this configuration by adding a named entity recognition, (sub-)classification and annotation subsystem, which also uses the named entities annotated to populate a domain ontology, in order to provide a concrete application of the present work in the two areas involved (the Semantic Web and Corpus Linguistics). 3. MAIN RESULTS: ASSESSMENT OF ONTOTAG’S UNDERLYING HYPOTHESES The model developed in the present thesis tries to shed some light on (i) whether linguistic annotation tools can effectively interoperate; (ii) whether their results can be combined and integrated; and, if they can, (iii) how they can, respectively, interoperate and be combined and integrated. Accordingly, several hypotheses had to be supported (or rejected) by the development of the OntoTag model and OntoTagger (its implementation). The hypotheses underlying OntoTag are surveyed below. Only one of the hypotheses (H.6) was rejected; the other five could be confirmed. H.1 The annotations of different levels (or layers) can be integrated into a sort of overall, comprehensive, multilayer and multilevel annotation, so that their elements can complement and refer to each other. • CONFIRMED by the development of: o OntoTag’s annotation scheme, o OntoTag’s annotation architecture, o OntoTagger’s (XML, RDF, OWL) annotation schemas, o OntoTagger’s configuration. H.2 Tool-dependent annotations can be mapped onto a sort of tool-independent annotations and, thus, can be standardised. • CONFIRMED by means of the standardisation phase incorporated into OntoTag and OntoTagger for the annotations yielded by the tools. H.3 Standardisation should ease: H.3.1: The interoperation of linguistic tools. H.3.2: The comparison, combination (at the same level and layer) and integration (at different levels or layers) of annotations. • H.3 was CONFIRMED by means of the development of OntoTagger’s ontology-based configuration: o Interoperation, comparison, combination and integration of the annotations of three different linguistic tools (Connexor’s FDG, Bitext’s DataLexica and LACELL’s tagger); o Integration of EuroWordNet-based, domain-ontology-based and named entity annotations at the semantic level. o Integration of morphosyntactic, syntactic and semantic annotations. H.4 Ontologies and Semantic Web technologies (can) play a crucial role in the standardisation of linguistic annotations, by providing consensual vocabularies and standardised formats for annotation (e.g., RDF triples). • CONFIRMED by means of the development of OntoTagger’s RDF-triple-based annotation schemas. H.5 The rate of errors introduced by a linguistic tool at a given level, when annotating, can be reduced automatically by contrasting and combining its results with the ones coming from other tools, operating at the same level. However, these other tools might be built following a different technological (stochastic vs. rule-based, for example) or theoretical (dependency vs. HPS-grammar-based, for instance) approach. • CONFIRMED by the results yielded by the evaluation of OntoTagger. H.6 Each linguistic level can be managed and annotated independently. • REJECTED: OntoTagger’s experiments and the dependencies observed among the morphosyntactic annotations, and between them and the syntactic annotations. In fact, Hypothesis H.6 was already rejected when OntoTag’s ontologies were developed. We observed then that several linguistic units stand on an interface between levels, belonging thereby to both of them (such as morphosyntactic units, which belong to both the morphological level and the syntactic level). Therefore, the annotations of these levels overlap and cannot be handled independently when merged into a unique multileveled annotation. 4. OTHER MAIN RESULTS AND CONTRIBUTIONS First, interoperability is a hot topic for both the linguistic annotation community and the whole Computer Science field. The specification (and implementation) of OntoTag’s architecture for the combination and integration of linguistic (annotation) tools and annotations by means of ontologies shows a way to make these different linguistic annotation tools and annotations interoperate in practice. Second, as mentioned above, the elements involved in linguistic annotation were formalised in a set (or network) of ontologies (OntoTag’s linguistic ontologies). • On the one hand, OntoTag’s network of ontologies consists of − The Linguistic Unit Ontology (LUO), which includes a mostly hierarchical formalisation of the different types of linguistic elements (i.e., units) identifiable in a written text; − The Linguistic Attribute Ontology (LAO), which includes also a mostly hierarchical formalisation of the different types of features that characterise the linguistic units included in the LUO; − The Linguistic Value Ontology (LVO), which includes the corresponding formalisation of the different values that the attributes in the LAO can take; − The OIO (OntoTag’s Integration Ontology), which  Includes the knowledge required to link, combine and unite the knowledge represented in the LUO, the LAO and the LVO;  Can be viewed as a knowledge representation ontology that describes the most elementary vocabulary used in the area of annotation. • On the other hand, OntoTag’s ontologies incorporate the knowledge included in the different standards and recommendations for linguistic annotation released so far, such as those developed within the EAGLES and the SIMPLE European projects or by the ISO/TC 37 committee: − As far as morphosyntactic annotations are concerned, OntoTag’s ontologies formalise the terms in the EAGLES (1996a) recommendations and their corresponding terms within the ISO Morphosyntactic Annotation Framework (ISO/MAF, 2008) standard; − As for syntactic annotations, OntoTag’s ontologies incorporate the terms in the EAGLES (1996b) recommendations and their corresponding terms within the ISO Syntactic Annotation Framework (ISO/SynAF, 2010) standard draft; − Regarding semantic annotations, OntoTag’s ontologies generalise and extend the recommendations in EAGLES (1996a; 1996b) and, since no stable standards or standard drafts have been released for semantic annotation by ISO/TC 37 yet, they incorporate the terms in SIMPLE (2000) instead; − The terms coming from all these recommendations and standards were supplemented by those within the ISO Data Category Registry (ISO/DCR, 2008) and also of the ISO Linguistic Annotation Framework (ISO/LAF, 2009) standard draft when developing OntoTag’s ontologies. Third, we showed that the combination of the results of tools annotating at the same level can yield better results (both in precision and in recall) than each tool separately. In particular, 1. OntoTagger clearly outperformed two of the tools integrated into its configuration, namely DataLexica and FDG in all the combination sub-phases in which they overlapped (i.e. POS tagging, lemma annotation and morphological feature annotation). As far as the remaining tool is concerned, i.e. LACELL’s tagger, it was also outperformed by OntoTagger in POS tagging and lemma annotation, and it did not behave better than OntoTagger in the morphological feature annotation layer. 2. As an immediate result, this implies that a) This type of combination architecture configurations can be applied in order to improve significantly the accuracy of linguistic annotations; and b) Concerning the morphosyntactic level, this could be regarded as a way of constructing more robust and more accurate POS tagging systems. Fourth, Semantic Web annotations are usually performed by humans or else by machine learning systems. Both of them leave much to be desired: the former, with respect to their annotation rate; the latter, with respect to their (average) precision and recall. In this work, we showed how linguistic tools can be wrapped in order to annotate automatically Semantic Web pages using ontologies. This entails their fast, robust and accurate semantic annotation. As a way of example, as mentioned in Sub-goal 5.5, we developed a particular OntoTagger module for the recognition, classification and labelling of named entities, according to the MUC and ACE tagsets (Chinchor, 1997; Doddington et al., 2004). These tagsets were further specified by means of a domain ontology, namely the Cinema Named Entities Ontology (CNEO). This module was applied to the automatic annotation of ten different web pages containing cinema reviews (that is, around 5000 words). In addition, the named entities annotated with this module were also labelled as instances (or individuals) of the classes included in the CNEO and, then, were used to populate this domain ontology. • The statistical results obtained from the evaluation of this particular module of OntoTagger can be summarised as follows. On the one hand, as far as recall (R) is concerned, (R.1) the lowest value was 76,40% (for file 7); (R.2) the highest value was 97, 50% (for file 3); and (R.3) the average value was 88,73%. On the other hand, as far as the precision rate (P) is concerned, (P.1) its minimum was 93,75% (for file 4); (R.2) its maximum was 100% (for files 1, 5, 7, 8, 9, and 10); and (R.3) its average value was 98,99%. • These results, which apply to the tasks of named entity annotation and ontology population, are extraordinary good for both of them. They can be explained on the basis of the high accuracy of the annotations provided by OntoTagger at the lower levels (mainly at the morphosyntactic level). However, they should be conveniently qualified, since they might be too domain- and/or language-dependent. It should be further experimented how our approach works in a different domain or a different language, such as French, English, or German. • In any case, the results of this application of Human Language Technologies to Ontology Population (and, accordingly, to Ontological Engineering) seem very promising and encouraging in order for these two areas to collaborate and complement each other in the area of semantic annotation. Fifth, as shown in the State of the Art of this work, there are different approaches and models for the semantic annotation of texts, but all of them focus on a particular view of the semantic level. Clearly, all these approaches and models should be integrated in order to bear a coherent and joint semantic annotation level. OntoTag shows how (i) these semantic annotation layers could be integrated together; and (ii) they could be integrated with the annotations associated to other annotation levels. Sixth, we identified some recommendations, best practices and lessons learned for annotation standardisation, interoperation and merge. They show how standardisation (via ontologies, in this case) enables the combination, integration and interoperation of different linguistic tools and their annotations into a multilayered (or multileveled) linguistic annotation, which is one of the hot topics in the area of Linguistic Annotation. And last but not least, OntoTag’s annotation scheme and OntoTagger’s annotation schemas show a way to formalise and annotate coherently and uniformly the different units and features associated to the different levels and layers of linguistic annotation. This is a great scientific step ahead towards the global standardisation of this area, which is the aim of ISO/TC 37 (in particular, Subcommittee 4, dealing with the standardisation of linguistic annotations and resources).

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The article deals with the topicality and problems of using information and communication technologies in secondary education, conditions and methods for Ukrainian language learning with the distance support in senior classes. The article shows the principal similarity of distance learning to training one. The common and specific principles of creation of teaching materials for a distance learning course are described. It reveals the conditions of effective organization of Ukrainian language learning with distance support on the material of distance course “Business Ukrainian and Culture of Communication”.

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In order to develop scientific literacy students need the cognitive tools that enable them to read and evaluate science texts. One cognitive tool that has been widely used in science education to aid the development of conceptual understanding is concept mapping. However, it has been found some students experience difficulty with concept map construction. This study reports on the development and evaluation of an instructional sequence that was used to scaffold the concept-mapping process when middle school students who were experiencing difficulty with science learning used concept mapping to summarise a chapter of a science text. In this study individual differences in working memory functioning are suggested as one reason that students experience difficulty with concept map construction. The study was conducted using a design-based research methodology in the school’s learning support centre. The analysis of student work samples collected during the two-year study identified some of the difficulties and benefits associated with the use of scaffolded concept mapping with these students. The observations made during this study highlight the difficulty that some students experience with the use of concept mapping as a means of developing an understanding of science concepts and the amount of instructional support that is required for such understanding to develop. Specifically, the findings of the study support the use of multi-component, multi-modal instructional techniques to facilitate the development of conceptual understanding with students who experience difficulty with science learning. In addition, the important roles of interactive dialogue and metacognition in the development of conceptual understanding are identified.

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The advancement of online teaching environments during the past several years presents an exciting opportunity to extend existing teaching methodologies. The software package known as Elluminate is one example of a virtual classroom, facilitating the provision of real time interaction, collaboration and group meetings. This paper will examine the use of Elluminate in the teaching of large classes. The use of such technology for large classes is of particular interest, as large classes are often, unfairly, associated with a reputation for being impersonal as well as notions of conveyor belt learning. In this paper the potential to extend teaching and learning opportunities using Elluminate, in the context of large classes, will be explored. It will be shown that the use of technology such as Elluminate can assist in providing students with a more flexible means of accessing academic support, as well as allowing for a customised delivery of course content so as to focus learning outcomes.

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As increasing numbers of Chinese language learners choose to learn English online (CNNIC, 2012), there is a need to investigate popular websites and their language learning designs. This paper reports on the first stage of a study that analysed the pedagogical, linguistic and content features of 25 Chinese English Language Learning (ELL) websites ranked according to their value and importance to users. The website ranking was undertaken using a system known as PageRank. The aim of the study was to identify the features characterising popular sites as opposed to those of less popular sites for the purpose of producing a framework for ELL website design in the Chinese context. The study found that a pedagogical focus with developmental instructional materials accommodating diverse proficiency levels was a major contributor to website popularity. Chinese language use for translations and teaching directives and intermediate level English for learning materials were also significant features. Content topics included Anglophone/Western and non-Anglophone/Eastern contexts. Overall, popular websites were distinguished by their mediation of access to and scaffolded support for ELL.

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The linguistic turn within philosophy has recently gained increased attention within social sciences. It can be seen as an attempt to investigate traditional philosophical problems by analysing the linguistic expressions used for these investigations. More generally, the phenomenon of language itself must be considered because of its (constitutional) impact on the investigation of phenomena in social sciences. In order to understand the consequences of the linguistic turn, its origins in philosophy are important and will be discussed. Within social sciences the linguistic turn already had significant impact. As an example, we will therefore discuss what directions the linguistic turn enabled for organizational analysis. Information Systems as a discipline must face the consequences of the linguistic turn as well. We will discuss how the linguistic framework introduced impacts the development of knowledge management and that of managerial and organizational support systems. This example shows what different perspectives the linguistic turn can provide for investigations within Information Systems. In addition, we will briefly outline the impact of the linguistic turn with respect to methodologies in Information Systems research.

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Currently, the GNSS computing modes are of two classes: network-based data processing and user receiver-based processing. A GNSS reference receiver station essentially contributes raw measurement data in either the RINEX file format or as real-time data streams in the RTCM format. Very little computation is carried out by the reference station. The existing network-based processing modes, regardless of whether they are executed in real-time or post-processed modes, are centralised or sequential. This paper describes a distributed GNSS computing framework that incorporates three GNSS modes: reference station-based, user receiver-based and network-based data processing. Raw data streams from each GNSS reference receiver station are processed in a distributed manner, i.e., either at the station itself or at a hosting data server/processor, to generate station-based solutions, or reference receiver-specific parameters. These may include precise receiver clock, zenith tropospheric delay, differential code biases, ambiguity parameters, ionospheric delays, as well as line-of-sight information such as azimuth and elevation angles. Covariance information for estimated parameters may also be optionally provided. In such a mode the nearby precise point positioning (PPP) or real-time kinematic (RTK) users can directly use the corrections from all or some of the stations for real-time precise positioning via a data server. At the user receiver, PPP and RTK techniques are unified under the same observation models, and the distinction is how the user receiver software deals with corrections from the reference station solutions and the ambiguity estimation in the observation equations. Numerical tests demonstrate good convergence behaviour for differential code bias and ambiguity estimates derived individually with single reference stations. With station-based solutions from three reference stations within distances of 22–103 km the user receiver positioning results, with various schemes, show an accuracy improvement of the proposed station-augmented PPP and ambiguity-fixed PPP solutions with respect to the standard float PPP solutions without station augmentation and ambiguity resolutions. Overall, the proposed reference station-based GNSS computing mode can support PPP and RTK positioning services as a simpler alternative to the existing network-based RTK or regionally augmented PPP systems.

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The acyl composition of membrane phospholipids in kidney and brain of mammals of different body mass was examined. It was hypothesized that reduction in unsaturation index (number of double bonds per 100 acyl chains) of membrane phospholipids with increasing body mass in mammals would be made-up of similar changes in acyl composition across all phospholipid classes and that phospholipid class distribution would be regulated and similar in the same tissues of the different-sized mammals. The results of this study supported both hypotheses. Differences in membrane phospholipid acyl composition (i. e. decreased omega-3 fats, increased monounsaturated fats and decreased unsaturation index with increasing body size) were not restricted to any specific phospholipid molecule or to any specific phospholipid class but were observed in all phospholipid classes. With increase in body mass of mammals both monounsaturates and use of less unsaturated polyunsaturates increases at the expense of the long-chain highly unsaturated omega-3 and omega-6 polyunsaturates, producing decreases in membrane unsaturation. The distribution of membrane phospholipid classes was essentially the same in the different-sized mammals with phosphatidylcholine (PC) and phosphatidylethanolamine (PE) together constituting similar to 91% and similar to 88% of all phospholipids in kidney and brain, respectively. The lack of sphingomyelin in the mouse tissues and higher levels in larger mammals suggests an increased presence of membrane lipid rafts in larger mammals. The results of this study support the proposal that the physical properties of membranes are likely to be involved in changing metabolic rate.