Use of Verb-Noun Collocations by Advanced Learners of Chinese

The important role of collocations has been widely accepted in the current literature, but to date there are still relatively few studies on language learners’ collocation knowledge and development within different local contexts. The current study intends to contribute to the literature by investigating the oral production of Chinese verb-noun (V-N) collocations by a group of highly proficient learners comprised of both Chinese as a foreign language learners (CFL learners) and Chinese heritage language learners (CHL learners), as compared to Chinese native speakers (CNSs). The study brings together current literature on collocation and heritage language learners both from a Western perspective and from the Chinese linguistic and sociolinguistic perspective. Samples of spoken language data discussing both academic and non-academic topics were collected through one-on-one interviews with 10 CFL learners, 10 CHL learners and 10 CNSs. The data are analyzed both quantitatively and qualitatively to yield the following three findings: (1) There is a significant difference in using Chinese verb-noun (V-N) collocations among CFL learners, CHL learners, and CNSs. In general, CNSs produced significantly more V-N collocations in terms of both number (token) and range (type) than CFL learners and CHL learners, (2) The two different oral topics are also found to affect learners’ production of collocations. All three groups used more monosyllabic V-N collocations in discussing daily topics and more disyllabic V-N collocations in discussing academic topics. Moreover, CFL learners and CFL learners exhibited both similarities and differences in applying collocations under the two oral contexts, (3) There are different categories and characteristics of collocation usage in terms of the acceptability and communicativeness of non-conventional collocations produced by learners. The discussion further analyzes several factors that tend to influence CFL learners’ and CHL learners’ production of collocations. The findings of this study expand our understanding about advanced learners’ knowledge and production of Chinese V-N collocations. Moreover, they also provide invaluable information for educators and practitioners who are involved in FL and HL instruction of Chinese

Addressing the grammar needs of Chinese EAP students: an account of a CALL materials development project

This study investigated the grammar needs of Chinese EAP Foundation students and developed electronic self-access grammar materials for them. The research process consisted of three phases. In the first phase, a corpus linguistics based error analysis was conducted, in which 50 student essays were compiled and scrutinized for formal errors. A tagging system was specially devised and employed in the analysis. The EA results, together with an examination of Foundation tutors’ perceptions of error frequency and gravity led me to prioritise article errors for treatment; in the second phase, remedial materials were drafted based on the EA results and insights drawn from my investigations into four research areas (article pedagogy, SLA theory, grammar teaching approaches and CALL methodologies) and existing grammar materials; in the third phase, the materials were refined and evaluated for their effectiveness as a means of improving the Chinese Foundation students’ use of the article. Findings confirm the claim that L2 learner errors are systematic in nature and lend support to the value of Error Analysis. L1 transfer appears to be one of the main contributing factors in L2 errors. The salient errors identified in the Chinese Foundation corpus show that mismanagement of the article system is the most frequent cause of grammatical errors; Foundation tutors, however, perceive article errors to be neither frequent nor serious. An examination of existing materials reveals that the article is given low priority in ELT textbooks and treatments provided in pedagogical grammar books are inappropriate in terms of presentation, language and exercise types. The devised remedial materials employ both consciousness-raising activities and production exercises, using EAP language and authentic learner errors. Preliminary evaluation results suggest that the EA-informed customised materials have the potential to help learners to perform better in proofreading article errors in academic texts

A multidimensional investigation of a data-driven approach to learning collocations

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

A Study of the Use of Lexical Cohesion in Chinese Postgraduate Writing at a UK University

As a key feature in the creation of coherent texts (Tanskanen, 2006), lexical cohesion is of critical importance for students’ academic performance. Chinese students, whose writing is the subject of this thesis, have been identified as lacking awareness of lexical cohesiveness in English academic writing (Zhang, 2000). In order to inform EAP pedagogy for them, this thesis used a corpus-based approach to conduct in-depth investigations of lexical cohesive devices used in Chinese postgraduates’ writing at a UK university. Based on Halliday and Hasan’s model (1976), an analytical framework for the analysis of lexical cohesion was developed in two corpora, incorporating a new sub-category of lexical cohesive device alongside modifications of existing categories. One corpus consisted of 52 module assignment samples (17,538 words) allocated into four marking-scale groups (failed, pass, merit and distinction), the other corpus comprising 45 dissertation excerpts (19,148 words) divided into five functional-section groups (introduction, literature review, methodology, findings/discussion, and conclusion). Applying this framework, manual analysis of the corpora identified homogeneities of lexical cohesion as context sensitivity, topic-based use of lexical cohesion, dominant use of repetition, and use of modifiers to indicate lexical cohesive relations, suggesting the value of context-based pedagogy and the need to teach complex lexical cohesive devices with exemplars. The results of the ANOVA test and the Kolmogorov-Smirnov test suggested a significant difference in the use of lexical cohesion between the marking-scale groups due to fewer repetition pairs identified in the merit group, and no statistically significant difference in overall the use of lexical cohesion among the functional-section groups although the function of each section influences the use of certain lexical cohesive devices. Several factors are proposed as influencing the use of lexical cohesion: topic variety, writers’ choice and function of texts, indicating the complexity of both applying and teaching lexical cohesion in academic writing

Enhancing the acquisition of discipline-specific vocabulary through student concordancing

This Master’s Project focuses on advanced-level English learners\u27 acquisition of discipline-specific vocabulary as they transition from intensive English programs into English-medium university coursework. During this period, the number of discipline-specific terms students must master quickly and independently can be overwhelming. To address this problem, this M.A. Project argues that vocabulary-acquisition strategies should be foregrounded in intensive English programs, and that instructors should train students to supplement traditional vocabulary learning methods with independent concordancing strategies. Using concordancers, students can research vocabulary items by scanning a corpus (a large collection of texts) to retrieve examples of discipline-specific terms within authentic texts, revealing patterns of usage and collocation, and facilitating deeper knowledge of new lexical items that can result in more accurate production. Although many applied linguists have promoted student concordancing, few teaching resources are available on the topic. Therefore, this project outlines an instructional unit scaffolding the process of independent student concordancing. It provides criteria for teachers to consider when selecting a corpus to suit instructional contexts and aims. It provides an overview of the Corpus of Contemporary American English, a large corpus that is freely accessible online, and it examines the features of its integrated concordancer that can help students learn to utilize corpus data for vocabulary learning. Finally, the project relates the writer’s tentative steps in introducing students to concordance data in his teaching, and it presents his experience using corpus-based tools in his own second-language academic writing

Automatic Construction of Clean Broad-Coverage Translation Lexicons

Word-level translational equivalences can be extracted from parallel texts by surprisingly simple statistical techniques. However, these techniques are easily fooled by {\em indirect associations} --- pairs of unrelated words whose statistical properties resemble those of mutual translations. Indirect associations pollute the resulting translation lexicons, drastically reducing their precision. This paper presents an iterative lexicon cleaning method. On each iteration, most of the remaining incorrect lexicon entries are filtered out, without significant degradation in recall. This lexicon cleaning technique can produce translation lexicons with recall and precision both exceeding 90\%, as well as dictionary-sized translation lexicons that are over 99\% correct.Comment: PostScript file, 10 pages. To appear in Proceedings of AMTA-9

A Corpus-based Language Network Analysis of Near-synonyms in a Specialized Corpus

As the international medium of communication for seafarers throughout the world, the importance of English has long been recognized in the maritime industry. Many studies have been conducted on Maritime English teaching and learning, nevertheless, although there are many near-synonyms existing in the language, few studies have been conducted on near-synonyms used in the maritime industry. The objective of this study is to answer the following three questions. First, what are the differences and similarities between different near-synonyms in English? Second, can collocation network analysis provide a new perspective to explain the distinctions of near-synonyms from a micro-scopic level? Third, is semantic domain network analysis useful to distinguish one near-synonym from the other at the macro-scopic level? In pursuit of these research questions, I first illustrated how the idea of incorporating collocates in corpus linguistics, Maritime English, near-synonyms, semantic domains and language network was studied. Then important concepts such as Maritime English, English for Specific Purposes, corpus linguistics, synonymy, collocation, semantic domains and language network analysis were introduced. Third, I compiled a 2.5 million word specialized Maritime English Corpus and proposed a new method of tagging English multi-word compounds, discussing the comparison of with and without multi-word compounds with regard to tokens, types, STTR and mean word length. Fourth, I examined collocates of five groups of near-synonyms, i.e., ship vs. vessel, maritime vs. marine, ocean vs. sea, safety vs. security, and harbor vs. port, drawing data through WordSmith 6.0, tagging semantic domains in Wmatrix 3.0, and conducting network analyses using NetMiner 4.0. In the final stage, from the results and discussions, I was able to answer the research questions. First, maritime near-synonyms generally show clear preference to specific collocates. Due to the specialty of Maritime English, general definitions are not helpful for the distinction between near-synonyms, therefore a new perspective is needed to view the behaviors of maritime words. Second, as a special visualization method, collocation network analysis can provide learners with a direct vision of the relationships between words. Compared with traditional collocation tables, learners are able to more quickly identify the collocates and find the relationship between several node words. In addition, it is much easier for learners to find the collocates exclusive to a specific word, thereby helping them to understand the meaning specific to that word. Third, if the collocation network shows learners relationships of words, the semantic domain network is able to offer guidance cognitively: when a person has a specific word, how he can process it in his mind and therefore find the more appropriate synonym to collocate with. Main semantic domain network analysis shows us the exclusive domains to a certain near-synonym, and therefore defines the concepts exclusive to that near-synonym: furthermore, main semantic domain network analysis and sub-semantic domain network analysis together are able to tell us how near-synonyms show preference or tendency for one synonym rather than another, even when they have shared semantic domains. The options in identifying relationships of near-synonyms can be presented through the classic metaphor of "the forest and the trees." Generally speaking, we see only the vein of a tree leaf through the traditional way of sentence-level analysis. We see the full leaf through collocation network analysis. We see the tree, even the whole forest, through semantic domain network analysis.Contents Chapter 1. Introduction 1 1.1 Focus of Inquiry 1 1.2 Outline of the Thesis 5 Chapter 2. Literature Review 8 2.1 A Brief Synopsis 8 2.2 Maritime English as an English for Specific Purposes (ESP) 9 2.2.1 What is ESP? 9 2.2.2 Maritime English as ESP 10 2.2.3 ESP and Corpus Linguistics 11 2.3 Synonymy 12 2.3.1 Definition of Synonymy 13 2.3.2 Synonymy as a Matter of Degree 15 2.3.3 Criteria for Synonymy Differentiation 18 2.3.4 Near-synonyms in Corpus Linguistics 19 2.4 Collocation 21 2.4.1 Definition of Collocation 21 2.4.2 Collocation in Corpus Linguistics 22 2.4.2.1 Definition of Collocation in Corpus Linguistics 23 2.4.2.2 Collocation vs. Colligation 24 2.4.3 Lexical Priming of Collocation in Psychology 25 2.5 Language Network Analysis 26 2.5.1 Definition 26 2.5.2 Classification 27 2.5.3 Basic Concepts 31 2.5.4 Previous Studies 33 2.6 Semantic Domain Analysis 39 2.6.1 Concepts of Semantic Domains 39 2.6.2 Previous Studies on Semantic Domain Analysis 39 Chapter 3. Data and Methodology 41 3.1 Maritime English Corpus 41 3.1.1 What is a Corpus? 41 3.1.2 Characteristics of a Corpus 42 3.1.2.1 Corpus-driven vs. Corpus-based research 42 3.1.2.2 Specialized Corpora for Specialized Discourse 43 3.1.3 Maritime English Corpus (MEC) 44 3.1.3.1 Sampling of the MEC 45 3.1.3.2 Size, Balance, and Representativeness 51 3.1.3.3 Multi-word Compounds in the MEC 53 3.1.3.4 Basic Information of the MEC 56 3.2 Methodology for Collocates Extraction 60 3.3 Methodology for Networks Visualization 63 3.4 Methodology for Semantic Tagging 65 3.5 Process of Data Analysis 69 Chapter 4. Collocation Network Analysis of Near-synonyms 70 4.1 Meaning Differences 71 4.1.1 Ship vs. Vessel 71 4.1.2 Maritime vs. Marine 72 4.1.3 Sea vs. Ocean 73 4.1.4 Safety vs. Security 74 4.1.5 Port vs. Harbor 76 4.2 Similarity Degree of Groups of Near-synonyms 76 4.2.1 Similarity Degree Based on Number of Shared Collocates 77 4.2.2 Similarity Degree Based on MI3 Cosine Similarity 78 4.3 Collocation Network Analysis 80 4.3.1 Ship vs. Vessel 80 4.3.2 Maritime vs. Marine 82 4.3.3 Sea vs. Ocean 84 4.3.4 Safety vs. Security 85 4.3.5 Port vs. Harbor 87 4.4 Advantages and Limitations of Collocation Network Analysis 88 Chapter 5. Semantic Domain Network Analysis of Near-synonyms 89 5.1 Comparison between Collocation and Semantic Domain Analysis 89 5.2 Semantic Domain Network Analysis of Exclusiveness 92 5.2.1 Ship vs. Vessel 93 5.2.2 Maritime vs. Marine 96 5.2.3 Sea vs. Ocean 99 5.2.4 Safety vs. Security 102 5.2.5 Port vs. Harbor 105 5.3 Analysis of Shared Semantic Domains 108 5.4 Advantages and Limitations of Semantic Domain Network Analysis 112 Chapter 6. Conclusion 113 6.1 Summary 113 6.2 Limitations and Implications 116 References 118 Appendix: Collocates of Near-synonyms 136Docto