Students

COMP8440 – Automated Decision Making in Business

2026 – Session 1, In person-scheduled-weekday, North Ryde

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff Convenor & Lecturer
Xiaohan Yu
xiaohan.yu@mq.edu.au
Floor 3, 3 Innovation Road
By appointment
Lecturer
Neda Sakhaee
neda.sakhaee@mq.edu.au
By appointment
Credit points Credit points
10
Prerequisites Prerequisites
COMP6200
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description

Automation of decision making has been part of AI for a long time. It is becoming more important with the entrenched position of AI in modern life. In this unit students will be exposed to historical, foundational, cognitive, socio-cultural as well as implementational aspects of automatic decision making. Students will evaluate the kinds of decisions that are amenable to automation, the sources of data that are required, and the kinds of systems that can be built to complete the task.

Learning in this unit enhances student understanding of global challenges identified by the United Nations Sustainable Development Goals (UNSDGs) Industry, Innovation and Infrastructure.

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates

Learning Outcomes

On successful completion of this unit, you will be able to:

  • ULO1: Use tangible and intangible resources to understand requirements needed for automated decision making in business
  • ULO2: Demonstrate effective communication of AI generated decisions with various stakeholders in a business
  • ULO3: Critically assess the positive and negative socioeconomic consequences and implications of automated decision making in an industry context
  • ULO4: Evaluate alternate AI technologies for use to support decision making in business.

General Assessment Information

Release

Assessment 1 - System Evaluation: To be released no later than 06/03/2026

Assessment 2 - Business Rules at work: To be released no later than 02/04/2026

Assessment 3 - Reflective Report: To be released no later than 01/05/2026

 

Requirements to Pass this Unit

To pass this unit you must:

  • Achieve a total mark equal to or greater than 50%.

 

Late Submission Policy

  • 5% penalty per day: If you submit your assessment late, 5% of the total possible marks will be deducted for each day (including weekends), up to 7 days.
    • Example 1 (out of 100): If you score 85/100 but submit 20 hours late, you will lose 5 marks and receive 80/100.
    • Example 2 (out of 30): If you score 27/30 but submit 1 day late, you will lose 1.5 marks and receive 25.5/30.
  • After 7 days: Submissions more than 7 days late will receive a mark of 0.
  • Extensions:
    • Automatic short extension: Some assessments are eligible for automatic short extension. You can only apply for an automatic short extension before the due date.
    • Special Consideration: If you need more time due to serious issues and for any assessments that are not eligible for Short Extension, you must apply for Special Consideration.

Need help? Review the Special Consideration page HERE

 

Assessment 1 – YES, Late Submission Policy applies.

Assessment 2 – YES, Late Submission Policy applies.

Assessment 3 – YES, Late Submission Policy applies.

 

Special Consideration

The Special Consideration Policy aims to support students who have been impacted by short-term circumstances or events that are serious, unavoidable and significantly disruptive, and which may affect their performance in assessment. If you experience circumstances or events that affect your ability to complete the assessments in this unit on time, please inform the convenor and submit a Special Consideration request through http://connect.mq.edu.au/.

 

Assessment Tasks

Name Weighting Hurdle Due Groupwork/Individual Short Extension AI Approach
System Evaluation 35% No Due 27/03/2026 Individual No Observed
Business Rules at work 35% No 08/05/2026 Individual Yes Open
Reflective Report 30% No 29/05/2026 Individual Yes Open

System Evaluation

Assessment Type 1: Experiential task
Indicative Time on Task 2: 27 hours
Due: Due 27/03/2026
Weighting: 35%
Groupwork/Individual: Individual
Short extension 3: No
AI Approach: Observed

Evaluate an existing product or system for a given task using available data.
On successful completion you will be able to:
  • Use tangible and intangible resources to understand requirements needed for automated decision making in business
  • Critically assess the positive and negative socioeconomic consequences and implications of automated decision making in an industry context
  • Evaluate alternate AI technologies for use to support decision making in business.

Business Rules at work

Assessment Type 1: Portfolio
Indicative Time on Task 2: 27 hours
Due: 08/05/2026
Weighting: 35%
Groupwork/Individual: Individual
Short extension 3: Yes
AI Approach: Open

Design and implement a set of business rules using an open-source rules engine, focusing on how these rules can be applied to automate decision-making processes in a business.
On successful completion you will be able to:
  • Use tangible and intangible resources to understand requirements needed for automated decision making in business
  • Demonstrate effective communication of AI generated decisions with various stakeholders in a business
  • Evaluate alternate AI technologies for use to support decision making in business.

Reflective Report

Assessment Type 1: Reflection task
Indicative Time on Task 2: 21 hours
Due: 29/05/2026
Weighting: 30%
Groupwork/Individual: Individual
Short extension 3: Yes
AI Approach: Open

A reflective report on the student's experience in the unit and their vision of the impact of automated decision making on industry practice.
On successful completion you will be able to:
  • Demonstrate effective communication of AI generated decisions with various stakeholders in a business
  • Critically assess the positive and negative socioeconomic consequences and implications of automated decision making in an industry context

1 If you need help with your assignment, please contact:

  • the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
  • Academic Success for academic skills support.

2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation.

3 An automatic short extension is available for some assessments. Apply through the Service Connect Portal.

Delivery and Resources

Week 1 Classes

In week 1, we will have on-site lecture on Tuesday (2.0 hrs) 5:00 PM - 7:00 PM (23WW P.G.Price Lecture Theatre). Practical will start from week 2.

Methods of Communication

We will communicate with you via your university email and through announcements on iLearn. Queries to convenors can either be placed on the iLearn discussion board or sent to the unit convenor via the contact email on iLearn.

 

Policies and Procedures

Macquarie University policies and procedures are accessible from Policy Central (https://policies.mq.edu.au). Students should be aware of the following policies in particular with regard to Learning and Teaching:

Students seeking more policy resources can visit Student Policies (https://students.mq.edu.au/support/study/policies). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.

To find other policies relating to Teaching and Learning, visit Policy Central (https://policies.mq.edu.au) and use the search tool.

Student Code of Conduct

Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/admin/other-resources/student-conduct

Results

Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit connect.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au

Academic Integrity

At Macquarie, we believe academic integrity – honesty, respect, trust, responsibility, fairness and courage – is at the core of learning, teaching and research. We recognise that meeting the expectations required to complete your assessments can be challenging. So, we offer you a range of resources and services to help you reach your potential, including free online writing and maths support, academic skills development and wellbeing consultations.

Student Support

Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/

Academic Success

Academic Success provides resources to develop your English language proficiency, academic writing, and communication skills.

The Library provides online and face to face support to help you find and use relevant information resources. 

Student Services and Support

Macquarie University offers a range of Student Support Services including:

Student Enquiries

Got a question? Ask us via the Service Connect Portal, or contact Service Connect.

IT Help

For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/. 

When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.

Changes from Previous Offering

We value student feedback to be able to continually improve the way we offer our units. As such we encourage students to provide constructive feedback via student surveys, to the teaching staff directly, or via the FSE Student Experience & Feedback link in the iLearn page.

Changes since First Published

Date Description
13/02/2026 Switchde due for two assessment (correction)

Unit information based on version 2026.03 of the Handbook