Outline

Overview

In this unit you will produce knowledge for Wikipedia audiences around the globe. You will write across networks, negotiate various discourse communities, and contribute to and draw from creative commons resources while increasing the number of diverse voices that contribute to networked knowledge.

Unit details and rules

Academic unit
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Frances Di Lauro, frances.dilauro@sydney.edu.au
Tutor(s)	Megan Nash, megan.nash@sydney.edu.au
	Daniel Dixon, daniel.dixon@sydney.edu.au
	Brandon Thai, brandon.thai@sydney.edu.au
	Jedidiah Evans, jedidiah.evans@sydney.edu.au
	Lawrence Boikov, lawrence.boikov@sydney.edu.au
	Ryan Johnson, ryan.johnson@sydney.edu.au
	Robert Myers, r.myers@sydney.edu.au
	Thomas Melick, thomas.melick@sydney.edu.au
	Jessica Sun, jsun8032@uni.sydney.edu.au
	Carrol Besseling, carrol.besseling@sydney.edu.au

Type	Description	Weight	Due	Length
In-semester test	Module 2 Quiz MCQ	10%	Week 01 Due date: 28 Feb 2020 at 23:00	250 words
Outcomes assessed:
In-semester test	Module 1 Quiz MCQ	10%	Week 01 Due date: 28 Feb 2020 at 23:00	250 words equivalent
Outcomes assessed:
Assignment	Proposal, justification and bibliography n/a	20%	Week 05 Due date: 23 Mar 2020 at 23:00	1000 words
Outcomes assessed:
Assignment	Draft article n/a	20%	Week 08 Due date: 24 Apr 2020 at 00:04	1000 words
Outcomes assessed:
Participation	Peer-review n/a	5%	Week 09 Due date: 01 May 2020 at 23:00	500 words equivalent
Outcomes assessed:
Participation	Self-assessment Self-review of draft	5%	Week 10 Due date: 08 May 2020 at 23:00	500 words
Outcomes assessed:
Assignment	Final article submission Final article	30%	Week 13 Due date: 29 May 2020 at 23:00	1000 words equivalent
Outcomes assessed:

Assessment summary

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a High distinction indicates work of an exceptional standard, a Distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100	Awarded when you demonstrate the learning outcomes for the unit at an exceptional standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Distinction	75 - 84	Awarded when you demonstrate the learning outcomes for the unit at a very high standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Credit	65 - 74	Awarded when you demonstrate the learning outcomes for the unit at a good standard, as defined by grade descriptors or exemplars outlined by your faculty or school
Pass	50 - 64	Awarded when you demonstrate the learning outcomes for the unit at an acceptable standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Weekly schedule

WK	Topic	Learning activity
Week 01	1 x 1 hour online lecture 1 x 2 hour live seminar	Lecture and tutorial (3 hr)
Week 02	1 x 1 hour online lecture 1 x 2 hour live seminar	Lecture and tutorial (3 hr)
Week 03	1 x 1 hour online lecture 1 x 2 hour live seminar	Lecture and tutorial (3 hr)
Week 04	1 x 1 hour online lecture 1 x 2 hour live seminar	Lecture and tutorial (3 hr)
Week 05	1 x 1 hour online lecture 1 x 2 hour live seminar	Lecture and tutorial (3 hr)
Week 06	1 x 1 hour online lecture 1 x 2 hour live seminar	Lecture and tutorial (3 hr)
Week 07	1 x 1 hour online lecture 1 x 2 hour live seminar	Lecture and tutorial (3 hr)
Week 08	1 x 1 hour online lecture 1 x 2 hour live seminar	Lecture and tutorial (3 hr)
Week 09	1 x 1 hour online lecture 1 x 2 hour live seminar	Lecture and tutorial (3 hr)
Week 10	1 x 1 hour online lecture 1 x 2 hour live seminar	Lecture and tutorial (3 hr)
Week 11	1 x 1 hour online lecture 1 x 2 hour live seminar	Lecture and tutorial (3 hr)
Week 12	1 x 1 hour online lecture 1 x 2 hour live seminar	Lecture and tutorial (3 hr)
Week 13	1 x 1 hour online lecture 1 x 2 hour live seminar	Lecture and tutorial (3 hr)

Attendance and class requirements

Attendance: students are expected to attend 90% of their classes. If you attend less than 50% of classes, regardless of the reasons, you may be referred to the Examiner’s Board which will decide whether you should pass or fail the unit of study if your attendance falls below this threshold.
Lecture recording: Most lectures (in recording-equipped venues) will be recorded and may be made available to students on the LMS. However, you should not rely on lecture recording to substitute your classroom learning experience.
Preparation: students should commit to spend approximately three hours’ preparation time (reading, studying, homework, essays, etc.) for every hour of scheduled instruction.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

All reading material for OLES2129 is accessible through hyperlinks in the online lecture modules.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. demonstrate proficiency in research, ethics and persuasion
LO2. think critically and write for a broad audience
LO3. use visual editor software to edit or create online content
LO4. identify and complete projects that draw on the conventions of your disciplinary area or area of interest
LO5. research incrementally to build a comprehensive and substantial draft article
LO6. create and add material to, and draw from creative commons repositories
LO7. create a good or featured article that contributes to Wikiprojects.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

No changes have been made since this unit was last offered

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

OLES2129: Writing for the Digital World

Semester 1, 2020 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links