Course coordinator
Associate Professor Metin Uyanik
Course overview
- Study period
- Semester 1, 2026 (23/02/2026 - 20/06/2026)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Economics School
Developments & implications of microeconomic theory.
Microeconomic theory aims to model economic activity as an interaction of individual economic agents pursuing their own goals. It provides the foundations for economic, political, strategic, and financial analysis. This subject aims to present a systematic treatment of decision-making. The subject demonstrates how we can use models to understand the fundamental principles behind familiar economic concepts, and how we apply these models. Examples and applications will be used to motivate concepts.
Course requirements
Assumed background
See Pre-requisites.
Prerequisites
You'll need to complete the following courses before enrolling in this one:
ECON1050 + 2010. For BAdvFin&Econ(Hons) students - ECON1050 and 2030.
Recommended prerequisites
We recommend completing the following courses before enrolling in this one:
ECON2050
Course contact
Course staff
Timetable
The timetable for this course is available on the UQ Public Timetable.
Additional timetable information
Please see the Learning Activities section of this Course Profile for the timetabling implications of public holidays.
Important Dates:
- Public Holidays: Fri 3 April (Good Friday), Mon 4 May (Labour Day).
- Mid-Semester Break: 6 April - 10 April. Semester 1 classes recommence on Mon 13 April.
Students should refer to the timetable prior to the commencement of classes to ensure that they have the most up to date information, as from time to time late room changes may occur.
Aims and outcomes
The aim of this subject is to present a systematic treatment of the basic tools of microeconomicﾠanalysis including procedures for analyzing decision making under uncertainty.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Demonstrate familiarity with the mathematical and intuitive fundamentals of economic theory.
LO2.
Analyse, critically evaluate, and develop advanced economic models, including modelling choices involving uncertainty and strategic interaction.
LO3.
Analyse and present microeconomic reasoning and problems in group-based activities, including the responsible use of artificial intelligence to support analysis.
LO4.
Apply the main principles of microeconomic theory to economic problems.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Quiz, Reflection |
Review Questions
|
10% |
Refer to Description (weekly) |
| Participation/ Student contribution, Presentation, Reflection |
Interactive In-Class Learning Activities
|
15% |
Due during the Workshops. See the Description. |
| Essay/ Critique, Participation/ Student contribution, Presentation |
AI Assisted Group Case Study with Presentation: Microeconomic Theory in Action
|
35% |
The Written Case Study is due on May 29, Friday 4pm. The Presentation will be during the examination period. Detailed information will be posted on Blackboard. |
| Examination |
End-of-semester Exam
|
40% |
End of Semester Exam Period 6/06/2026 - 20/06/2026 |
Assessment details
Review Questions
- Online
- Mode
- Written
- Category
- Quiz, Reflection
- Weight
- 10%
- Due date
Refer to Description (weekly)
- Other conditions
- Time limited.
- Learning outcomes
- L01, L02, L04
Task description
After each workshop (excluding the last workshop), review questions will be posted on Blackboard. There are 60+ questions in total.
The answers must be submitted before the next class. The due date of review questions for each workshop (say Workshop X) is 10am on Wednesday in the following week (before Workshop X+1).
You have only one attempt to submit the answers. Your answers will be graded only if they are SUBMITTED before the due date.
Each review question is worth 0.25 marks. The best 40 out of all (60+) scores are considered.
The answers will be released after the due date.
The details will be posted on Blackboard.
Use of AI or 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
Refer to Description (weekly)
Deferral or extension
You cannot defer or apply for an extension for this assessment.
The best 40 out of all (60+) scores are considered.
Late submission
Late submission is not allowed and a penalty of 100% for non-submissions.
Interactive In-Class Learning Activities
- Identity Verified
- Team or group-based
- In-person
- Mode
- Oral, Written
- Category
- Participation/ Student contribution, Presentation, Reflection
- Weight
- 15%
- Due date
Due during the Workshops. See the Description.
- Other conditions
- Time limited, Peer assessment factor.
- Learning outcomes
- L01, L02, L03, L04
Task description
Each workshop has individual and group based interactive learning activities during the active learning sessions.
There are in total 30+ in class learning activities throughout the course. They involve individual and group activities as well as presentations.
Each learning activity is worth 1 mark. The best 15 out of all (30+) scores are considered.
The details will be posted on Blackboard.
Use of AI or MT: Some learning activities involve use of AI and some do not allow AI. Specific guidelines will be provided before each activity.
Submission guidelines
See the Description and Blackboard Announcements.
Deferral or extension
You cannot defer or apply for an extension for this assessment.
Extensions are not possible. The best 15 out of all (30+) scores are considered.
Late submission
Late submissions are not possible as students conduct the activities during the live workshop.
AI Assisted Group Case Study with Presentation: Microeconomic Theory in Action
- Team or group-based
- In-person
- Online
- Mode
- Oral, Written
- Category
- Essay/ Critique, Participation/ Student contribution, Presentation
- Weight
- 35%
- Due date
The Written Case Study is due on May 29, Friday 4pm.
The Presentation will be during the examination period.
Detailed information will be posted on Blackboard.
- Other conditions
- Time limited, Peer assessment factor, Secure.
- Learning outcomes
- L01, L02, L03, L04
Task description
This task consists of an AI-assisted case study, in which students will research and critically analyse a recent real-world case by using the models and tools of microeconomics we learn in this course.
This is a group assessment involving AI-Generated Output and Critical Analysis (Evaluation & Reflection) of this output and Presentation of the Case Study.
Detailed guideline will be provided on Blackboard.
Use of AI or 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
Detailed information will be posted on 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.
Requests for the granting of extensions must be submitted through my.UQ: Applying for an extension - my.UQ - University of Queensland with supporting documentation before the submission due date/time. If an extension is approved, the new agreed date for submission will be noted on the application and the student notified through their student email. Extensions cannot exceed the number of days you suffered from a medical condition, as stated on the medical certificate.
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.
The late submission penalties apply only to the written component of the case study.
Late submission for the presentation component is not possible.
End-of-semester Exam
- Identity Verified
- In-person
- Mode
- Written
- Category
- Examination
- Weight
- 40%
- Due date
End of Semester Exam Period
6/06/2026 - 20/06/2026
- Other conditions
- Time limited, Secure.
- Learning outcomes
- L01, L02, L04
Task description
Details will be posted on Blackboard.
Use of AI or MT: This assessment task is to be completed in-person. The use of generative Artificial Intelligence (AI) or Machine Translation (MT) tools will not be permitted. Any attempted use of AI or MT may constitute student misconduct under the Student Code of Conduct.
Exam details
| Planning time | 10 minutes |
|---|---|
| Duration | 120 minutes |
| Calculator options | (In person) Casio FX82 series only or UQ approved and labelled calculator |
| Open/closed book | Closed book examination - no written materials permitted |
| Exam platform | Paper based |
| Invigilation | Invigilated in person |
Submission guidelines
Deferral or extension
You may be able to defer this exam.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Grade | Cut off Percent | Description |
|---|---|---|
| 1 (Low Fail) | 0% - 29% |
Absence of evidence of achievement of course learning outcomes. |
| 2 (Fail) | 30% - 46% |
Minimal evidence of achievement of course learning outcomes. |
| 3 (Marginal Fail) | 47% - 49% |
Demonstrated evidence of developing achievement of course learning outcomes |
| 4 (Pass) | 50% - 64% |
Demonstrated evidence of functional achievement of course learning outcomes. |
| 5 (Credit) | 65% - 74% |
Demonstrated evidence of proficient achievement of course learning outcomes. |
| 6 (Distinction) | 75% - 84% |
Demonstrated evidence of advanced achievement of course learning outcomes. |
| 7 (High Distinction) | 85% - 100% |
Demonstrated evidence of exceptional achievement of course learning outcomes. |
Additional course grading information
A student's final overall end of semester percentage mark will be rounded to determine their final grade. For example, 64.5% rounds to 65%, while 64.4% rounds to 64%.
Supplementary assessment
Supplementary assessment is available for this course.
Additional assessment information
Using AI at UQ
Visit the AI Student Hub for essential information on understanding and using Artificial Intelligence in your studies responsibly.
Plagiarism
The School of Economics is committed to reducing the incidence of plagiarism. You are encouraged to read the UQ Student Integrity and Misconduct Policy available in the Policies and Procedures section of this course profile.
The Academic Integrity Module (AIM) outlines your obligations and responsibilities as a UQ student. It is compulsory for all new to UQ students to complete the AIM.
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 |
|---|---|---|
Week 1 (23 Feb - 01 Mar) |
Workshop |
L1. Introduction to Advanced Micro Economics Learning outcomes: L01 |
Week 2 (02 Mar - 08 Mar) |
Workshop |
L2. Decision under Certainty I: Preferences Learning outcomes: L01, L02, L03 |
Week 3 (09 Mar - 15 Mar) |
Workshop |
L3. Decision under Certainty II: Utility Theory Learning outcomes: L01, L02, L04 |
Week 4 (16 Mar - 22 Mar) |
Workshop |
L4. Decision under Certainty IV: Maximization Learning outcomes: L01, L02, L03, L04 |
Week 5 (23 Mar - 29 Mar) |
Workshop |
L5. Decision under Uncertainty: Expected Utility Learning outcomes: L01, L02, L03, L04 |
Week 6 (30 Mar - 05 Apr) |
Workshop |
L6. Game Theory -- Part I Learning outcomes: L01, L02 |
Mid-sem break (06 Apr - 12 Apr) |
No student involvement (Breaks, information) |
Mid-Semester Break |
Week 7 (13 Apr - 19 Apr) |
Workshop |
L7. Game Theory -- Part II Learning outcomes: L01, L02, L03 |
Week 8 (20 Apr - 26 Apr) |
Workshop |
L8. Game Theory -- Part III Learning outcomes: L01, L02, L03, L04 |
Week 9 (27 Apr - 03 May) |
Workshop |
L9. Consumer Theory Learning outcomes: L01, L02, L03, L04 |
Week 10 (04 May - 10 May) |
Workshop |
L10. Producer Theory Learning outcomes: L01, L02, L03, L04 |
Week 11 (11 May - 17 May) |
Workshop |
L11. Revealed Preference Learning outcomes: L01, L02, L03, L04 |
Week 12 (18 May - 24 May) |
Workshop |
L12. General Equilibrium -- Part I Learning outcomes: L01, L02, L03 |
Week 13 (25 May - 31 May) |
Workshop |
L13. General Equilibrium -- Part II & Review Learning outcomes: L01, L02, L03, L04 |
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 for Students Policy and Procedure
- AI for Assessment Guide
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.