Course overview
- Study period
- Semester 2, 2024 (22/07/2024 - 18/11/2024)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Languages & Cultures School
Social interaction in online spaces and with digital technologies is at the core of today’s daily life. This course aims to explore in detail the key components of digital discourse, primarily focussing on conversations on social media, and provide students with the tools to analyse social interaction in those contexts. The data analysed in the course will come from various naturally-occurring conversations on social media as well as from human-computer interactions. The topics covered in the course will be indicative of the main discourses that are prevalent in digital and online settings.
Course requirements
Assumed background
This is a level 3 course, which means that students should have already completed at least 16 units of level 1 and level 2 courses.ﾠ
While the course does not require you to have any prior knowledge in linguistics or pragmatics, recommended pre-requisites are COMU1002 and COMU2040 or any other courses on linguistics and language use.
Prerequisites
You'll need to complete the following courses before enrolling in this one:
16 units of study
Recommended prerequisites
We recommend completing the following courses before enrolling in this one:
COMU1002, COMU2040 or other relevant courses (please contact the course coordinator)
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.
Aims and outcomes
This course aims to introduce students to the pragmatics of digital interaction andﾠprovide them with the tools to analyse social interaction in those contexts. We willﾠexplore in detail the key components of digital discourse with the primary focus will beﾠon conversations in online settings and social media.ﾠ
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Identify the features of digital interactions
LO2.
Explain how conversations are constructed in digital discourse
LO3.
Effectively apply theoretical concepts to the data analysis
LO4.
Carry out a small-scale project on online discourse
LO5.
Critically examine academic literature on the course content
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Participation/ Student contribution |
Reading discussion engagement
|
10% |
2/08/2024 - 4/10/2024 |
| Paper/ Report/ Annotation |
Critical Analysis
|
45% (15% per analysis) |
20/08/2024 5:00 pm 3/09/2024 5:00 pm 17/09/2024 5:00 pm 8/10/2024 5:00 pm |
| Presentation, Project |
Project Part A: Presentation
|
15% |
14/10/2024 - 25/10/2024 |
| Project |
Project Part B: Written submission
|
30% |
6/11/2024 5:00 pm |
Assessment details
Reading discussion engagement
- Identity Verified
- In-person
- Mode
- Oral, Written
- Category
- Participation/ Student contribution
- Weight
- 10%
- Due date
2/08/2024 - 4/10/2024
- Learning outcomes
- L05
Task description
In the seminars in Weeks 2-10, students will be engaging with the weekly readings in group and individual discussions.
It will be done via a live document and the discussion of the answers provided.
Marking:
There will be 9 opportunities for weekly engagement (1% per week), best 7 out of 9 will count towards the final mark.
Engagement will be assessed through the contribution to the online document and discussion afterwards.
Each engagement will be marked as follows:
1 mark - Student shows the excellent engagement with and understanding of the readings
0.5 marks - Student shows some engagement with and understanding of the readings
0 marks - Student does not engage and, thus, shows no to very limited engagement with and understanding of the readings
Generative AI & MT Statement
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
Deferral or extension
You cannot defer or apply for an extension for this assessment.
This assessment task is designed to assess students’ active participation in class (group) discussions and engagement with weekly readings, which is difficult to recreate outside the classroom environment. Each class includes specific activities that allow teaching team to track students’ participation and engagement to fulfil marking criteria outlined above. These activities are made available to students regardless of their presence in class (via Blackboard course site). Furthermore, there will be 9 opportunities for weekly engagement (1% per week), best 7 out of 9 will count towards the final mark.
Critical Analysis
- Online
- Mode
- Oral, Written
- Category
- Paper/ Report/ Annotation
- Weight
- 45% (15% per analysis)
- Due date
20/08/2024 5:00 pm
3/09/2024 5:00 pm
17/09/2024 5:00 pm
8/10/2024 5:00 pm
- Learning outcomes
- L01, L02, L03
Task description
You will need to analyse various datasets as relevant to the course content.
Your best 3 analyses out of 4 will count towards the final mark.
Length: 500 words (excluding references) for written analyses; 5-7 min. for oral analyses
In the Weeks 2, 5, 7 and 9, you will have access to the interactional data in the Assessment folder on Blackboard that you will need to analyse in terms of what is covered in the weeks that correspond to the analysis:
Critical Analysis 1: Weeks 2, 3 & 4 - written submission
Critical Analysis 2: Weeks 5 & 6 - video submission
Critical Analysis 3: Weeks 7 & 8 - written submission
Critical Analysis 4: Weeks 9 & 10 - video submission
In your analysis, you will need to
- identify linguistic and discourse features in the data relevant to the weeks indicated in the task;
- explain those features and what happens in the data in terms of the relevant course concepts;
- support your analysis with the relevant readings from the course (from the reading list, plus any relevant readings covered in lecture and seminar; 4-6 references). Do not use outside-the-course additional readings.
Generative AI & MT Statement
This assessment task evaluates students' abilities, skills and knowledge without the aid of Artificial Intelligence (Al) or Machine Translation (MT). Students are advised that the use of Al technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
TurnItIn or Blackboard
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.
To provide timely feedback, including each analysis discussion in class, prior to the following Critical Analyses in a sequence, the maximum extension length is 14 days.
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.
Project Part A: Presentation
- In-person
- Mode
- Activity/ Performance
- Category
- Presentation, Project
- Weight
- 15%
- Due date
14/10/2024 - 25/10/2024
- Learning outcomes
- L02, L04, L05
Task description
Project consists of 2 parts:
1) Presentation (Week 12/13) - 15%; and
2) Written submission (Week 15) - 30%.
Timeline:
- Weeks 3-8: data search and relevant concept identification;
- Weeks 3-8: data approval;
- Weeks 9-11: consultations for the concept confirmation;
- Weeks 12/13: Presentations;
- Week 15: Written submission.
Data:
You will need to find a dataset that they would like to analyse. The data needs to be naturally-occurring interactions of digital discourse, including but not limited to such contexts as:
- emails;
- chats (e.g. Messenger, WhatsApp, WeChat, Tinder, Bumble, service bot);
- forums and discussion boards;
- social media (e.g. Facebook, Twitter);
- YouTube (videos and comments);
- Human-computer interaction (e.g. Alexa, Siri, GPS).
! You cannot analyse your own interactions, unless they occurred before taking the course.
Once your dataset has been approved, you will need to:
- explore it in detail numerous times and identify the concept that is most salient in the data;
- choose 2 sample extracts for your analysis (if you are using video/audio data, you will need to transcribe it);
- analyse the selected extracts in light of your chosen concept.
IMPORTANT: Start looking for the data early in the semester!
Presentation (15%)
Due: Week 12/13
Length: 10 minutes
In your presentation, you will need to:
- explain what your concept is (support your claims with peer-reviewed publications, including from the course reading list);
- introduce your data (whom you have recorded);
- show a sample data and present a short sample analysis of 1 of your chosen extracts.
You must submit your presentation pdf file before your presentation starts.
Generative AI & MT Statement
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
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.
Project Part B: Written submission
- Online
- Mode
- Written
- Category
- Project
- Weight
- 30%
- Due date
6/11/2024 5:00 pm
- Learning outcomes
- L02, L04, L05
Task description
Project consists of 2 parts:
1) Presentation (Week 12/13) - 15%;
2) Written submission (Week 15) - 30%.
Timeline:
- Weeks 3-8: data search and relevant concept identification;
- Weeks 3-8: data approval;
- Weeks 9-11: consultations for the concept confirmation;
- Week 12: Presentations;
- Week 15: Written submission.
Data:
You will need to find a dataset that they would like to analyse. The data needs to be naturally-occurring interactions of digital discourse, including but not limited to such contexts as:
- emails;
- chats (e.g. Messenger, WhatsApp, WeChat, Tinder, Bumble, service bot);
- forums and discussion boards;
- social media (e.g. Facebook, Twitter);
- YouTube (videos and comments);
- Human-computer interaction (e.g. Alexa, Siri, GPS).
! You cannot analyse your own interactions, unless they occurred before taking the course.
Once your dataset has been approved, you will need to:
- explore it in detail numerous times and identify the concept that is most salient in the data;
- choose 2 sample extracts for your analysis (if you are using video/audio data, you will need to transcribe it);
- analyse the selected extracts in light of your chosen concept.
IMPORTANT: Start looking for the data early in the semester!
Interaction Project - written submission (30%)
Due: First week after the revision week
Length: 1800-2000 words (excluding extracts and references)
Your written submission must include the following sections and at least 10 references (for more information, see the template on Blackboard):
- Introduction (explanation of why it is important to research pragmatic phenomena of digital discourse - provide examples from empirical studies);
- Literature review (research done in relation to the identified concept + aims of this project);
- Data description (source, participants, context, etc.);
- Analysis & discussion (here you need to focus on 1 concept from the course that became visible in the recorded interaction): provide in-depth analyses of 2 extracts.
- Conclusion (present a summary of your research project).
Generative AI & MT Statement
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
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: Does not show understanding of interactional and pragmatics features in digital discourse |
| 2 (Fail) | 25 - 44 |
Minimal evidence of achievement of course learning outcomes. Course grade description: Shows minimal understanding of interactional and pragmatics features in digital discourse |
| 3 (Marginal Fail) | 45 - 49 |
Demonstrated evidence of developing achievement of course learning outcomes Course grade description: Shows limited understanding of interactional and pragmatics features in digital discourse |
| 4 (Pass) | 50 - 64 |
Demonstrated evidence of functional achievement of course learning outcomes. Course grade description: Shows functional understanding of interactional and pragmatics features in digital discourse |
| 5 (Credit) | 65 - 74 |
Demonstrated evidence of proficient achievement of course learning outcomes. Course grade description: Shows proficient understanding of interactional and pragmatics features in digital discourse |
| 6 (Distinction) | 75 - 84 |
Demonstrated evidence of advanced achievement of course learning outcomes. Course grade description: Shows advanced understanding of interactional and pragmatics features in digital discourse |
| 7 (High Distinction) | 85 - 100 |
Demonstrated evidence of exceptional achievement of course learning outcomes. Course grade description: Shows exceptional understanding of interactional and pragmatics features in digital discourse |
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.
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
| Learning period | Activity type | Topic |
|---|---|---|
Multiple weeks From Week 1 To Week 13 |
Lecture |
Lecture Learning outcomes: L01, L03 |
General contact hours |
Contact Learning outcomes: L01, L02, L03, L05 |
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:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments - Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.