Дисертації з теми "Language transfer (Language learning) Germany"
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Samperio, Sanchez Nahum. "General learning strategies : identification, transfer to language learning and effect on language achievement." Thesis, University of Southampton, 2016. https://eprints.soton.ac.uk/412008/.
Повний текст джерелаZhang, Yuan Ph D. Massachusetts Institute of Technology. "Transfer learning for low-resource natural language analysis." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/108847.
Повний текст джерелаThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 131-142).
Expressive machine learning models such as deep neural networks are highly effective when they can be trained with large amounts of in-domain labeled training data. While such annotations may not be readily available for the target task, it is often possible to find labeled data for another related task. The goal of this thesis is to develop novel transfer learning techniques that can effectively leverage annotations in source tasks to improve performance of the target low-resource task. In particular, we focus on two transfer learning scenarios: (1) transfer across languages and (2) transfer across tasks or domains in the same language. In multilingual transfer, we tackle challenges from two perspectives. First, we show that linguistic prior knowledge can be utilized to guide syntactic parsing with little human intervention, by using a hierarchical low-rank tensor method. In both unsupervised and semi-supervised transfer scenarios, this method consistently outperforms state-of-the-art multilingual transfer parsers and the traditional tensor model across more than ten languages. Second, we study lexical-level multilingual transfer in low-resource settings. We demonstrate that only a few (e.g., ten) word translation pairs suffice for an accurate transfer for part-of-speech (POS) tagging. Averaged across six languages, our approach achieves a 37.5% improvement over the monolingual top-performing method when using a comparable amount of supervision. In the second monolingual transfer scenario, we propose an aspect-augmented adversarial network that allows aspect transfer over the same domain. We use this method to transfer across different aspects in the same pathology reports, where traditional domain adaptation approaches commonly fail. Experimental results demonstrate that our approach outperforms different baselines and model variants, yielding a 24% gain on this pathology dataset.
by Yuan Zhang.
Ph. D.
Jin, Di Ph D. Massachusetts Institute of Technology. "Transfer learning and robustness for natural language processing." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/129004.
Повний текст джерелаCataloged from student-submitted PDF of thesis.
Includes bibliographical references (pages 189-217).
Teaching machines to understand human language is one of the most elusive and long-standing challenges in Natural Language Processing (NLP). Driven by the fast development of deep learning, state-of-the-art NLP models have already achieved human-level performance in various large benchmark datasets, such as SQuAD, SNLI, and RACE. However, when these strong models are deployed to real-world applications, they often show poor generalization capability in two situations: 1. There is only a limited amount of data available for model training; 2. Deployed models may degrade significantly in performance on noisy test data or natural/artificial adversaries. In short, performance degradation on low-resource tasks/datasets and unseen data with distribution shifts imposes great challenges to the reliability of NLP models and prevent them from being massively applied in the wild. This dissertation aims to address these two issues.
Towards the first one, we resort to transfer learning to leverage knowledge acquired from related data in order to improve performance on a target low-resource task/dataset. Specifically, we propose different transfer learning methods for three natural language understanding tasks: multi-choice question answering, dialogue state tracking, and sequence labeling, and one natural language generation task: machine translation. These methods are based on four basic transfer learning modalities: multi-task learning, sequential transfer learning, domain adaptation, and cross-lingual transfer. We show experimental results to validate that transferring knowledge from related domains, tasks, and languages can improve the target task/dataset significantly. For the second issue, we propose methods to evaluate the robustness of NLP models on text classification and entailment tasks.
On one hand, we reveal that although these models can achieve a high accuracy of over 90%, they still easily crash over paraphrases of original samples by changing only around 10% words to their synonyms. On the other hand, by creating a new challenge set using four adversarial strategies, we find even the best models for the aspect-based sentiment analysis task cannot reliably identify the target aspect and recognize its sentiment accordingly. On the contrary, they are easily confused by distractor aspects. Overall, these findings raise great concerns of robustness of NLP models, which should be enhanced to ensure their long-run stable service.
by Di Jin.
Ph. D.
Ph.D. Massachusetts Institute of Technology, Department of Mechanical Engineering
Utgof, Darja. "The Perception of Lexical Similarities Between L2 English and L3 Swedish." Thesis, Linköping University, Department of Culture and Communication, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-15874.
Повний текст джерелаThe present study investigates lexical similarity perceptions by students of Swedish as a foreign language (L3) with a good yet non-native proficiency in English (L2). The general theoretical framework is provided by studies in transfer of learning and its specific instance, transfer in language acquisition.
It is accepted as true that all previous linguistic knowledge is facilitative in developing proficiency in a new language. However, a frequently reported phenomenon is that students see similarities between two systems in a different way than linguists and theoreticians of education do. As a consequence, the full facilitative potential of transfer remains unused.
The present research seeks to shed light on the similarity perceptions with the focus on the comprehension of a written text. In order to elucidate students’ views, a form involving similarity judgements and multiple choice questions for formally similar items has been designed, drawing on real language use as provided by corpora. 123 forms have been distributed in 6 groups of international students, 4 of them studying Swedish at Level I and 2 studying at Level II.
The test items in the form vary in the degree of formal, semantic and functional similarity from very close cognates, to similar words belonging to different word classes, to items exhibiting category membership and/or being in subordinate/superordinate relation to each other, to deceptive cognates. The author proposes expected similarity ratings and compares them to the results obtained. The objective measure of formal similarity is provided by a string matching algorithm, Levenshtein distance.
The similarity judgements point at the fact that intermediate similarity values can be considered problematic. Similarity ratings between somewhat similar items are usually lower than could be expected. Besides, difference in grammatical meaning lowers similarity values significantly even if lexical meaning nearly coincides. Thus, the obtained results indicate that in order to utilize similarities to facilitate language learning, more attention should be paid to underlying similarities.
Casula, Camilla. "Transfer Learning for Multilingual Offensive Language Detection with BERT." Thesis, Uppsala universitet, Institutionen för lingvistik och filologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-412450.
Повний текст джерелаPanzeri-Alvarez, Christina. "Metacognition and language transfer for an English language development transitional program." CSUSB ScholarWorks, 1998. https://scholarworks.lib.csusb.edu/etd-project/1780.
Повний текст джерелаTse, Siu-ching, and 謝兆政. "Cross linguistic influence in polyglots: encoding of the future by L3 learners of Swedish." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B4842187X.
Повний текст джерелаpublished_or_final_version
Linguistics
Master
Master of Arts
Meftah, Sara. "Neural Transfer Learning for Domain Adaptation in Natural Language Processing." Thesis, université Paris-Saclay, 2021. http://www.theses.fr/2021UPASG021.
Повний текст джерелаRecent approaches based on end-to-end deep neural networks have revolutionised Natural Language Processing (NLP), achieving remarkable results in several tasks and languages. Nevertheless, these approaches are limited with their "gluttony" in terms of annotated data, since they rely on a supervised training paradigm, i.e. training from scratch on large amounts of annotated data. Therefore, there is a wide gap between NLP technologies capabilities for high-resource languages compared to the long tail of low-resourced languages. Moreover, NLP researchers have focused much of their effort on training NLP models on the news domain, due to the availability of training data. However, many research works have highlighted that models trained on news fail to work efficiently on out-of-domain data, due to their lack of robustness against domain shifts. This thesis presents a study of transfer learning approaches, through which we propose different methods to take benefit from the pre-learned knowledge on the high-resourced domain to enhance the performance of neural NLP models in low-resourced settings. Precisely, we apply our approaches to transfer from the news domain to the social media domain. Indeed, despite the importance of its valuable content for a variety of applications (e.g. public security, health monitoring, or trends highlight), this domain is still poor in terms of annotated data. We present different contributions. First, we propose two methods to transfer the knowledge encoded in the neural representations of a source model pretrained on large labelled datasets from the source domain to the target model, further adapted by a fine-tuning on few annotated examples from the target domain. The first transfers contextualised supervisedly pretrained representations, while the second method transfers pretrained weights, used to initialise the target model's parameters. Second, we perform a series of analysis to spot the limits of the above-mentioned proposed methods. We find that even if the proposed transfer learning approach enhances the performance on social media domain, a hidden negative transfer may mitigate the final gain brought by transfer learning. In addition, an interpretive analysis of the pretrained model, show that pretrained neurons may be biased by what they have learned from the source domain, thus struggle with learning uncommon target-specific patterns. Third, stemming from our analysis, we propose a new adaptation scheme which augments the target model with normalised, weighted and randomly initialised neurons that beget a better adaptation while maintaining the valuable source knowledge. Finally, we propose a model, that in addition to the pre-learned knowledge from the high-resource source-domain, takes advantage of various supervised NLP tasks
Mozafari, Marzieh. "Hate speech and offensive language detection using transfer learning approaches." Electronic Thesis or Diss., Institut polytechnique de Paris, 2021. http://www.theses.fr/2021IPPAS007.
Повний текст джерелаThe great promise of social media platforms (e.g., Twitter and Facebook) is to provide a safe place for users to communicate their opinions and share information. However, concerns are growing that they enable abusive behaviors, e.g., threatening or harassing other users, cyberbullying, hate speech, racial and sexual discrimination, as well. In this thesis, we focus on hate speech as one of the most concerning phenomenon in online social media.Given the high progression of online hate speech and its severe negative effects, institutions, social media platforms, and researchers have been trying to react as quickly as possible. The recent advancements in Natural Language Processing (NLP) and Machine Learning (ML) algorithms can be adapted to develop automatic methods for hate speech detection in this area.The aim of this thesis is to investigate the problem of hate speech and offensive language detection in social media, where we define hate speech as any communication criticizing a person or a group based on some characteristics, e.g., gender, sexual orientation, nationality, religion, race. We propose different approaches in which we adapt advanced Transfer Learning (TL) models and NLP techniques to detect hate speech and offensive content automatically, in a monolingual and multilingual fashion.In the first contribution, we only focus on English language. Firstly, we analyze user-generated textual content to gain a brief insight into the type of content by introducing a new framework being able to categorize contents in terms of topical similarity based on different features. Furthermore, using the Perspective API from Google, we measure and analyze the toxicity of the content. Secondly, we propose a TL approach for identification of hate speech by employing a combination of the unsupervised pre-trained model BERT (Bidirectional Encoder Representations from Transformers) and new supervised fine-tuning strategies. Finally, we investigate the effect of unintended bias in our pre-trained BERT based model and propose a new generalization mechanism in training data by reweighting samples and then changing the fine-tuning strategies in terms of the loss function to mitigate the racial bias propagated through the model. To evaluate the proposed models, we use two publicly available datasets from Twitter.In the second contribution, we consider a multilingual setting where we focus on low-resource languages in which there is no or few labeled data available. First, we present the first corpus of Persian offensive language consisting of 6k micro blog posts from Twitter to deal with offensive language detection in Persian as a low-resource language in this domain. After annotating the corpus, we perform extensive experiments to investigate the performance of transformer-based monolingual and multilingual pre-trained language models (e.g., ParsBERT, mBERT, XLM-R) in the downstream task. Furthermore, we propose an ensemble model to boost the performance of our model. Then, we expand our study into a cross-lingual few-shot learning problem, where we have a few labeled data in target language, and adapt a meta-learning based approach to address identification of hate speech and offensive language in low-resource languages
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.
Повний текст джерелаYuan, Boping. "Directionality of difficulty in second language acquisition of Chinese and English." Thesis, University of Edinburgh, 1993. http://hdl.handle.net/1842/17576.
Повний текст джерелаConradie, 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.
Повний текст джерелаThree 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.
Kwan, Chung-hin. "An investigation of English errors of Hong Kong secondary 1 and secondary 5 students and their relationship with mother tongue Cantonese transfer." Hong Kong : University of Hong Kong, 1997. http://sunzi.lib.hku.hk/hkuto/record.jsp?B18939326.
Повний текст джерелаPopa, Simona. "Language transfer in second language acquisition. Some effects of L1 instruction (Romanian) on L2/L3 learning (Catalan/Spanish)." Doctoral thesis, Universitat de Lleida, 2016. http://hdl.handle.net/10803/380548.
Повний текст джерелаEn contextos de migració, la diversitat de llengües en contacte esdevé processos d’adquisició de segones llengües (L2) i de transferència lingüística; a més de revifar el debat sobre la importància del manteniment de la llengua materna (L1). En el següent treball s’exploren els processos d’adquisició de l’L2 (català i castellà), del manteniment de l’L1 (romanès) i de la transferència lingüística de l’L1, de 130 estudiants immigrants d’origen romanès; així com l’efecte d’assistir a classes d’L1 i el temps d’estada, en les tres llengües estudiades. Per a aquest propòsit, s’han aplicat tres proves paral•leles de competència lingüística en set instituts d’Educació Secundària Obligatòria de Catalunya. A nivell general, els resultats indiquen que la transferència lingüística de l’L1 a les L2s sorgeix i que un major temps d’estada afavoreix l’aprenentatge del català i del castellà però, al mateix temps, va en detriment del nivell del coneixement adquirit en la seva L1. Així mateix, l’assistència a classes de romanès sembla influir en el manteniment de la seva llengua materna i en l’aprenentatge de segones llengües.
En contextos de migración, la diversidad de lenguas en contacto desencadena procesos de adquisición de segundas lenguas (L2) y de transferencia lingüística; además de reavivar el debate sobre la importancia del mantenimiento de la lengua materna (L1). En el siguiente trabajo se exploran los procesos de adquisición de L2 (catalán y castellano), del mantenimiento de la L1 (rumano) y de la transferencia lingüística de la L1, de 130 estudiantes inmigrantes de origen rumano, así como el efecto de asistir a clases de L1 y el tiempo de estancia, en las tres lenguas estudiadas. Para ello, se han aplicado tres pruebas paralelas de competencia lingüística en siete institutos de Educación Secundaria Obligatoria de Cataluña. A nivel general, los resultados indican que se da la influencia de la L1 en las L2 y que un mayor tiempo de estancia favorece el aprendizaje del catalán y del castellano, pero, a su vez, va en detrimento del nivel de conocimiento adquirido en su L1. Asimismo, la asistencia a clases de rumano parece influir en el mantenimiento de su lengua materna y en el aprendizaje de segundas lenguas.
Kung, Shui Man Jessica. "Language maintenance or language shift ? : a study of South Asian ethnic minorities' Chinese language learning in Hong Kong." HKBU Institutional Repository, 2012. http://repository.hkbu.edu.hk/etd_ra/1353.
Повний текст джерелаMau, 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.
Повний текст джерелаHalvardsson, Gustaf, and Johanna Peterson. "Interpretation of Swedish Sign Language using Convolutional Neural Networks and Transfer Learning." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-277859.
Повний текст джерелаAutomatisk tolkning av tecken i ett teckenspråk involverar bildigenkänning. Ett ändamålsenligt tillvägagångsätt för denna uppgift är att använda djupinlärning, och mer specifikt, Convolutional Neural Networks. Denna metod behöver generellt stora mängder data för att prestera väl. Därför kan transfer learning vara en rimlig metod för att nå en hög precision trots liten mängd data. Avhandlingens hypotes är att utvärdera om transfer learning fungerar för att tolka det svenska teckenspråkets handalfabet. Målet med projektet är att implementera en modell som kan tolka tecken, samt att bygga en användarvänlig webapplikation för detta syfte. Modellen lyckas klassificera 85% av testinstanserna korrekt. Då denna precision är jämförbar med de från andra studier, tyder det på att projektets hypotes är korrekt. Det slutgiltiga nätverket baseras på den förtränade modellen InceptionV3 med fem frysta lager, samt optimiseringsalgoritmen mini-batch gradient descent med en batchstorlek på 32 och en stegfaktor på 1,2. Transfer learning användes, men däremot inte till den nivå så att nätverket blev för specialiserat på den förtränade modellen och dess data. Nätverket har visat sig vara ickepartiskt för det mångfaldiga testningsdatasetet. Förslag på framtida arbeten inkluderar att integrera dynamisk teckendata för att kunna tolka ord och meningar, evaluera metoden på andra teckenspråkshandalfabet, samt att integrera dynamisk tolkning i webapplikationen så flera bokstäver eller ord kan tolkas efter varandra. I det långa loppet kan denna studie gagna döva personer som har tillgång till teknik, och därmed öka chanserna för god hälsa, kvalitetsundervisning, anständigt arbete och minskade ojämlikheter.
Tipa, Thep-Ackrapong Steffensen Margaret S. "Fossilization a case study of practical and theoretical parameters /." Normal, Ill. Illinois State University, 1990. http://wwwlib.umi.com/cr/ilstu/fullcit?p9101128.
Повний текст джерелаTitle from title page screen, viewed November 15, 2005. Dissertation Committee: Margaret Steffensen (chair), Irene Brosnahan, Bruce Hawkins, Maurice Scharton, Sandra Metts. Includes bibliographical references (leaves 211-218) and abstract. Also available in print.
Mostert, Annamarie. "A language programme evaluation : English as language of learning and teaching / A. Mostert." Thesis, North-West University, 2008. http://hdl.handle.net/10394/2032.
Повний текст джерелаLevesque, Guy-Luc. "Lexico-Semantic Influence in Interlingual Transfer." PDXScholar, 1994. https://pdxscholar.library.pdx.edu/open_access_etds/4771.
Повний текст джерелаLategano, Antonio. "Image-based programming language recognition." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/22208/.
Повний текст джерелаBecker, Thomas. "Contrastive analysis for teaching Koine Greek case syntax to Russian-speaking students." Theological Research Exchange Network (TREN), 2007. http://www.tren.com/search.cfm?p023-0209.
Повний текст джерелаKayama, Yuhko. "Second language acquisition of Japanese relative clauses." Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=100636.
Повний текст джерелаExperimental studies were conducted with high-intermediate and advanced learners of Japanese (15 English speakers and 18 Korean speakers). Tests examined the learners' knowledge of the two grammatical properties in Japanese---namely, the lack of wh-movement and the presence of pro. Korean is different from English but similar to Japanese with respect to the parameters in question. Following FTFA, it is hypothesized that English-speaking learners initially transfer their L1 values, and that eventually they are able to switch parameters to the L2 values by accessing UG. The results of several tasks (including interpretation tasks and judgment tasks) confirm this hypothesis; while Korean speakers generally performed well irrespective of proficiency levels, English-speaking intermediate learners transferred their L1 values, failing to accept grammatical Japanese sentences that are not possible in English. English-speaking advanced learners, on the other hand, performed better than intermediate learners, and exhibited evidence that they had acquired the two properties of Japanese, supporting FTFA.
Luk, Yuen-chau. "The role of phonological awareness in second language reading." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B36890613.
Повний текст джерелаGürel, 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.
Повний текст джерелаIn 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.
Berdugo, Oviedo Gloria. "Sentence processing strategies by bilinguals." Thesis, McGill University, 1990. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=60031.
Повний текст джерелаChan, Carol Suk Oi. "A cross-sectional study of syntactic errors in English composition by ESL students in Hong Kong : aspects of negative transfer." HKBU Institutional Repository, 2002. http://repository.hkbu.edu.hk/etd_ra/501.
Повний текст джерелаInagaki, Shunji. "Transfer and learnability in second language argument structure : motion verbs with locationaldirectional PPs in L2 English and Japanese." Thesis, McGill University, 2002. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=38492.
Повний текст джерелаKeung, Yuen-ching. "Transfer of cognitive skills in learning to read Chinese (L1) and English (L2) among HK elementary students." Click to view E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B37090720.
Повний текст джерелаAnanth, Priya. "Acquisition of tense and aspect in Toki 'when' clauses in Japanese as a second/foreign language." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1187208767.
Повний текст джерелаGraber, Elizabeth. "Evaluating Speech-Language Pathologists’ Transfer of Continuing Education Learning Outcomes to Their Practice Settings." Cleveland State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=csu1593547874361376.
Повний текст джерелаLam, Ka-ki Fiona. "The verb use in Cantonese monolingual and Cantonese-English bilingual children." Click to view the E-thesis via HKU Scholors Hub, 2005. http://lookup.lib.hku.hk/lookup/bib/B38279277.
Повний текст джерела"A dissertation submitted in partial fulfilment of the requirements for the Bachelor of Science (Speech and Hearing Sciences), The University of Hong Kong, June 30, 2005." Also available in print.
Wijayanto, Agus. "Interlanguage pragmatics of refusal strategies by Javanese EFL learners." Thesis, University of Aberdeen, 2011. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=183672.
Повний текст джерелаBrown, Cynthia A. 1967. "Acquisition of segmental structure : consequences for speech perception and second language acquisition." Thesis, McGill University, 1997. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=34704.
Повний текст джерелаThree related areas of research are explored and integrated in this work: first, a theoretical study explores the feature-geometric representation of sonorant and non-sonorant laterals, based on their behavior in a variety of phonological processes cross-linguistically, and suggests that [lateral] is not a phonological feature, but rather that laterality is a phonetic property that derives from a specific feature-geometric representation; second, an experimental study investigates the acquisition of phonemic contrasts by English children and demonstrates that segmental representations are acquired in a uniform order that is consistent with properties of Feature Geometry; finally, a series of experimental studies examines the perception and acquisition of the English /l-r/, /b-v/, /p-f/, /f-v/ and /s-theta/ contrasts by native speakers of Japanese, Mandarin Chinese and Korean.
The findings from each of these studies are synthesized to obtain a comprehensive picture of how segmental representations are acquired and how this L1 knowledge impinges on the acquisition of L2 phonemes: it is argued that the monotonic acquisition of feature-geometric structure by young children restricts their sensitivity to particular non-native contrasts, and the continued operation of this existing feature geometry in adult speech perception constrains which non-native contrasts adult learners will be sensitive to in the L2 input and, therefore, capable of acquiring; the circumstances in which the native grammar facilitates perception of non-native contrasts and in which acquisition is possible are also discussed.
Alasfour, Aisha Saud. "Grammatical Errors by Arabic ESL Students| An Investigation of L1 Transfer through Error Analysis." Thesis, Portland State University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10826886.
Повний текст джерелаThis study investigated the effect of first language (L1) transfer on Arabic ESL learners’ acquisition of the relative clauses, the passive voice and the definite article. I used Contrastive Analysis (CA) and Error Analysis (EA) to analyze 50 papers written by Arabic ESL students at the ACTFL Advanced Mid proficiency level. The analysis was paired with interviews with five advanced students to help determine whether L1 transfer was, in fact, influencing students’ errors predicted by CA.
Students in this study made L1 errors along with other errors. Although no statistical difference was found between the frequency of transfer and other (non-transfer) errors, L1 transfer errors were still common for many learners in this data. The frequency of the relative clause L1 transfer errors was slightly higher than other errors. However, passive voice L1 errors were as frequent as other errors whereas definite article L1 errors were slightly less frequent than other errors. The analysis of the interviews suggested that L1 still played a crucial role in influencing learners errors.
The analysis also suggested that the frequency of transfer errors in the papers used in this study might have been influenced by CA-informed instruction students received and students’ language level. Specifically, learners reported that both factors helped them reduce the frequency of L1 transfer errors in their writing.
The teaching implications of this study include familiarizing language instructors with possible sources of errors for Arabic ESL learners. Language instructors should try to identify sources of errors by conducting their own analyses or consulting existing literature on CA paired with EA. Finally, I recommend adopting a CA-informed instruction to help students reduce and overcome errors that are influenced by their L1.
Child, Michael W. "Cross-Linguistic Influence in L3 Portuguese Acquisition: Language Learning Perceptions and the Knowledge and Transfer of Mood Distinctions by Three Groups of English-Spanish Bilinguals." Diss., The University of Arizona, 2014. http://hdl.handle.net/10150/333340.
Повний текст джерелаBäck, Jesper. "Domain similarity metrics for predicting transfer learning performance." Thesis, Linköpings universitet, Interaktiva och kognitiva system, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-153747.
Повний текст джерелаMogofe, 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.
Повний текст джерелаPoor 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.
Valenzuela, Elena. "L2 ultimate attainment and the syntax-discourse interface : the acquisition of topic constructions in non-native Spanish and English." Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=102224.
Повний текст джерелаThree current theories of acquisition are examined, namely, the Full Transfer/Full Access model (FT/FA), Failed Functional Features Hypothesis/Representational Deficit Hypothesis (FFFH/RDH), and Optionality theory. The theories are considered with respect to their predictions about L2 ultimate attainment and the syntax-discourse interface.
Participants were 15 end state speakers of L2 Spanish/L1 English and 15 end state speakers of L2 English/L1 Spanish were tested. Three tasks were administered for each study (Sentence Completion Task, oral Sentence Selection Task, and oral Acceptability Task) targeting topic constructions and associated interpretive properties in the respective target languages. Results for the L2 Spanish study indicate that while the syntactic properties of CLLD were acquired, the interpretive properties of specificity were fossilized (i.e. clitic was overgeneralized). Results for the L2 English study also showed that the syntactic properties were acquired but the specificity distinction of the L1 was transferred into the L2. Results demonstrate that problems with specificity occur in both directions as predicted by the theory of Optionality. In both cases, the optionality found at the interpretive level was L1-based. Namely, non-target L1 forms co-existed with the L2 forms.
Visaggi, Salvatore. "Multimodal Side-Tuning for Code Snippets Programming Language Recognition." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/22993/.
Повний текст джерелаMcEleney, Sarah Nicole. "La influencia del conocimiento de otras lenguas en la identificación de palabras en español L2 un estudio de los modelos bia y bia+ /." Oxford, Ohio : Miami University, 2009. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=miami1248105154.
Повний текст джерелаKwan, Chung-hin, and 關仲顯. "An investigation of English errors of Hong Kong secondary 1 and secondary 5 students and their relationship with mother tongueCantonese transfer." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1997. http://hub.hku.hk/bib/B3195943X.
Повний текст джерелаMatsumura, Tomomi. "The Use of Evidentials in Hearsay Contexts in Japanese and English." PDXScholar, 2017. https://pdxscholar.library.pdx.edu/open_access_etds/4153.
Повний текст джерелаKanwal, Jasmeen Kaur. "Word length and the principle of least effort : language as an evolving, efficient code for information transfer." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/33051.
Повний текст джерелаRandolph, Gerda Ann Packard. "Building written language: A program for second language literacy in English." CSUSB ScholarWorks, 2000. https://scholarworks.lib.csusb.edu/etd-project/1866.
Повний текст джерела姜源貞 and Yuen-ching Keung. "Transfer of cognitive skills in learning to read Chinese (L1) and English (L2) among HK elementary students." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B37090720.
Повний текст джерелаAndersson, Kristin. "Explicit and implicit comparison of English and Swedish in English course books for year 7 and year 11 in Sweden." Thesis, Karlstads universitet, Institutionen för språk, litteratur och interkultur, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-47873.
Повний текст джерелаDen här uppsatsen jämför hur lingvistisk överföring behandlas engelska kursböcker för årskurs 7 och årskurs 11 i svenska skolor. Studien har fokuserat på att undersöka i vilken mån författarna uttryckligen eller underförstått refererat till överföring och transfer genom att identifiera var kursböckerna innehåller information om likheter och skillnader mellan svenska och engelska. Resultaten från denna studie visar att sådana jämförelser mellan språken fanns i alla böcker, men att uttrycklig jämförelse var det vanligast sättet för författarna att visa på likheter och skillnader. Av de fyra olika lingvistiska nivåer som användes i denna studie (uttal, grammatik, ordförråd, pragmatik), förekom jämförelse av grammatik mest. Författarna till böckerna för årskurs 7 använde sig mer av jämförelser mellan språken än författarna till böckerna för årskurs 11. En slutsats som man kan dra av denna studie är att det är upp till författarna själva att bestämma i vilken mån de ska jämföra de två språken, eftersom läroplanen för ämnet engelska inte ger någon information om hur överföring ska hanteras i språkinlärning.
Ramponi, Alan. "Knowledge Extraction from Biomedical Literature with Symbolic and Deep Transfer Learning Methods." Doctoral thesis, Università degli studi di Trento, 2021. http://hdl.handle.net/11572/310787.
Повний текст джерелаHan, Young Joo. "Feedback and Transfer in Second Language Writing: A Qualitative Study of ESL Students' Experiences." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1498779154665613.
Повний текст джерелаKruesemann, Heike. "Language learning motivation and the discursive representations of German, the Germans, and Germany in UK school settings and the press." Thesis, University of Reading, 2018. http://centaur.reading.ac.uk/77934/.
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