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Unit of study_

BUSS6101: Elective Option

Semester 2, 2021 [Normal day] - Remote

Elective unit option.

Unit details and rules

Unit code BUSS6101
Academic unit Business School
Credit points 6
Prohibitions
? 
None
Prerequisites
? 
None
Corequisites
? 
None
Assumed knowledge
? 

None

Available to study abroad and exchange students

No

Teaching staff

Coordinator Ganna Pogrebna, ganna.pogrebna@sydney.edu.au
Type Description Weight Due Length
Small continuous assessment Weekly Participation Assignments
Weekly assignments
30% - Varied
Outcomes assessed: LO1 LO6 LO5 LO3 LO2
Assignment Individual Assignment
Individual assignment
40% - 5,000 words
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6
Presentation group assignment Group work
Presentation
30% Week 07 Varied
Outcomes assessed: LO4 LO5
group assignment = group assignment ?

Assessment summary

TBC

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 sydney.edu.au/students/guide-to-grades.

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.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

Late assignments will be penalised as per the Business School policy.

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.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

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.

WK Topic Learning activity Learning outcomes
Week 01 Introduction: Artificial Intelligence or Intelligent Automation? Lecture and tutorial (4 hr) LO1 LO4 LO6
Week 02 Human-AI Interaction and Consumer Behaviour Analytics Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO6
Week 03 Risk Management in the Age of AI Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 04 Responsible Analytics, Ethics, Self-Regulation and Governance in the Age of AI Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 05 Analytics for Digital Transformation Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 06 Extracting Business Insights from Data Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 07 AI NUDGEATHON AND ASSESSED GROUP WORK Workshop (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 08 Applications: Blockchain: Past, Present and Future Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 09 Applications: Managing Feedback through Data-driven Methods Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 10 Applications: Leadership and People Analytics in the Age of AI Lecture and tutorial (4 hr) LO1 LO2 LO3 LO4 LO5 LO6

Attendance and class requirements

Lecture recordings: All lectures and seminars are recorded and will be available on Canvas for student use. Please note the Business School does not own the system and cannot guarantee that the system will operate or that every class will be recorded. Students should ensure they attend and participate in all classes.

 

Camera usage: Please, note that in 2021 this unit will be delivered online and you are expected to have your camera turned on at all times during work in group sessions as well as during your individual presentations to the class. 

 

Lecture and class dates: Please, see Canvas page for precise dates of each lecture/tutorial, as delivery opf various units in 2020 shifted in the calendar.

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

Readings will be available through Canvas page for this unit.

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.

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

  • LO1. approach and define real-world problems and limitations in leading digital transformation, which responsible thinking brings to data-driven business models
  • LO2. identify appropriate measures, variables and collection mechanisms of suitable data to minimize algorithmic bias and maximize business and customer value
  • LO3. select and apply the most appropriate methods and techniques to analyse the data and solve the problem
  • LO4. critically evaluate existing data science methodology against business needs
  • LO5. communicate AI and analytics findings for business-level understanding
  • LO6. approach all stages of the business problem-solving process in responsible and ethical manner

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
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

Alignment with Competency standards

Outcomes Competency standards
LO1
NESA Priority Area Elaborations - NESA
3-ICT.10. Ability to critically evaluate, retrieve, manipulate and manage the information from a range of digital sources including social media
LO2
NESA Priority Area Elaborations - NESA
3-ICT.02. Knowledge of responsible and ethical use of digital information including in relation to plagiarism, copyright, censorship, bullying and privacy
3-ICT.09. Understanding of the issues of appropriate access to, and verification of, information gained from a variety of sources including the Internet and other digital resources
LO3
NESA Priority Area Elaborations - NESA
3-ICT.02. Knowledge of responsible and ethical use of digital information including in relation to plagiarism, copyright, censorship, bullying and privacy
3-ICT.09. Understanding of the issues of appropriate access to, and verification of, information gained from a variety of sources including the Internet and other digital resources
LO4
NESA Priority Area Elaborations - NESA
3-ICT.10. Ability to critically evaluate, retrieve, manipulate and manage the information from a range of digital sources including social media
3-ICT.12. Ability to construct and manipulate texts and images, create presentations and store and retrieve digital information for classroom and on-line learning
LO5
NESA Priority Area Elaborations - NESA
3-ICT.12. Ability to construct and manipulate texts and images, create presentations and store and retrieve digital information for classroom and on-line learning
LO6
NESA Priority Area Elaborations - NESA
3-ICT.02. Knowledge of responsible and ethical use of digital information including in relation to plagiarism, copyright, censorship, bullying and privacy

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

Minor changes have been made in 2021 to simplify assessment schedule.

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.