Course coordinator
Dr Priscilla Man
Course overview
- Study period
- Semester 1, 2026 (23/02/2026 - 20/06/2026)
- Study level
- Postgraduate Coursework
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Economics School
This course explains how to conduct basic research in economics. It covers the main steps involved in the research process: development of the research proposal, finding and critically evaluating relevant literature, model development, methods for locating and collecting economic data, analytical methods, and writing mechanics. The course has a strong practical focus.
This course introduces students to practical skills required for conducting economic research. In the first part of this course, we will cover basic research skills -- ethics, posing research questions, literature search and evaluation. Next, we will survey research tools addressing causal identification in economic research. The last part of the course is devoted to research communication and collaboration -- presentation, pitching, giving and receiving feedback. Through sharing from industry speakers and workshops on employability, students can develop transferable skillsﾠthat can be applied to both industry and academic contexts. Who says research is only an academic pursuit?
Assessments are scaffolded, starting from in-class exercises through which students practise the skills introduced, leading to a research proposal and a presentation. For those intending for further academic research, the research proposal can be used as a stepping stone to Thesis (i.e., ECON7930/33/34).
Blended-learning
ECON7950 is a blended-learning course with the following learning activities:ﾠ
- Weekly online learning modules on UQ Extend;
- 2 -hour in-person, interactive lectures during weeks 1 to 13; and
- Three 2-hour tutorials: Week 4, week 8, and week 12.
Course requirements
Assumed background
Students are assumed to have backgroundﾠknowledge in microeconomics, macroeconomics and econometrics. Some knowledge in your field of research interests is expected.
Incompatible
You can't enrol in this course if you've already completed the following:
ECON7920 or 7921 or 7922
Course contact
School enquiries
School Enquiries, School of Economics
All enquiries regarding student and academic administration (i.e. non-course content information, e.g., class allocation, timetables, extension to assessment due date, etc.) should be directed toﾠenquiries@economics.uq.edu.au.ﾠ
Enquiries relating specifically to course content should be directed to the Course Coordinator/Lecturer.
Course staff
Lecturer
Dr Priscilla Man
Tutor
Mrs Imesha Waidyarathne
Timetable
The timetable for this course is available on the UQ Public Timetable.
Additional timetable information
Tutorial Preferencing: Students must select their preferred tutorial times via their MyUQ Timetable. This should be completed before the end of Teaching Week 1.
Tutorials Information: There will be three tutorials in this course, in Week 4, 8 and 12.
Lectures commence in Week 1.
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 course is to equip students with the necessary skills ﾠto undertake supervised independent research work ﾠto a professional standard, and in particular,ﾠ to undertaking future thesis work.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Apply research ethics and ethical standards in economic research.
LO2.
Pose targeted research questions and articulate their relationship to the literature in economics.
LO3.
Apply appropriate research tools for economic investigations.
LO4.
Communicate research ideas effectively to a specialised audience.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Participation/ Student contribution, Practical/ Demonstration, Reflection |
In-class exercises
|
20% (4% each, best 5 out of 7) |
In-lecture Week 2 In-lecture Week 4 In-lecture Week 5 In-lecture Week 6 In-lecture Week 7 In-lecture Week 8 In-lecture Week 9 |
| Paper/ Report/ Annotation, Presentation |
Research Proposal
|
50% |
5/05/2026 1:00 pm
The due date above is for the written proposal only. Interviews will be scheduled through Blackboard. |
| Presentation, Poster | Infographic Poster Presentation | 30% |
8/06/2026 1:00 pm |
Assessment details
In-class exercises
- In-person
- Mode
- Activity/ Performance, Written
- Category
- Participation/ Student contribution, Practical/ Demonstration, Reflection
- Weight
- 20% (4% each, best 5 out of 7)
- Due date
In-lecture Week 2
In-lecture Week 4
In-lecture Week 5
In-lecture Week 6
In-lecture Week 7
In-lecture Week 8
In-lecture Week 9
- Other conditions
- Longitudinal.
- Learning outcomes
- L01, L02, L03, L04
Task description
Throughout the course, there will be seven (7) lectures with interactive class activities. Students will complete a worksheet and reflect on their practices as they work through these activities with their peers. Course staff will bring physical copies of the worksheet for students to complete. At the end of the respective lecture, each student will submit their completed physical worksheet to the lecturer in-person. A student can earn up to 4 marks for each completed worksheet submitted. Only the best five (5) out of seven (7) worksheets will be counted.
These exercises are NOT quizzes. They are designed to guide students through a specific aspect of research (e.g., literature search), invite students to try different techniques, and ask them to reflect on their practices. The performance in the activities per se does not affect the marks from these exercises. Only the quality of documentation and/or reflection in the worksheet will affect the marks.
Since it may be difficult to add additional students after an activity has started, students wishing to earn marks from an in-class exercise should attend the respective lecture on time. Course staff reserves the right to refuse a worksheet submission if a student arrives to class after the core component of the activity is over.
As the activities are to be run during lectures, students are expected to be available. Students with a disability, mental health or medical condition, illness, injury or exceptional circumstances preventing them from regular class attendance should contact the course coordinator at the beginning of the semester to organise alternative arrangements.
Artificial Intelligence and Machine Learning Use
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
Submit the physical copy of completed worksheet in-person to the lecturer at the end of the lecture.
Deferral or extension
You cannot defer or apply for an extension for this assessment.
Due to the interactive nature of the tasks, extensions are not possible. If a student misses an in-class exercise, the best five (5) marks out of all the in-class exercises attempted will count. Students missing more than two (2) in-class exercises due to exceptional circumstances beyond their control should speak to the course coordinator for alternative arrangements.
Late submission
You will receive a mark of 0 if this assessment is submitted late.
As the activities are interactive in nature and are to be completed in-class, late submission is not possible.
Research Proposal
- Identity Verified
- In-person
- Mode
- Oral, Written
- Category
- Paper/ Report/ Annotation, Presentation
- Weight
- 50%
- Due date
5/05/2026 1:00 pm
The due date above is for the written proposal only. Interviews will be scheduled through Blackboard.
- Other conditions
- Secure.
- Learning outcomes
- L01, L02, L03, L04
Task description
Students will play the role of an economic consultant tasked with formulating a research proposal. They will submit a written proposal for their client's perusal, then meet the client in an in-person interview to discuss the detail of the proposal orally.
Written Proposal
The written proposal must be submitted in the format of the template provided on the course Blackboard site. In the written proposal, students should:
- State and classify their research question;
- Describe the innovations of their proposal relative to existing knowledge;
- Describe the methods they would like to use to answer their question; and
- Outline the expected benefits from their proposed research.
The completed template should be submitted electronically through Blackboard by the specified due date.
Oral Interview
Students will attend an individual in-person interview of approximately 5--7 minutes with a marker (playing the role of the client) to discuss their submitted written proposal. Students will need to clarify, explain, and justify elements of their own proposal. Students will not be asked questions about course materials that are not relevant to their submitted proposal. However, students will need to demonstrate detailed comprehension of their own submitted proposal without electronic aids.
The interview time slot will be allocated in coordination with students' preferences and can be OUTSIDE of lecture or tutorial time slots.
The interview is a mandatory integrated component of this assessment. The written proposal and the interview will be marked jointly on all criteria. If a student demonstrates poor understanding of their own written proposal, the student can be marked down on all criteria even if the details are in the written proposal.
Artificial Intelligence and Machine Learning use
This task has been designed to be challenging, authentic and complex. Whilst students may use Artificial Intelligence (AI) and/or Machine Translation (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
Written proposal: Submit completed template electronically to Turnitin via the course Blackboard site.
Oral interview: Students will schedule their interviews through Blackboard and attend their scheduled interviews.
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.
If a student misses their scheduled presentation time due to circumstances beyond their control, they should request an extension to the Research Proposal assessment with supporting documentation following the UQ assessment extension request process. If the extension is granted, an additional Q&A session will be held for students to make up their missed presentation.
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.
Failing to schedule, attend or complete the interview session could lead to a zero mark for the entire assessment item. Being late for the session at the allocated time will be treated as failing to attend the presentation.
Infographic Poster Presentation
- Mode
- Product/ Artefact/ Multimedia
- Category
- Presentation, Poster
- Weight
- 30%
- Due date
8/06/2026 1:00 pm
- Learning outcomes
- L01, L02, L03, L04
Task description
Based on their research proposals submitted for the Research Proposal assessment, students will create an infographic poster depicting their research proposal and record themselves doing a 3-minute poster presentation.
Infographic Poster
Students will create a one-page A1-size infographic poster depicting their research proposal for a professional audience. A successful poster should convince its readers that the research project is addressing an interesting, significant question, and that the researchers are applying the appropriate methods and tools to answer this question.
Presentation Video
Students will make a three-minute video, pitching their research proposal to a professional audience using the infographic poster as their only presentation aid. In the video, students should:
- Introduce their research question and explain how it aims to address a significant gap in knowledge or problem;
- Outline the methods they intend to answer the question; and
- Explain how answering the question may create new knowledge or benefits.
Students are required to be physically and clearly visible in the video.
Students must submit both the Infographic Poster and the Presentation Video to be eligible for marks. Course staff will not mark posters without a video or videos without a poster.
Artificial Intelligence and Machine Learning use
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
Poster: Submit electronically to Turnitin via the course Blackboard site.
Video: Submit electronically to Blackboard Assignment via the course Blackboard site. Please read the instructions on submitting a video assignment before making the submission.
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.
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% - 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
Plagiarism
The School of Economics is committed to reducing the incidence of plagiarism. Further information on plagiarism and how to avoid an allegation of plagiarism is available in this course profile under Policies and Procedures. Please refer to the Academic Integrity Modules (AIM). It is strongly recommended that you complete the AIM if you have not already done so.
SUBMISSION OF ASSIGNMENTS:
All assignments must be submitted by the due date and time stated in the course profile. For this course, students are required to submit an electronic copy through the relevant submission link on the course Blackboard site.
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.
Additional learning resources information
Academic Papers for Discussion
We will discuss a number of academic papers during the course. A list with a reading schedule will be posted on Blackboard, with papers added gradually during the semester. It is important that students read these papers before they are discussed in class.
UQ Library Resources
APA 7th Referencing guide ﾠ-- This course adopts APA 7th referencing style.
EndNote guide -- You are not required to use EndNote for this course, but if you wish to use it, UQ Library provides a helpful guide.
AI Student Hub -- Use AI responsibly and effectively in your studies. Inappropriate or unreferenced AI use in ECON7950 will be handled as academic misconduct.
Write, Cite, Submit -- UQ Library's guide on planning assessments, referencing and submitting assessments.
Choose the right tool -- For finding the right tool to make your infographic poster and video.
Student Services Resources
UQ Student Central offers a range of student support services, ranging from handling day-to-day student life to crisis support. The following resources may be of particular interest:
Student workshops -- There are many different workshops but ECON7950 students may be particularly interested in the peer-led drop-in writing sessions.
Academic English support -- Your English is probably better than you think, if you are willing to use it.
Study adjustments -- ECON7950 supports students with a disability, mental health or medical condition, illness, injury or exceptional circumstances. If a condition or circumstance is impacting your ability to study, make an appointment with an adviser to create a plan and discuss the support available to you.
BEL Employability Resources
BEL Faculty Careers and Employability ﾠoffers a range of development workshops (among other services) on employability skills, which are part of the focus of this course. See their list of workshops.
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) |
Lecture |
Lecture 1: Introduction and Research Ethics Introduction to the course. Research ethics in economics. Learning outcomes: L01 |
Week 2 (02 Mar - 08 Mar) |
Lecture |
Lecture 2: Research Questions The what, why and how of research. JEL Classification. In-class exercise 1 (assessment item) will be completed during this lecture. Learning outcomes: L01, L02, L03 |
Week 3 (09 Mar - 15 Mar) |
Lecture |
Lecture 3: Library Resources A workshop by UQ Librarians on library resources for conducting research. Learning outcomes: L01, L02, L03 |
Week 4 (16 Mar - 22 Mar) |
Tutorial |
Tutorial 1: Research Question Carnival Working in teams, students will practise posing research questions and locating the relevant literature. Learning outcomes: L02, L03, L04 |
Lecture |
Lecture 4: Literature Search Positioning your research question against the existing literature. In-class exercise 2 (assessment item) will be completed during this lecture. Learning outcomes: L01, L02, L03, L04 |
|
Week 5 (23 Mar - 29 Mar) |
Lecture |
Lecture 5: Randomised Controlled Trials Randomised controlled trials and economic experiments. In-class exercise 3 (assessment item) will be completed during this lecture. Learning outcomes: L01, L02, L03 |
Week 6 (30 Mar - 05 Apr) |
Lecture |
Lecture 6: Causal Identification Difference-in-difference, Regression discontinuity, Instrumental variables and Propensity score matching. In-class exercise 4 (assessment item) will be completed during this lecture. Learning outcomes: L01, L02, L03 |
No student involvement (Breaks, information) |
Public Holiday (Good Friday) Friday 03/04 is a public holiday. There will be no lecture, tutorial, or consultation on this day. |
|
Mid-sem break (06 Apr - 12 Apr) |
No student involvement (Breaks, information) |
Mid-semester break No lecture, workshop or consultation. |
Week 7 (13 Apr - 19 Apr) |
Lecture |
Lecture 7: Structural Estimation Structural estimation and calibration. In-class exercise 5 (assessment item) will be completed during this lecture. Learning outcomes: L01, L02, L03 |
Week 8 (20 Apr - 26 Apr) |
Tutorial |
Tutorial 2: Research Proposal Clinic Be a staff member and mark a mock research proposal! How would you improve it? Learning outcomes: L01, L02, L03, L04 |
Lecture |
Lecture 8: Planning Research Bringing a research proposal together. In-class exercise 6 (assessment item) will be completed during this lecture. Learning outcomes: L01, L02, L03, L04 |
|
Week 9 (27 Apr - 03 May) |
Lecture |
Lecture 9: Pitching research Persuasion and explaining research ideas. In-class exercise 7 (assessment item) will be completed during this lecture. Learning outcomes: L01, L03, L04 |
Week 10 (04 May - 10 May) |
No student involvement (Breaks, information) |
Labour Day (Public Holiday) Monday 04/05 is a public holiday (Labour Day). There will be no lecture, tutorial, or consultation on this day. |
Lecture |
Lecture 10: Research in an Industry Context Guest lecture by Dr. Sarah Cornell-Farrow (FTI Consulting) on conducting economic research in an industry context. Learning outcomes: L01, L02, L03, L04 |
|
Week 11 (11 May - 17 May) |
Lecture |
Lecture 11: Communicating Economics Guest lecture by Dr. Sunny Kim Nguyen (Moody) on communicating economics to a wide audience. Learning outcomes: L01, L02, L03, L04 |
Week 12 (18 May - 24 May) |
No student involvement (Breaks, information) |
Tutorial 3: Assessment Interviews Tutorial hours will be used for conducting Research Proposal interviews (assessment item). Learning outcomes: L01, L02, L03, L04 |
No student involvement (Breaks, information) |
Lecture 12: Assessment Interviews Lecture hours will be used for conducting Research Proposal interviews (assessment item). |
|
Week 13 (25 May - 31 May) |
Lecture |
Lecture 13: Grand Finale Join us for the 3-minute proposal competition and vote for your favourite contestant! Learning outcomes: L01, L02, L03, L04 |
Additional learning activity information
In-class exercises (assessment) will be conducted during lectures as specified above. Students are expected to attend lectures to complete these exercises. Absence will lead to incompletion of in-class exercises. Students with a disability, mental health or medical condition, illness, injury or exceptional circumstances preventing them from regular class attendance should contact the course coordinator at the beginning of the semester to organise alternative arrangements.
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.