代写LNG209 Coursework Part 2 2025/2026代写C/C++编程

Department of Applied Linguistics

LNG209 Coursework Part 2

2025/2026

This coursework assignment for LNG209 is worth 70% of the module mark.  The second coursework assignment is designed to assess the following learning outcomes:

A. develop an ability to apply analytical approaches and techniques to analyse and interpret linguistic and discourse features of authentic English texts;

B. reflect critically on the written and spoken language used in a variety of contexts;

D. compare and contrast language choices in different varieties of texts by successfully using software for the identification of textual features

E. demonstrate through project work their understanding of principles of corpus construction and corpus analyses

In this task you are requested to produce a report of approximately 2,000 words to:

l introduce the situational contexts of two varieties of English;

l present a quantitative analysis of the varieties using two self-built corpora.

DIY Corpus Design

You will need to build two small corpora from two varieties of English and use corpus tools to analyze these.  The two corpora do not need to be exactly equal in size (tokens or number of texts) but they should have a combined total of at least 40,000 tokens and be comprised of at least 10 texts.  The table below provides rough guidelines on how many texts of some suggested varieties might be needed to reach this target.

	Approximate number of texts needed
Text type	20,000 tokens	40,000 tokens
customer reviews	100 to 200	200 to 400
extended product descriptions	10 to 15	20 to 30
short product reviews	100 to 150	200 to 300
chairman’s statements	40 to 80	80 to 160
financial reviews	1 to 5	2 to 10
chapters from novels	5 to 10	10 to 20
abstracts from academic articles	100 to 200	200 to 400
complete academic articles	3 to 4	6 to 8
newspaper articles	20-40	40-80
magazine articles	10-40	20-80

While all sources may not be equal in terms of the difficulty of data collection; the evaluation of the suitability of the sources of the data and the way texts have been prepared will be made on the basis of the overall value of the project and how well the sourcing and selection of texts matches your stated aims.

Corpus Software

The majority of the corpus analysis should be completed using The Prime Machine (Jeaco 2017), available to all staff and students at XJTLU from http://www.theprimemachine.net/ and free from the App Store (macOS) and the Microsoft Store.  You will need to use the App directly, but you may also use the AI Agent (tPMAgent) on the XIPU AI Platform, provided you declare use of AI as described on page 3.

You may also choose to include additional data using the following tools:

1.   AntConc (Anthony 2024), which is freely available from http://www.laurenceanthony.net/software.html.

2.   LancsBox X (Brezina, McEnery, & Wattam 2015; Brezina & Platt 2025), available from https://lancsbox.lancs.ac.uk/.

3.   WordSmith Tools V5(Scott, 2010), which is available for free if you follow instructions from the Learning Mall Core page.

Time in the workshop sessions will be dedicated to supporting you as you work through designing the project, finding source texts, managing the data and making use of corpus tools.  During these sessions practice texts will be available, but you will also be able to apply the methods directly to your own corpora.

Suggested Structure for the report

The word count should exclude all tables and any examples from the corpus which you use in your essay.  You should also attach the table of the situational context analysis and the  text which you produce yourself as appendices (also not included in the word count).

Suggested sections for the report are:

•    Introduction

Provide brief background information about the text varieties

Provide a brief statement of the purpose of doing linguistics analysis of this variety of English

•    Method

Explain how the files were selected and downloaded; explain the corpus tools used and methods employed.

•    Results and Analysis

Present tables of data from your corpus analysis and summarize key features.

•    Discussion

Use some of the key findings to explain how differences in the situational context seem to influence the language choices.

•   Conclusion

Only a very brief conclusion should be necessary

•   Appendixes

The complete situational context analysis table following page 40 of Biber and Conrad (2009).

Prompts and raw output from all use of AI powered analysis (using the template).

You do not need to write an abstract for this assignment

This is an individual piece of work and plagiarism or collusion will not be tolerated.    If an AI Agent and/or Generative AI is used for the generation of corpus data summaries, comparisons between Large Language Models and corpus data, generation of translations or paraphrases of concordance lines or any other kind of analysis, a full description of the prompt used to generate the analysis must be provided and the raw output from the AI Agent should be presented (see template in the appendix).  The report must be written by yourself, so when introducing, comparing or contrasting raw AI generated analysis, you should use quotation marks to clearly indicate any phrases or expressions from raw AI output.

You will also need to upload your raw data.

The report and supporting data must be submitted no later than 8pm on the following date: Monday 15th December 2025.  Late submission will be penalized according to university policy.

References

Anthony, L. (2024). AntConc. In (Version 4.3.1) Waseda University.

https://www.laurenceanthony.net/software/antconc/

Biber, D. & Conrad, S. 2009. Register, Genre, and Style.  Cambridge: Cambridge University Press.

Brezina, V., McEnery, T., & Wattam, S. (2015). Collocations in context: A new perspective on collocation networks. International Journal of Corpus Linguistics(2), 139-173.

Brezina, V., Platt, W. (2025). #LancsBox  X  5.5.1 [software package].  Available at: https://lancsbox.lancs.ac.uk/.

Jeaco, S. (2017). Concordancing Lexical Primings. In M. Pace-Sigge & K. J. Patterson (Eds.), Lexical Priming: Applications and Advances (pp. 273-296). Amsterdam: John Benjamins.

Scott, M. 2010. WordSmith Tools (Version 5.0). Oxford: Oxford University Press.

https://lexically.net/wordsmith/version5/index.html