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Автор: Grafiati
Опубліковано: 10 грудня 2022
Оновлено: 28 січня 2023

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Статті в журналах з теми "Cross-language learning"

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Nayan, Surina, Hariharan N. Krishnasamy, and Latisha Asmaak Shafie. "A Cross-National Study of Motivation in Language Learning." International Journal of Information and Education Technology 4, no. 2 (2014): 194–97. http://dx.doi.org/10.7763/ijiet.2014.v4.397.

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Anderson, Neil J., and Terence Odlin. "Language Transfer: Cross Linguistic Influence in Language Learning." Modern Language Journal 76, no. 1 (1992): 82. http://dx.doi.org/10.2307/329911.

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Schachter, Jacquelyn, and Terence Odlin. "Language Transfer: Cross-Linguistic Influence in Language Learning." Language 67, no. 1 (March 1991): 155. http://dx.doi.org/10.2307/415550.

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4

Ringbom, Håkan. "Language transfer. Cross-linguistic influence in language learning." System 18, no. 3 (January 1990): 392–93. http://dx.doi.org/10.1016/0346-251x(90)90015-w.

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5

Solodka, Anzhelika, Oksana Filatova, Oksana Hinkevych, and Oleksandr Spanatiy. "Cross-cultural Language Learning: Interpretative Engagement." Arab World English Journal 12, no. 3 (September 15, 2021): 82–96. http://dx.doi.org/10.24093/awej/vol12no3.6.

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Conceptualization of foreign language teaching as a cross-cultural interaction means engaging learners in various cultural mediations. Language use becomes a form of interpretative architecture of a target language. Understanding language use from a discursive perspective develops meta-pragmatic awareness and interpretative capacities of learners. The study answers the question of how to design the architecture of context analysis. This research aims to determine the effective ways of interpretative engagement of learners with aspects of pragmatics in the Ukrainian university setting. The study investigates how the process of interaction shapes the engagement of learners in practices of noticing, reflection, and comparison of cross-cultural situations. The data came from a case study on cross-cultural language learning within the second semester, 2021. The study analyzes the audio-recording of the classes, researcher notes, and post-course interviews of 24 participants. This research used a method of the content analysis. The study of the results, based on six categories (narrative analysis, discourse analysis, semiotic analysis, interpretative analyses, conversation analysis, and critical analysis), showed that the learners started to consider the nature of their cross-cultural mediation. The research proved that through such an interpretative engagement, students become engaged into working with languages and cultures. The study presents some recommendations for language teachers to create a meaning-making process from multiple perspectives.
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Vidgren, Noora. "Cross-linguistic similarity in foreign language learning." International Journal of Multilingualism 8, no. 2 (May 2011): 151–53. http://dx.doi.org/10.1080/14790718.2011.552237.

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7

Zhou, Zhonghao. "Cross-cultural Training and Second Language Learning." Asian Education Studies 2, no. 3 (September 19, 2017): 1. http://dx.doi.org/10.20849/aes.v2i3.176.

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Culture and language are inseparable, and cultures as groups adopt particular practices and norms of behavior. Culture teaching is a long and complex process concerning something more than language use itself. The two popular theories influencing practice today are the Constructivist and the Creative Constructionist approaches, and the technique for conveying cultural awareness is cultural assimilator, which has been designed for specific cultures around the world. Cross-cultural training can be used to promote cultural awareness, that is, sensitize people to the influence of culture on people’s values and behaviors and help them recognize and accept the existence of cultural differences.
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Taghizadeh, Nasrin, Heshaam Faili, and Jalal Maleki. "Cross-Language Learning for Arabic Relation Extraction." Procedia Computer Science 142 (2018): 190–97. http://dx.doi.org/10.1016/j.procs.2018.10.475.

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Havas, Viktória, Otto Waris, Lucía Vaquero, Antoni Rodríguez-Fornells, and Matti Laine. "Morphological learning in a novel language: A cross-language comparison." Quarterly Journal of Experimental Psychology 68, no. 7 (July 2015): 1426–41. http://dx.doi.org/10.1080/17470218.2014.983531.

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McCauley, Stewart M., and Morten H. Christiansen. "Language learning as language use: A cross-linguistic model of child language development." Psychological Review 126, no. 1 (January 2019): 1–51. http://dx.doi.org/10.1037/rev0000126.

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Дисертації з теми "Cross-language learning"

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Hjelm, Hans. "Cross-language Ontology Learning : Incorporating and Exploiting Cross-language Data in the Ontology Learning Process." Doctoral thesis, Stockholms universitet, Institutionen för lingvistik, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-8414.

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An ontology is a knowledge-representation structure, where words, terms or concepts are defined by their mutual hierarchical relations. Ontologies are becoming ever more prevalent in the world of natural language processing, where we currently see a tendency towards using semantics for solving a variety of tasks, particularly tasks related to information access. Ontologies, taxonomies and thesauri (all related notions) are also used in various variants by humans, to standardize business transactions or for finding conceptual relations between terms in, e.g., the medical domain. The acquisition of machine-readable, domain-specific semantic knowledge is time consuming and prone to inconsistencies. The field of ontology learning therefore provides tools for automating the construction of domain ontologies (ontologies describing the entities and relations within a particular field of interest), by analyzing large quantities of domain-specific texts. This thesis studies three main topics within the field of ontology learning. First, we examine which sources of information are useful within an ontology learning system and how the information sources can be combined effectively. Secondly, we do this with a special focus on cross-language text collections, to see if we can learn more from studying several languages at once, than we can from a single-language text collection. Finally, we investigate new approaches to formal and automatic evaluation of the quality of a learned ontology. We demonstrate how to combine information sources from different languages and use them to train automatic classifiers to recognize lexico-semantic relations. The cross-language data is shown to have a positive effect on the quality of the learned ontologies. We also give theoretical and experimental results, showing that our ontology evaluation method is a good complement to and in some aspects improves on the evaluation measures in use today.
För att köpa boken skicka en beställning till exp@ling.su.se/ To order the book send an e-mail to exp@ling.su.se
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Woldemariam, Yonas Demeke. "Natural language processing in cross-media analysis." Licentiate thesis, Umeå universitet, Institutionen för datavetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-147640.

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A cross-media analysis framework is an integrated multi-modal platform where a media resource containing different types of data such as text, images, audio and video is analyzed with metadata extractors, working jointly to contextualize the media resource. It generally provides cross-media analysis and automatic annotation, metadata publication and storage, searches and recommendation services. For on-line content providers, such services allow them to semantically enhance a media resource with the extracted metadata representing the hidden meanings and make it more efficiently searchable. Within the architecture of such frameworks, Natural Language Processing (NLP) infrastructures cover a substantial part. The NLP infrastructures include text analysis components such as a parser, named entity extraction and linking, sentiment analysis and automatic speech recognition. Since NLP tools and techniques are originally designed to operate in isolation, integrating them in cross-media frameworks and analyzing textual data extracted from multimedia sources is very challenging. Especially, the text extracted from audio-visual content lack linguistic features that potentially provide important clues for text analysis components. Thus, there is a need to develop various techniques to meet the requirements and design principles of the frameworks. In our thesis, we explore developing various methods and models satisfying text and speech analysis requirements posed by cross-media analysis frameworks. The developed methods allow the frameworks to extract linguistic knowledge of various types and predict various information such as sentiment and competence. We also attempt to enhance the multilingualism of the frameworks by designing an analysis pipeline that includes speech recognition, transliteration and named entity recognition for Amharic, that also enables the accessibility of Amharic contents on the web more efficiently. The method can potentially be extended to support other under-resourced languages.
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Mau, Pui-sze Priscilla. "Cross-language transfer of phonological awareness in Chinese-English bilinguals." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B36889301.

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Mau, Pui-sze Priscilla, and 繆佩詩. "Cross-language transfer of phonological awareness in Chinese-English bilinguals." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B36889301.

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Mogofe, Romulus Asaph. "Integrating language literacy skills in teaching physical sciences in Riba Cross District, South Africa." Thesis, University of Limpopo, 2016. http://hdl.handle.net/10386/1590.

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Thesis (M. A. (Education)) -- University of Limpopo, 2016
Poor performance, by English Language Learners (ELLs), in Science examinations remains a thorny issue in countries where English is not the home language. Research around the world and the Department of Basic Education in South Africa have long recommended the integration of Language Literacy skills in the teaching of Physical Sciences in order to solve this issue. Despite that, learners’ poor performance in Physical Sciences examinations has been found to be positively related to low language literacy skills. The questions are: Do Physical Sciences teachers integrate language literacy skills in teaching the subject?; If yes, to what extent is the integration of language literacy skills practiced in Physical Sciences classroom? In an attempt to answer the above questions, a quantitative survey was carried out in Riba Cross District of Sekhukhune Region of Limpopo Province in South Africa. 211 learners and five teachers from selected nine schools took part in the study and questionnaires were used to collect data. Data were analysed using descriptive and inferential statistics and the Statistical Package for the Social Sciences (SPSS) version 22 was used. The results indicate that Language Literacy skills are integrated into the teaching of Physical Sciences in Riba Cross District, despite concerns raised by the teachers. The areas of concern include letting learners to argue using evidences and writing reports. Furthermore, schools with large classes have challenges in integrating Language Literacy Skills in the teaching of Physical Sciences. Therefore, further studies are recommended which should integrate both qualitative and quantitative approaches in school contexts.
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6

Lennane, B. Michael. "Cross-cultural influences on corrective feedback preferences in English language instruction." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=112502.

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This cross-cultural study examined the preferences of 137 Taiwanese EFL students and 97 ESL Quebecois students for specific types of corrective feedback, as well as their attitudes and beliefs about error correction, and those of 12 Taiwanese English instructors and 12 native English teachers in Quebec. All participants completed two questionnaires, the first eliciting overall preferences and attitudes for corrective feedback, and the second eliciting preferences for specific types of feedback aurally modeled through a digital recording designed for the purpose of this study. In addition, a subsample of participants was selected for follow-up interviews. Descriptive analysis of the initial questionnaire coupled with trends found in interview data revealed cross-cultural differences in preferences for types of errors to correct, the use of correction, rates of correction and affective reactions to error correction. However, statistical analysis of the data yielded by the main elicitation instrument revealed similar preferences within both cultural groups, with explicit correction being ranked highest, followed by recasts and then prompts.
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7

Gupta, Parth Alokkumar. "Cross-view Embeddings for Information Retrieval." Doctoral thesis, Universitat Politècnica de València, 2017. http://hdl.handle.net/10251/78457.

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In this dissertation, we deal with the cross-view tasks related to information retrieval using embedding methods. We study existing methodologies and propose new methods to overcome their limitations. We formally introduce the concept of mixed-script IR, which deals with the challenges faced by an IR system when a language is written in different scripts because of various technological and sociological factors. Mixed-script terms are represented by a small and finite feature space comprised of character n-grams. We propose the cross-view autoencoder (CAE) to model such terms in an abstract space and CAE provides the state-of-the-art performance. We study a wide variety of models for cross-language information retrieval (CLIR) and propose a model based on compositional neural networks (XCNN) which overcomes the limitations of the existing methods and achieves the best results for many CLIR tasks such as ad-hoc retrieval, parallel sentence retrieval and cross-language plagiarism detection. We empirically test the proposed models for these tasks on publicly available datasets and present the results with analyses. In this dissertation, we also explore an effective method to incorporate contextual similarity for lexical selection in machine translation. Concretely, we investigate a feature based on context available in source sentence calculated using deep autoencoders. The proposed feature exhibits statistically significant improvements over the strong baselines for English-to-Spanish and English-to-Hindi translation tasks. Finally, we explore the the methods to evaluate the quality of autoencoder generated representations of text data and analyse its architectural properties. For this, we propose two metrics based on reconstruction capabilities of the autoencoders: structure preservation index (SPI) and similarity accumulation index (SAI). We also introduce a concept of critical bottleneck dimensionality (CBD) below which the structural information is lost and present analyses linking CBD and language perplexity.
En esta disertación estudiamos problemas de vistas-múltiples relacionados con la recuperación de información utilizando técnicas de representación en espacios de baja dimensionalidad. Estudiamos las técnicas existentes y proponemos nuevas técnicas para solventar algunas de las limitaciones existentes. Presentamos formalmente el concepto de recuperación de información con escritura mixta, el cual trata las dificultades de los sistemas de recuperación de información cuando los textos contienen escrituras en distintos alfabetos debido a razones tecnológicas y socioculturales. Las palabras en escritura mixta son representadas en un espacio de características finito y reducido, compuesto por n-gramas de caracteres. Proponemos los auto-codificadores de vistas-múltiples (CAE, por sus siglas en inglés) para modelar dichas palabras en un espacio abstracto, y esta técnica produce resultados de vanguardia. En este sentido, estudiamos varios modelos para la recuperación de información entre lenguas diferentes (CLIR, por sus siglas en inglés) y proponemos un modelo basado en redes neuronales composicionales (XCNN, por sus siglas en inglés), el cual supera las limitaciones de los métodos existentes. El método de XCNN propuesto produce mejores resultados en diferentes tareas de CLIR tales como la recuperación de información ad-hoc, la identificación de oraciones equivalentes en lenguas distintas y la detección de plagio entre lenguas diferentes. Para tal efecto, realizamos pruebas experimentales para dichas tareas sobre conjuntos de datos disponibles públicamente, presentando los resultados y análisis correspondientes. En esta disertación, también exploramos un método eficiente para utilizar similitud semántica de contextos en el proceso de selección léxica en traducción automática. Específicamente, proponemos características extraídas de los contextos disponibles en las oraciones fuentes mediante el uso de auto-codificadores. El uso de las características propuestas demuestra mejoras estadísticamente significativas sobre sistemas de traducción robustos para las tareas de traducción entre inglés y español, e inglés e hindú. Finalmente, exploramos métodos para evaluar la calidad de las representaciones de datos de texto generadas por los auto-codificadores, a la vez que analizamos las propiedades de sus arquitecturas. Como resultado, proponemos dos nuevas métricas para cuantificar la calidad de las reconstrucciones generadas por los auto-codificadores: el índice de preservación de estructura (SPI, por sus siglas en inglés) y el índice de acumulación de similitud (SAI, por sus siglas en inglés). También presentamos el concepto de dimensión crítica de cuello de botella (CBD, por sus siglas en inglés), por debajo de la cual la información estructural se deteriora. Mostramos que, interesantemente, la CBD está relacionada con la perplejidad de la lengua.
En aquesta dissertació estudiem els problemes de vistes-múltiples relacionats amb la recuperació d'informació utilitzant tècniques de representació en espais de baixa dimensionalitat. Estudiem les tècniques existents i en proposem unes de noves per solucionar algunes de les limitacions existents. Presentem formalment el concepte de recuperació d'informació amb escriptura mixta, el qual tracta les dificultats dels sistemes de recuperació d'informació quan els textos contenen escriptures en diferents alfabets per motius tecnològics i socioculturals. Les paraules en escriptura mixta són representades en un espai de característiques finit i reduït, composat per n-grames de caràcters. Proposem els auto-codificadors de vistes-múltiples (CAE, per les seves sigles en anglès) per modelar aquestes paraules en un espai abstracte, i aquesta tècnica produeix resultats d'avantguarda. En aquest sentit, estudiem diversos models per a la recuperació d'informació entre llengües diferents (CLIR , per les sevas sigles en anglès) i proposem un model basat en xarxes neuronals composicionals (XCNN, per les sevas sigles en anglès), el qual supera les limitacions dels mètodes existents. El mètode de XCNN proposat produeix millors resultats en diferents tasques de CLIR com ara la recuperació d'informació ad-hoc, la identificació d'oracions equivalents en llengües diferents, i la detecció de plagi entre llengües diferents. Per a tal efecte, realitzem proves experimentals per aquestes tasques sobre conjunts de dades disponibles públicament, presentant els resultats i anàlisis corresponents. En aquesta dissertació, també explorem un mètode eficient per utilitzar similitud semàntica de contextos en el procés de selecció lèxica en traducció automàtica. Específicament, proposem característiques extretes dels contextos disponibles a les oracions fonts mitjançant l'ús d'auto-codificadors. L'ús de les característiques proposades demostra millores estadísticament significatives sobre sistemes de traducció robustos per a les tasques de traducció entre anglès i espanyol, i anglès i hindú. Finalment, explorem mètodes per avaluar la qualitat de les representacions de dades de text generades pels auto-codificadors, alhora que analitzem les propietats de les seves arquitectures. Com a resultat, proposem dues noves mètriques per quantificar la qualitat de les reconstruccions generades pels auto-codificadors: l'índex de preservació d'estructura (SCI, per les seves sigles en anglès) i l'índex d'acumulació de similitud (SAI, per les seves sigles en anglès). També presentem el concepte de dimensió crítica de coll d'ampolla (CBD, per les seves sigles en anglès), per sota de la qual la informació estructural es deteriora. Mostrem que, de manera interessant, la CBD està relacionada amb la perplexitat de la llengua.
Gupta, PA. (2017). Cross-view Embeddings for Information Retrieval [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/78457
TESIS
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Conradie, Simone. "Verb movement parameters in Afrikaans : investigating the Full Transfer Full Access hypothesis." Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=85899.

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Анотація:
This thesis sets out to test the Full Transfer Full Access hypothesis (FTFA), which claims (i) that second language (L2) learners start out with the parameter settings instantiated in their first language (L1) grammars ('full transfer') and (ii) that they can subsequently reset parameters to the target L2 settings where these differ from the L1 settings, provided the required (triggering) positive evidence is available in the L2 input ('full access').
Three studies on the L2 acquisition of two verb movement parameters, the V2 parameter and the Split-IP parameter (SIP), are reported. The first study investigates 'full access', testing whether English-speaking learners of Afrikaans, who started acquiring the L2 in early childhood and are thus child L2 learners, can reset the two parameters. The second study investigates 'full transfer' and 'full access' by testing whether English-speaking and German-speaking learners start out with different settings of the two parameters and whether the English-speaking learners can reset the parameters. All participants in this study are adult L2 learners, which facilitates a comparison of child L2 acquisition (first study) with adult L2 acquisition. The third study investigates whether Afrikaans-speaking learners of French can acquire knowledge of the ungrammaticality of certain construction types that are allowed in their L1 but not in the L2 (although the languages share the same parameter setting), despite the fact that there seems to be no positive evidence to this effect in the L2 input. It is argued that, taken together, the studies provide evidence in support of the FTFA.
The original contribution of this thesis lies in (i) investigating both verb movement parameters (instead of only one), (ii) providing a thorough discussion of the relevant syntactic properties of Afrikaans, (iii) investigating the L2 acquisition of Afrikaans, and (iv) addressing the question of how learners go about acquiring a parameter setting ([+SIP]) in cases where both the L1 and the L2 share the parameter setting but the L1 exhibits a superset of the properties exhibited by the L2.
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Christodoulopoulos, Christos. "Iterated learning framework for unsupervised part-of-speech induction." Thesis, University of Edinburgh, 2013. http://hdl.handle.net/1842/8880.

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Computational approaches to linguistic analysis have been used for more than half a century. The main tools come from the field of Natural Language Processing (NLP) and are based on rule-based or corpora-based (supervised) methods. Despite the undeniable success of supervised learning methods in NLP, they have two main drawbacks: on the practical side, it is expensive to produce the manual annotation (or the rules) required and it is not easy to find annotators for less common languages. A theoretical disadvantage is that the computational analysis produced is tied to a specific theory or annotation scheme. Unsupervised methods offer the possibility to expand our analyses into more resourcepoor languages, and to move beyond the conventional linguistic theories. They are a way of observing patterns and regularities emerging directly from the data and can provide new linguistic insights. In this thesis I explore unsupervised methods for inducing parts of speech across languages. I discuss the challenges in evaluation of unsupervised learning and at the same time, by looking at the historical evolution of part-of-speech systems, I make the case that the compartmentalised, traditional pipeline approach of NLP is not ideal for the task. I present a generative Bayesian system that makes it easy to incorporate multiple diverse features, spanning different levels of linguistic structure, like morphology, lexical distribution, syntactic dependencies and word alignment information that allow for the examination of cross-linguistic patterns. I test the system using features provided by unsupervised systems in a pipeline mode (where the output of one system is the input to another) and show that the performance of the baseline (distributional) model increases significantly, reaching and in some cases surpassing the performance of state-of-the-art part-of-speech induction systems. I then turn to the unsupervised systems that provided these sources of information (morphology, dependencies, word alignment) and examine the way that part-of-speech information influences their inference. Having established a bi-directional relationship between each system and my part-of-speech inducer, I describe an iterated learning method, where each component system is trained using the output of the other system in each iteration. The iterated learning method improves the performance of both component systems in each task. Finally, using this iterated learning framework, and by using parts of speech as the central component, I produce chains of linguistic structure induction that combine all the component systems to offer a more holistic view of NLP. To show the potential of this multi-level system, I demonstrate its use ‘in the wild’. I describe the creation of a vastly multilingual parallel corpus based on 100 translations of the Bible in a diverse set of languages. Using the multi-level induction system, I induce cross-lingual clusters, and provide some qualitative results of my approach. I show that it is possible to discover similarities between languages that correspond to ‘hidden’ morphological, syntactic or semantic elements.
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10

Gürel, Ayşe. "Linguistic characteristics of second language acquisition and first language attrition : Turkish overt versus null pronouns." Thesis, McGill University, 2002. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=38201.

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Анотація:
This thesis investigates the binding of overt and null subject pronouns in second language (L2) acquisition and first language (L1) attrition of Turkish. The aim is to provide a comparative investigation of language transfer effects in the ultimate state of the L2 and L1 grammar. More specifically, it examines transfer effects from English L1 and English L2 into the grammars of Turkish L2 and Turkish L1, respectively.
In this thesis, I propose that the Subset Condition (Berwick, 1985; Manzini & Wexler, 1987) can account for transfer phenomena observed in both L2 acquisition and L1 attrition. I argue that the subset relation that holds between the L1 and the L2 can be a predictor for the extent and duration of cross-linguistic transfer in L2 acquisition and L1 attrition. In other words, whether or not a particular property will resist L2 acquisition and undergo L1 attrition can be determined by looking at the subset relationship between the L1 and the L2 with respect to that property.
The prediction is that in configurations where the 'influencing language' (L1 in L2 acquisition and L2 in L1 attrition) is the superset of the 'affected language' (L2 in L2 acquisition and L1 in L1 attrition), L1 transfer effect will persist in L2 acquisition and we will see more signs of L2 transfer into the L1 grammar, resulting in more attrition effects.
Pronominal binding is chosen to investigate such cross-linguistic transfer effects. English and Turkish differ with respect to governing domains and types of pronominals present in two languages. Turkish, being a pro-drop language, allows null subject pronouns in main and embedded clauses. It also has a special type of anaphoric pronominal, kendisi, for which English has no corresponding form.
Two experiments were conducted to test L2 acquisition and L1 attrition of binding properties of Turkish overt and null subject pronouns under the influence of English. Participants included native English-speakers living in Turkey (end-state L2 Turkish speakers) and native Turkish-speakers living in North America (end-state L2 English speakers). Overall, results obtained from the two studies reveal cross-linguistic transfer effects in the manner predicted. In particular, properties of English overt pronouns (e.g., him/her) are transferred onto the overt Turkish pronoun o in L2 acquisition and in attrition, whereas properties of the Turkish null pronoun and the anaphoric pronominal kendisi are unaffected by English.
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Книги з теми "Cross-language learning"

1

Odlin, Terence. Language transfer: Cross-linguistic influence in language learning. Cambridge: Cambridge University Press, 1989.

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2

Ringbom, Håkan. Cross-linguistic similarity in foreign language learning. Clevedon [England]: Multilingual Matters, 2007.

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3

Janusz, Arabski, ed. Cross-linguistic influences in the second language lexicon. Buffalo: Multilingual Matters, 2006.

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4

L, Oxford Rebecca, ed. Language learning strategies around the world: Cross-cultural perspectives. Honolulu: Second Language Teaching & Curriculum Center, University of Hawai'i at Mānoa, 1996.

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5

Leong, Che Kan, and R. Malatesha Joshi, eds. Cross-Language Studies of Learning to Read and Spell. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-017-1197-5.

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6

Karpinski, Eva C. The language we share: A Canadian cross-cultural reader for learning English. Toronto: Harcourt Brace Canada, 1995.

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7

Kan, Leong Che, Joshi R. Malatesha, and NATO Advanced Study Institute on Cognitive and Linguistic Bases of Reading, Writing, and Spelling (1994 : Alvor, Portugal), eds. Cross-language studies of learning to read and spell: Phonologic and orthographic processing. Dordrecht: Kluwer Academic, 1997.

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8

1951-, Pienemann Manfred, ed. Cross-linguistic aspects of processability theory. Amsterdam: J.Benjamins Pub. Co., 2005.

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9

Pennington, Martha C. English on the world stage: A cross-language view of code correspondencies and their effect on language contact and language learning. Hong Kong: City Polytechnic of Hong Kong, 1994.

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10

Georgetown University Round Table on Languages and Linguistics (1986). Developments in linguistics and semiotics, language teaching and learning, communication across cultures. Edited by Battestini Simon P. X. Washington, D.C: Georgetown University Press, 1987.

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Частини книг з теми "Cross-language learning"

1

Shultz, Thomas R., Scott E. Fahlman, Susan Craw, Periklis Andritsos, Panayiotis Tsaparas, Ricardo Silva, Chris Drummond, et al. "Cross-Language Document Categorization." In Encyclopedia of Machine Learning, 242. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-30164-8_186.

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2

Shultz, Thomas R., Scott E. Fahlman, Susan Craw, Periklis Andritsos, Panayiotis Tsaparas, Ricardo Silva, Chris Drummond, et al. "Cross-Language Information Retrieval." In Encyclopedia of Machine Learning, 242. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-30164-8_187.

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3

Shultz, Thomas R., Scott E. Fahlman, Susan Craw, Periklis Andritsos, Panayiotis Tsaparas, Ricardo Silva, Chris Drummond, et al. "Cross-Language Question Answering." In Encyclopedia of Machine Learning, 242. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-30164-8_188.

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4

Schmidt, Anna Marie. "Cross-language consonant identification." In Language Experience in Second Language Speech Learning, 185–200. Amsterdam: John Benjamins Publishing Company, 2007. http://dx.doi.org/10.1075/lllt.17.18sch.

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5

Strange, Winifred. "Cross-language phonetic similarity of vowels." In Language Experience in Second Language Speech Learning, 35–55. Amsterdam: John Benjamins Publishing Company, 2007. http://dx.doi.org/10.1075/lllt.17.08str.

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6

Liu, Yue, Lin Dai, Weitao Zhou, and Heyan Huang. "Active Learning for Cross Language Text Categorization." In Advances in Knowledge Discovery and Data Mining, 195–206. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30217-6_17.

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7

Huang, Hui. "10. Developing Interactional Competence in Dyadic Conversations: Cross-language Evidence." In Rethinking Second Language Learning, edited by Marisa Cordella and Hui Huang, 187–225. Bristol, Blue Ridge Summit: Multilingual Matters, 2016. http://dx.doi.org/10.21832/9781783095414-015.

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8

Narla, Swapna, Vijaya Kumar Koppula, and G. SuryaNarayana. "Information Retrieval Based on Telugu Cross-Language Transliteration." In Machine Learning and Information Processing, 343–50. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4859-2_34.

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9

Dittmar, Norbert, and Heiner Terborg. "Modality and second language learning." In Cross Currents in Second Language Acquisition and Linguistic Theory, 347. Amsterdam: John Benjamins Publishing Company, 1991. http://dx.doi.org/10.1075/lald.2.19dit.

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10

Arabski, Janusz. "Chapter 2. Language Transfer in Language Learning and Language Contact." In Cross-linguistic Influences in the Second Language Lexicon, edited by Janusz Arabski, 12–21. Bristol, Blue Ridge Summit: Multilingual Matters, 2006. http://dx.doi.org/10.21832/9781853598579-005.

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Тези доповідей конференцій з теми "Cross-language learning"

1

Hoang, Phuong Nguyen. "Cross-Disciplinary Language Teaching." In 18th International Conference of the Asia Association of Computer-Assisted Language Learning (AsiaCALL–2-2021). Paris, France: Atlantis Press, 2022. http://dx.doi.org/10.2991/assehr.k.211224.008.

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2

Peeters, Ralph, and Christian Bizer. "Cross-Language Learning for Product Matching." In WWW '22: The ACM Web Conference 2022. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3487553.3524234.

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3

Joty, Shafiq, Preslav Nakov, Lluís Màrquez, and Israa Jaradat. "Cross-language Learning with Adversarial Neural Networks." In Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017). Stroudsburg, PA, USA: Association for Computational Linguistics, 2017. http://dx.doi.org/10.18653/v1/k17-1024.

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4

Zhang, Yue-Jie, and Tao Zhang. "Research on English-Chinese Cross-Language Information Retrieval." In 2007 International Conference on Machine Learning and Cybernetics. IEEE, 2007. http://dx.doi.org/10.1109/icmlc.2007.4370744.

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5

Tao Zhang and Yue-Jie Zhang. "Research on Chinese-English Cross-Language Information Retrieval." In 2008 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE, 2008. http://dx.doi.org/10.1109/icmlc.2008.4620845.

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6

Kochmar, Ekaterina, and Ekaterina Shutova. "Cross-Lingual Lexico-Semantic Transfer in Language Learning." In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Stroudsburg, PA, USA: Association for Computational Linguistics, 2016. http://dx.doi.org/10.18653/v1/p16-1092.

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7

Zhao, Yue, Yan M. Xu, Mei J. Sun, Xiao N. Xu, Hui Wang, Guo S. Yang, and Qiang Ji. "Cross-language transfer speech recognition using deep learning." In 2014 11th IEEE International Conference on Control & Automation (ICCA). IEEE, 2014. http://dx.doi.org/10.1109/icca.2014.6871132.

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8

Thi Do, Quynh Ngoc, and Judith Gaspers. "Cross-lingual Transfer Learning for Spoken Language Understanding." In ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2019. http://dx.doi.org/10.1109/icassp.2019.8682346.

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9

Perera, Ian, and James Allen. "Quantity, Contrast, and Convention in Cross-Situated Language Comprehension." In Proceedings of the Nineteenth Conference on Computational Natural Language Learning. Stroudsburg, PA, USA: Association for Computational Linguistics, 2015. http://dx.doi.org/10.18653/v1/k15-1023.

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10

Chen, Rung-Ching, Chung-Yi Huang, and Yu-Len Huang. "Clustering Synonymous English and Chinese Keywords for Cross-Language Queries." In 2007 International Conference on Machine Learning and Cybernetics. IEEE, 2007. http://dx.doi.org/10.1109/icmlc.2007.4370454.

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Звіти організацій з теми "Cross-language learning"

1

Shalatska, Hanna M., Olena Yu Zotova-Sadylo, and Ivan O. Muzyka. Moodle course in teaching English language for specific purposes for masters in mechanical engineering. [б. в.], July 2020. http://dx.doi.org/10.31812/123456789/3881.

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Анотація:
The central thesis of this paper is that e-learning courses can have a significant impact on English language for specific purposes (ESP) proficiency of mining mechanical engineering students. The purpose of this study is to assess the effectiveness of ESP Moodle-based course “English for Mining Mechanical Engineers” and to reveal the results of its experimental approbation. In order to identify the lectures’ and learners’ needs we have applied the survey research. The survey confirmed the greatest demand for Moodle courses that include all the elements of a coherent training manual to provide self-development of engineering students. The interview results contributed to design of author’s ESP course syllabus. The importance and originality of this study are that to approbate the course materials’ effectiveness two approaches have been adopted simultaneously. The first is blended learning method based on e-learning platform applied in the experimental group and the second one is classic in-class instructor-led studying used in a control group. Students’ progress in ESP proficiency has been assessed using the cross assessment method. The experiment has validated the initial hypothesis that the special online courses focused on honing foreign language skills and integrated in the domain of specific professional knowledge have a beneficial effect on students’ communicative competencies in general. There were identified the advantages of self-tuition based on Moodle platform. The Moodle course lets the teachers save considerable in-class time to focus more on communicative assignments. The findings of this study have a number of practical implications in ESP online courses development.
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2

Lavadenz, Magaly, Jongyeon Ee, Elvira Armas, and Grecya López. Leaders’ Perspectives on the Preparation of Bilingual/Dual Language Teachers. Center for Equity for English Learners, 2021. http://dx.doi.org/10.15365/ceel.policy.10.

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Анотація:
This research and policy brief uplifts findings from a 2020 survey of 223 California school district leaders. Findings regarding the preparation of beginning bilingual/dual language educators indicate that leaders rated teachers’ linguistic competencies in two languages as the most important ability, followed by teachers’ understanding of bilingualism and biliteracy development and linguistic pedagogical knowledge. Respondents rated beginning bilingual teachers’ preparation to meet the needs of their districts/schools as “moderately well” (M=3.1 out of 5). The brief concludes by identifying policy recommendations for state and local levels as well as for institutions of higher education policies and practice in this statewide “new ecology of biliteracy”: (1) data collection and reporting on bilingual teacher demographics and authorization; (2) increased quality of fieldwork and clinical experiences for future bilingual teachers; (3) increased funding for bilingual teacher preparation programs to diversity pipelines into bilingual education preparation programs, recruitment, support, and program completion; and (4) differentiated professional development experiences for beginning bilingual teachers including mentoring, learning communities, and cross-departmental teams.
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3

Hernández, Ana, Magaly Lavadenz, and JESSEA YOUNG. Mapping Writing Development in Young Bilingual Learners. CEEL, 2012. http://dx.doi.org/10.15365/ceel.article.2012.2.

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A growing interest in Two-Way Bilingual Immersion (TWBI) programs has led to increased attention to bilingualism, biliteracy, and biculturalism. This article describes the writing development in Spanish and English for 49 kindergarten students in a 50/50 Two-Way Bilingual Immersion program. Over the course of an academic year, the authors collected writing samples to analyze evidence of cross-linguistic resource sharing using a grounded theoretical approach to compare and contrast writing samples to determine patterns of cross-linguistic resource sharing in English and Spanish. The authors identified four patterns: phonological, syntactic, lexical, and metalinguistic awareness. Findings indicated that emergent writers applied similar strategies as older bilingual students, including lexical level code-switching, applied phonological rules of L1 to their respective L2s, and used experiential and content knowledge to write in their second language. These findings have instructional implications for both English Learners and native English speakers as well as for learning from students for program improvement.
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