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Course profile

Text Analysis and Corpus Linguistics (SLAT7829)

Study period
Sem 1 2025
Location
St Lucia
Attendance mode
In Person

Course overview

Study period
Semester 1, 2025 (24/02/2025 - 21/06/2025)
Study level
Postgraduate Coursework
Location
St Lucia
Attendance mode
In Person
Units
2
Administrative campus
St Lucia
Coordinating unit
Languages & Cultures School

The analysis of texts is undoubtedly a core aspect of many academic fields and important applications in education as well as the private sector. This course introduces students to the study of texts using computers, commonly called text analysis or corpus linguistics. Over the past decades, corpus linguistics has emerged both as a field in its own right but also as an important methodology across the language sciences including studies on language acquisition and learning, language variation and change as well as language use. As such, text analysis and corpus linguistics have helped to place linguistic theorizing on a sounder empirical footing by allowing researchers to explore massive amounts of textual data, be it learner essays, transcriptions of dinner table conversation, or historical documents. This course covers the fundamental concepts, origins, and methods of corpus linguistics and text analysis with a focus on a hands-on approach and using specific examples of how corpora can be used in applied linguistic research.

Course requirements

Assumed background

This course assumes no previous knowledge of corpus linguistics or text analysis, but some knowledge of quantitative research methods in applied linguistics and a willingness to engage with software applications will be useful.

Course staff

Course coordinator

Lecturer

Timetable

The timetable for this course is available on the UQ Public Timetable.

Additional timetable information

Public holidays:

Alternative arrangements for affected students will be announced through the Blackboard site.

Class allocation:

In order to optimise the student experience, it may be necessary to reallocate students to a different class from their first choice. Before this happens, every effort will be made to enable students to voluntarily change into an alternative class that is suitable. Please note: Teaching staff do not have access to the timetabling system to help with class allocation. Therefore, should you need

help with your timetable and/or allocation of classes, please ensure you email hass.mytimetable@uq.edu.au from your UQ student email account with the following details:

  • Full name,
  • Student ID, and
  • the Course Code

Additional information and support can be found here.

Weekly learning activities consist of a one-hour face-to-face or online lecture and a two-hour tutorial.ᅠ Weekly lecture content consists of pre-recorded lectures that are uploaded to Blackboard one week before the scheduled week.ᅠ Weekly tutorials are conducted face-to-faceᅠ following your scheduled timetable allocations. Throughout the semester you will be expected to contribute substantially and consistently to our tutorial activities and discussions of research approaches and methodologies drawing on your own ideas and experiences. Please make sure that you keep up with the course content by reviewing the online materilas made available on Blackboard (e.g., lecture podcasts, lecture and tutorial slides, readings) and completing the assessments.

Tutorial allocations usually take a few weeks to finalise so please be patient.

Aims and outcomes

The analysis of texts is undoubtedly a core aspect of many academic fields and important applications in education as well as the private sector. This course introduces students to the study of texts using computers, commonly called text analysis or corpus linguistics. Over the past decades, corpus linguistics has emerged both as a field in its own right but also as an important methodology across the language sciences including studies on language acquisition and learning, language variation and change as well as language use. As such, text analysis and corpus linguistics have helped to place linguistic theorizing on a sounder empirical footing by allowing researchers to explore massive amounts of textual data, be it learner essays, transcriptions of dinner table conversation, or historical documents. This course covers the fundamental concepts, origins, and methods of corpus linguistics and text analysis with a focus on a hands-on approach and using specific examples of how corpora can be used in applied linguistic research.

Learning outcomes

After successfully completing this course you should be able to:

LO1.

Describe and explain how language is used in different contexts

LO2.

Understanding of concepts and methods in text analysis and corpus linguistics

LO3.

Effectively apply the concepts and theories studied in the course to the analysis of language data (texts)

LO4.

Practically apply text analysis and corpus linguistics methods

LO5.

Critically evaluate analyses of language data

LO6.

Identify differences between learners and native speakers of English

Assessment

Assessment summary

Category Assessment task Weight Due date
Quiz Weekly Study Online Task
  • Online
20%

10/03/2025 1:00 pm

17/03/2025 1:00 pm

24/03/2025 1:00 pm

31/03/2025 1:00 pm

7/04/2025 1:00 pm

14/04/2025 1:00 pm

28/04/2025 1:00 pm

6/05/2025 1:00 pm

12/05/2025 1:00 pm

19/05/2025 1:00 pm

Presentation Research Project Presentation
  • Identity Verified
  • Online
30%

9/05/2025 4:00 pm

Week 10

Paper/ Report/ Annotation Research Project Write-Up
  • Online
50%

13/06/2025 4:00 pm

Exam Week 1

Assessment details

Weekly Study Online Task

  • Online
Mode
Written
Category
Quiz
Weight
20%
Due date

10/03/2025 1:00 pm

17/03/2025 1:00 pm

24/03/2025 1:00 pm

31/03/2025 1:00 pm

7/04/2025 1:00 pm

14/04/2025 1:00 pm

28/04/2025 1:00 pm

6/05/2025 1:00 pm

12/05/2025 1:00 pm

19/05/2025 1:00 pm

Learning outcomes
L01, L02

Task description

Every week from Week 3 to Week 12, there will be an Online Study Task consisting of 10 questions that you need to answer and submit in preparation for that week.

These tasks are available 7 days before the due date and must be submitted by Monday at 1 pm (or Tuesday if Monday is a public holiday).

The questions will cover the lecture content and required readings for that week. For example, the Week 3 Online Study Task will be about the Week 3 lecture and readings, and you need to submit it by 1 pm on Monday of Week 3.

Each Online Study Task is worth 2% of your final grade. You have 60 minutes and one attempt to complete each task.

After all ten Online Study Tasks are completed, your total study task score will be calculated. Please note that tasks not completed and awarded 0 points are included in the average calculation. The percentage of the maximum achievable points will determine your final grade for this assessment.

The link to each week's Online Study Task will be available on Blackboard.

Marking Information

The weekly Online Study Tasks must be accessed, completed, and submitted via Blackboard.

Answers will be assessed automatically, and results will be made available to students within the week of submission. Answers to questions will be rated as correct or incorrect. For each correct answer, students will receive 1 point. Each Online Study Task consists of 10 questions, and there are 10 tasks in total, meaning students can earn up to 100 points if they answer all questions correctly. The marks for the Online Study Tasks follow the marking scheme of the School of Language and Cultures.

Statement on Gen AI & MT

This assessment task evaluates students' abilities, skills and knowledge without the aid of generative Artificial Intelligence (AI) or Machine Translation (MT). Students are advised that the use of AI or MT technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.

Submission guidelines

The online study tasks have to be submitted weekly from Week 3 at Monday 1 pm via UQ.learn/Blackboard.

Deferral or extension

You cannot defer or apply for an extension for this assessment.

No extensions are allowed for this series of ten tasks as students are given a seven-day period to complete them. Individual results and correct answers are automatically upon completion of the task. Timely engagement with these tasks supports sequential nature of learning in this course.

Research Project Presentation

  • Identity Verified
  • Online
Mode
Activity/ Performance, Oral
Category
Presentation
Weight
30%
Due date

9/05/2025 4:00 pm

Week 10

Learning outcomes
L01, L02, L03, L05

Task description

The Research Project Presentation carries a weight of 30% in your final grade. This assessment entails the submission of a video presentation outlining your research proposal, centred around corpus analysis. The primary objective is to guide students in structuring and preparing their research projects while providing an opportunity for valuable feedback.

Submission Format

Submit a recorded video presentation lasting 10 minutes (the presentation must not be longer than 11 minutes).

Purpose

This task is designed to showcase your ability to articulate and present a novel and original research project in the language sciences, utilizing corpus data.

Video Presentation Structure

Introduction

  • Clearly state your research topic.
  • Establish the relevance of your research.
  • Provide a succinct outline of your presentation's organization.

Literature Review

  • Present a structured literature review.
  • Ensure seamless transitions between themes, points, and sections.
  • Demonstrate mastery of relevant theories and concepts, backed by a detailed understanding of previous findings.

Research Question

  • Provide a clear and specific statement of the Research Question.
  • Motivate the Research Question based on insights from the literature review.

Data and Methodology

  • Describe the data and method intended for answering the research question.
  • Offer detailed information about the research context, data sources, and data analysis.

Conclusion and Evaluation

  • Present a critical evaluation of the proposed study.
  • Discuss potential contributions to the relevant field.
  • Acknowledge and address any identified limitations.

References (APA7 format)

  • Bibliographic details should be presented in APA 7 citation style. Any sources or citations mentioned in your presentation need to be added in a reference list at the end of your presentation (which should also be formatted according to APA7).

Important Guidelines

  • The entire presentation should be between 9 and a maximum of 11 minutes (recordings must not be longer than 11 minutes).
  • Articulate your points clearly, maintaining a balance between conciseness and detail.
  • Leverage visual aids if necessary to enhance the presentation's clarity.
  • Aim to engage your audience, fostering an understanding of the significance of your proposed research.
  • Prepare slides for your presentation and record yourself and the slides (we suggest you use Zoom and share your screen).

This task serves as a vital step in the preparation of your research project, offering a platform for you to convey the essence of your work effectively. Utilize the provided rubric (accessible via UQ.learn/Blackboard) as a reference for your presentation. Please refer to the rubic (available via UQ.learn/Blackboard) for details.

Statement on Gen AI & MT

Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT in completing this assessment task. Students must clearly reference any use of AI or MT in each instance. A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.

Submission guidelines

Online via Turnitin.

Deferral or extension

You may be able to apply for an extension.

The maximum extension allowed is 14 days. Extensions are given in multiples of 24 hours.

The maximum extension length ensures that assessors can provide timely feedback, supporting the progressive, sequential, and cumulative nature of learning experience that underpins this course.

Late submission

A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.

Research Project Write-Up

  • Online
Mode
Written
Category
Paper/ Report/ Annotation
Weight
50%
Due date

13/06/2025 4:00 pm

Exam Week 1

Learning outcomes
L01, L02, L03, L04, L05, L06

Task description

SLAT7829 Corpus and Text Analysis: Research Project Write-Up

Overview

The Research Project Write-Up contributes 50% to your final grade. This assessment requires you to submit a written report detailing your research project focusing on a corpus-based analysis of a topic in Applied Linguistics. This research project write-up allows you to apply the knowledge and skills acquired throughout the course. The objective is to demonstrate your ability to design, execute, and document an original and insightful corpus-based research study. This assessment serves as a significant milestone in developing your research skills.

Assessment Criteria

Your Research Project Write-Up will be evaluated out of 50 points. Please refer to the detailed marking criteria in the rubric (available via UQ.learn/Blackboard) for a breakdown of assessment components.

Submission Guidelines

  • Submit a written report with a maximum of 2000 words (excluding references and Appendix).
  • Ensure your submission adheres to APA 7 formatting for citations and references.
  • The report must be written in academic English and it must be structured logically and coherently, following the format outlined below.

Purpose

This task is designed to assess your ability to conduct independent and original research focusing on a corpus-based analysis of a topic in Applied Linguistics. You will demonstrate:

✔ The ability to define a research problem and formulate research questions.

✔ A clear understanding of relevant theories and literature.

✔ Competence in data selection, analysis, and interpretation using corpus methodologies.

✔ The capacity to present findings in a clear, well-structured, and engaging manner.

Report Structure

1. Introduction (What are you doing, and why is it relevant?)

  • Clearly define your research topic.
  • Describe and exemplify the phenomenon under investigation that is relevant in Applied Linguistics.
  • Justify the relevance and significance of your research.
  • Provide a brief outline of the report structure.

2. Literature Review (Motivation and Background)

  • Present a structured review of relevant research.
  • Ensure logical and smooth transitions between themes.
  • Demonstrate mastery of theories and key concepts.
  • Conclude with well-defined Research Questions and/or Hypotheses, motivated by the literature.

3. Data and Methodology (What data and methods will you use, and why are they appropriate?)

  • Describe your data (e.g., corpus details, size, mode, compilers). Use tables where appropriate to present your data.
  • Justify the methodology, explaining why it is appropriate for addressing your research questions.
  • Explain the methodology, including any software tools you intend to use.
  • Detail the data processing steps, analytical techniques, and tools/software used.

4. Results

  • Present the findings of your study using textual descriptions, tables, and visualizations (charts/graphs) where appropriate.
  • Ensure clarity and coherence in presenting analytical outcomes.

5. Discussion and Conclusion

  • Reflect on how your study addresses the research questions.
  • Compare and contrast your findings with existing research.
  • Critically evaluate the strengths, limitations, and potential contributions of your study.

6. References (APA 7 Format)

  • Provide a complete and correctly formatted reference list following APA 7 guidelines.

7. Appendix (what does not belong in the main text)

  • Add additional and relevant resources such as code you have written, regular expression you have used, or extended tables detailing statistical results.

Important Guidelines

  • Conciseness & Clarity: Each section should be succinct yet comprehensive and written in academic English as used in high-quality journal papers.
  • Originality & Depth: Ensure your project presents an original and meaningful contribution to corpus research.
  • Structure & Formatting: Follow the provided structure for clarity and coherence.

Statement on Gen AI & MT

This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance. A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct. To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI and MT tools.

Submission guidelines

Submit a written report of a research project of no longer than 2000 words (excluding references) via Turnitin.

Deferral or extension

You may be able to apply for an extension.

The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.

Late submission

A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.

Course grading

Full criteria for each grade is available in the Assessment Procedure.

Grade Cut off Percent Description
1 (Low Fail) 0 - 24

Absence of evidence of achievement of course learning outcomes.

Course grade description: No submitted work or submitted work incomplete.

2 (Fail) 25 - 44

Minimal evidence of achievement of course learning outcomes.

Course grade description: Student shows little understanding of the research process, manifested in consistent lack of application of research techniques to assessment items, inability to formulate a topic and central question, very limited degree of analysis and synthesis of findings from data, and lack of clear and logical presentation of findings in a manner consistent with accepted academic standards. Nil or very poor bibliographic and citation technique.

3 (Marginal Fail) 45 - 49

Demonstrated evidence of developing achievement of course learning outcomes

Course grade description: Falls short of satisfying all basic requirements of a pass. Student shows a poor understanding of the research process, manifested in lack of application of research techniques to most assessment items, poor ability to formulate a topic and central question, a limited degree of analysis and synthesis of findings from data, and substantial lapses in clear and logical presentation of findings in a manner consistent with accepted academic standards. Poor bibliographic and citation technique.

4 (Pass) 50 - 64

Demonstrated evidence of functional achievement of course learning outcomes.

Course grade description: Student shows an adequate understanding of the research process, manifested in application of research techniques to most assessment items, adequate ability to formulate to a topic and central research question, and adequate degree of analysis and synthesis of findings from data, and at times clear and logical presentation of findings (albeit with many incoherencies) in a manner broadly consistent with accepted academic standards. Work contains a notable number of factual errors and grammatical infelicities. Many errors in bibliography and in citations. Sources not consistently or correctly acknowledged.

5 (Credit) 65 - 74

Demonstrated evidence of proficient achievement of course learning outcomes.

Course grade description: Students shows a good understanding of the research process, manifested in application of research techniques to most assessment items, good ability to formulate a topic and central research question, a good degree of analysis and synthesis of findings from data, and usually clear and logical presentation of findings (albeit with some major incoherencies) in a manner that is mostly consistent with accepted academic standards. Work contains some factual errors and grammatical infelicities. Some obvious errors in the bibliography. Sources not consistently correctly acknowledged.

6 (Distinction) 75 - 84

Demonstrated evidence of advanced achievement of course learning outcomes.

Course grade description: Students shows a good understanding of the research process, manifested in application of research techniques to most assessment items, good ability to formulate a topic and central research question, a very good degree of analysis and synthesis of findings from data, and almost always clear and logical presentation of findings (some minor incoherencies) in a manner consistent with accepted academic standards. Work may contain rare factual errors and minor grammatical infelicities. Comprehensive bibliography, although with some minor errors. Sources correctly acknowledged.

7 (High Distinction) 85 - 100

Demonstrated evidence of exceptional achievement of course learning outcomes.

Course grade description: Student shows an excellent understanding of the research process, manifested in consistent application of research techniques to all assessment items, excellent ability to formulate a topic and central research question, coherent analysis and synthesis of findings from data, and consistently clear and logical presentation of findings in a manner consistent with accepted academic standards. Work has no factual errors, few grammatical infelicities and a comprehensive bibliography, with sources consistently and correctly acknowledged.

Additional course grading information

Marking criteria and/or marking rubrics are available in the ‘Assessment’ folder in Blackboard for this course.

Supplementary assessment

Supplementary assessment is available for this course.

Learning resources

You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.

Library resources

Find the required and recommended resources for this course on the UQ Library website.

Additional learning resources information

Language Technology and Data Analysis Laboratory (LADAL) available via https://ladal.edu.au/

Learning activities

The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.

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Learning period Activity type Topic
Multiple weeks

From Week 1 To Week 13
(24 Feb - 01 Jun)

Tutorial

Tutorial: Corpus Linguistics and Text Analysis

How to design and build a corpus?

Learning outcomes: L01, L02, L03, L04, L05, L06

Not Timetabled

Recorded Lecture: Corpus Linguistics and Text Analysis

Weekly lecture content consists of pre-recorded hour-long lectures that are uploaded to Blackboard one week before the scheduled week.ᅠ Students are expected to watch the recorded lecture content before taking the Online Study Tasks for the respective week and before attending the tutorials.

Learning outcomes: L02, L05, L06

Policies and procedures

University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:

Learn more about UQ policies on my.UQ and the Policy and Procedure Library.