Due to the various functions and diverse attitudes to lexical repetition in discourse, it is an aspect of cohesion which creates difficulty for raters when assessing L2 academic written discourse. Current computer-aided lexical cohesion analysis frameworks built for large-scale assessment fail to take into account where repetitions occur in text and what role their patterns play in organizing discourse. This study intends to fill this gap, by applying a sequential mixed method design, drawing on Hoey’s (1991) theory-based analytical tool devised for the study of the text-organizing role of lexical repetition, and its refined version, Károly’s (2002) lexical repetition model, which was found to be capable of predicting teachers’ perceptions of argumentative essay quality with regard to its content and structure. It first aims to test the applicability of the previous models to assessing the role of lexical repetition in the organization of other academic genres, then propose a more complex, computer aided analytical instrument that may be used to directly assess discourse cohesion through the study of lexical repetition.
In order to test the applicability of Károly’s model on other academic genres, two small corpora of thirty-five academic summaries and eight compare/contrast essays were collected from English major BA students at Eötvös Loránd University. The lexical repetition patterns within the corpora were analyzed manually in the case of the summaries, and partially with a concordance program in the case of the compare/contrast essays. The findings revealed that in both genres lexical repetition patterns differed in high and low-rated texts.
Given that in its present form the model cannot be used on large-scale corpora, in the third stage of the research, a computer-aided model was designed for large-scale lexical repetition analysis. First, by employing the theoretical, empirical and methodological results gained from the corpora, several new analytical steps were proposed and built into a modular format. Next, in order to better align the new computer-aided analysis to its manual version, parallel processes were identified between the new analytical model and an existing sociocognitive framework. The newly proposed model may help teachers to assess discourse cohesion, or can be used as a self-study aid by visualizing the lexical net created by semantic relations among sentences in text.
Table of Contents
1. Introduction.
1.1 Background to the study.
1.2 Aims of the present research.
1.3 An overview of the dissertation.
2 Theoretical Framework.
2.0 Overview.
2.1 Coherence and cohesion.
2.1.1 Definitions of coherence and cohesion
2.1.2 Types of cohesion
2.2 Lexical cohesion and lexical repetition.
2.2.1 Categories of lexical cohesion
2.2.2 Lexical chains or a lexical net?
2.3 Hoey’s (1991) Repetition Model 16
2.3.1 The theoretical background of the model
2.3.2 Hoey’s (1991) taxonomy of lexical repetition
2.3.3 Links and bonds creating a lexical net
2.3.4 The steps of the analysis
2.3.5 Applications of Hoey’s (1991) model
2.3.6 Inconsistencies within Hoey’s (1991) model
2.3.7 The link triangle and the mediator missing
2.3.8 The questions of anaphora resolution
2.3.9 Prescriptiveness or descriptiveness of the model
2.4 Károly’s (2002) Repetition Model 29
2.4.1 Károly’s (2002) taxonomy of lexical repetition
2.4.2 Károly’s (2002) method of analysis
2.4.3 Károly’s empirical investigation
2.4.4 A corpus-based investigation using Károly’s (2002) taxonomy. 332.5 .. Summary
3 Methodological background: the academic writing context.
3.0 Overview..
3.1 The nature of academic discourse.
3.1.1 General features of English academic discourse
3.1.2 The types of writing tasks required at university
3.1.3 Disciplinary differences in academic discourse
3.1.4 Implications for language pedagogy
3.1.5 Independent vs. integrative writing tasks
3.2 Task variables influencing academic discourse quality.
3.2.1 The classification of variables in academic writing
3.2.2 Contextual variables of integrated academic discourse quality
3.2.3 Cognitive variables of integrated academic discourse quality
3.2.4 Summary writing as a complex task
3.2.5 Writing a compare/contrast essay
3.3 Assessing academic discourse.
3.3.1 ‘Traditional’ and recent academic essay assessment practices
3.3.2 Validity in L2 academic writing assessment
3.3.3 Generalizability of judgement on academic discourse quality
3.3.4 Reliability of perceived discourse quality
3.3.5 Text quality requirements by course teachers
3.3.6 Explicit instruction on coherence, cohesion and lexical repetition in higher education
3.3.7 Automated assessment of text quality
3.3.8 Controversial views on the automated assessment of essay quality
3.4 Summary.
4 Aims and Research Questions.
5 Research design and procedures of analysis.
5.1 A sequential mixed design.
5.2 Stage 1: Analysis of academic summaries.
5.2.1 The summary writing task
5.2.2 Corpus size and representativity
5.2.3 Context validity evaluation of the summary writing task
5.2.4 Features of the input text
5.2.5 Quality assessment of the corpus
5.2.6 Methods of data analysis in Stage
5.3 Stage 2: Analysis of compare/contrast essays.
5.3.1 The compare/contrast essay writing task
5.3.2 Quality assessment of the corpus
5.3.3 Methods of data analysis in Stage
6 Results of the lexical repetition analysis of academic summaries.
6.1 General features of the summaries.
6.2 Results related to repetition type.
6.3 Results related to the combination of links and bonds.
6.4 Methodological outcomes.
6.5 Summary.
7 Results of the lexical repetition analysis of compare/contrast essays.
7.1 General features of the compare/contrast essays.
7.2 Results related to repetition type.
7.3 Results related to the combination of links and bonds.
7.4 Features not detected.
7.5 Methodological outcomes with automation in mind.
7.6 Summary.
8 The design of a new LRA model for large-scale analysis.
8.1 The newly proposed LRA model: the three modules of the analysis.
8.2 Phase 1: Preparation of the corpus. 125
8.2.1 Plagiarism check
8.2.2 L2 special corpora treatment / Error treatment
8.2.3 POS tagging
8.2.4 POS tagging for lower level L2 texts
8.2.5 Using WordNet with the existing taxonomy
8.2.6 Using WordNet with errors in a learner corpus
8.3 Phase 2: Finding links.
8.3.1 Theoretical considerations: altering the taxonomy
8.3.2 Introducing the concept of ‘key term’ into the coding process
8.3.3 Lexical unit identification in the case of multiword units
8.4 Special use of the model for academic summary writing.
8.5 Visual representation of links and bonds.
8.6 Connecting the new LRA model to a cognitive framework.
8.7 The scope and limitations of the new LRA model
9 Conclusions.
9.1 Summary of main results.
9.2 Pedagogical implications.
9.3 Limitations.
9.4 Terminology issues
9.5 Suggestions for further research.
References.
APPENDICES.
- Citar trabajo
- Dr Maria Adorjan (Autor), 2016, Lexical Repetition in Academic Discourse, Múnich, GRIN Verlag, https://www.grin.com/document/459913
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