Course overview
- Study period
- Semester 1, 2026 (23/02/2026 - 20/06/2026)
- Study level
- Postgraduate Coursework
- Location
- External
- Attendance mode
- Online
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- The Environment School
The aim of environmental problem-solving is to avoid the complex psychological biases inherent in decision-making and to allow the engagement of multiple stakeholders, incorporate all available information, and ensure that we know exactly what we are trying to achieve, before making a decision. In this course we will outline a structured approach to problem-solving and decision-making from an environmental perspective and present tools for structuring and solving complex environmental problems. This course is a foundational course for environmental management and should change the way you approach problem-solving both at work and at home.
Albert Einstein once said that if he had one hour to save the world he would spend 55 minutes defining the problem and 5 minutes finding the solution. Of course, he was a genius.
In ENVM7512 – Environmental Problem Solving, you will learn what Einstein pondered about in those 55 minutes before making the decision. You will learn a structured approach to solving problems and making decisions from an environmental perspective. You will learn how to avoid psychological biases in decision-making; how different stakeholders bring in a multitude of values; how to incorporate the available information, and how to ensure that we know our objectives before making a decision. We will give you tools for structuring and solving complex environmental problems. This course is a foundational course for environmental management and should change the way you approach problem-solving both at work and at home.
This innovative course is delivered through an online learning platform with a mix of video and written content for students to follow each week and solidified through expert-led weekly workshops that include online content summary and practical implementation of learning modules.
External courses are delivered entirely online, and students must participate online for learning and assessment. Note: students may be required to sit exams at a UQ campus or an approved off-campus exam centre. Please refer to the Assessment tab details for information on exam attendance requirements.
Course requirements
Assumed background
No assumed background.
The course will lay a foundation for how to approach environmental problem solving, it will help you think holistically about decision-making (of all forms) and assist you both in your future careers and also with subsequent courses.
Course contact
Course staff
Lecturer
Tutor
Mr Tom Deweerdt
Timetable
The timetable for this course is available on the UQ Public Timetable.
Additional timetable information
The course includes a weekly two-hour practical workshop that is designed to assist you in completing the assessments and is core to the learning experience of the course. We are offering different time slots to accommodate different schedules. Completion of weekly online learning content is essential andﾠattendance of practicals is highly recommended to ensure success in this course.ﾠ
Aims and outcomes
The central aim of this course is to provide students with the essential skills to formulate problems and find solutions to complex environmental issues and to facilitate decision-making for environmental practitioners.
The content of this course will be based on sound theory and practice and will be delivered by world leading researchers in this field as well as practitioners from key environmental organisations.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Appreciate and articulate the complex social, cultural, political, economic and environmental dimensions of environmental issues
LO2.
Identify the key steps in effective environmental problem solving
LO3.
Represent the key dimensions of an environmental issue as measurable objectives
LO4.
Select and apply appropriate tools and methods for mapping the consequences of environmental decisions
LO5.
Select and apply appropriate decision-making tools to inform best practice decisions and incorporate weighting of alternative stakeholder values
LO6.
Demonstrate an understanding of the value of monitoring and evaluation in effective environmental problem solving
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Paper/ Report/ Annotation |
Problem Plan
|
25% |
24/03/2026 2:00 pm |
| Quiz |
Video quiz on biases
|
5% |
2/04/2026 2:00 pm |
| Paper/ Report/ Annotation | Analysing an environmental problem | 25% |
12/05/2026 2:00 pm |
| Examination |
End of Semester Exam
|
45% |
End of Semester Exam Period 6/06/2026 - 20/06/2026 |
A hurdle is an assessment requirement that must be satisfied in order to receive a specific grade for the course. Check the assessment details for more information about hurdle requirements.
Assessment details
Problem Plan
- Team or group-based
- Mode
- Written
- Category
- Paper/ Report/ Annotation
- Weight
- 25%
- Due date
24/03/2026 2:00 pm
- Learning outcomes
- L01, L02, L03
Task description
Groups will be required to present a short document on their environmental problem. This document should contain:
1) Short referenced background to the environmental problem (max 300 words; 20% of total assessment mark, 5 marks total)
2) Elements of the problem statement provided on template provided (20% of total assessment mark - 5 marks total);
3) Objectives hierarchy (60% of total assessment mark - 15 marks total).
The topic used must be one of the two provided topics. The use of an alternative topic will result in a mark of zero.
Important notes:
There is one group assessment in this course. Groups should be between 3 and 4 Students. Assessment 1 and 3 must be done on the same topic. It is expected that all group members satisfactorily contribute to this assignment. Please note that if you are having issues with the group assessment we expect you to make all reasonable efforts to resolve them and to engage effectively as an integrated team (as in a real consulting environment). If you need advice we encourage you to talk with the course staff or coordinator as soon as possible to help resolve any concerns.
Use of Artificial Intelligence (AI) and Machine Translation (MT)
Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT in completing this assessment task. Students must clearly reference any use of AI or MT in each instance. A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Group Report (to be submitted by one group member on behalf of the rest of the group). Instructions for submission will be provided closer to the due date.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 28 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.
You are required to submit assessable items on time. If you fail to meet the submission deadline for any assessment item, then 10% of the maximum possible mark for the assessment item (assessment ‘marked from’ value) will be deducted as a late penalty for every day (or part day) late after the due date. For example, if you submit your assignment 1 hour late, you will be penalised 10%; if your assignment is 24.5 hours late, you will be penalised 20% (because it is late by one 24-hour period plus part of another 24-hour period).
Video quiz on biases
- Online
- Mode
- Written
- Category
- Quiz
- Weight
- 5%
- Due date
2/04/2026 2:00 pm
- Learning outcomes
- L01
Task description
Watch a video in your own time. At five times in the video, we will ask you a question about the content of the video. You will need to identify the cognitive biases, from a drop down list, that the presenter is discussing in an online quiz.
There will be 5 places in the video (given by the time on the video) when you are expected to name the cognitive bias being referred to.
Each of the five biases is worth 1 marks for a total of 5 marks.
Use of Artificial Intelligence (AI) and Machine Translation (MT)
Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT in completing this assessment task. Students must clearly reference any use of AI or MT in each instance. A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
This is to be completed in an online quiz. Details will be provided via blackboard the week before the assessment.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.
Late submission
Exams submitted after the end of the submission time will incur a late penalty.
Digital exams generally provide planning time (10 minutes) and working time (e.g. 90 minutes). Following your working time, you have an extra 15 minutes to submit your exam. If you submit your exam after the 15 minute submission time, you will be penalised.
For submissions:
- less than 5 minutes late: 5% penalty
- between 5 minutes to less than 15 minutes late: 20% penalty
- more than 15 minutes late: 100% penalty.
If you experience technical difficulties and are unable to submit your exam on time, you may apply for exemption of the late penalty.
Analysing an environmental problem
- Mode
- Written
- Category
- Paper/ Report/ Annotation
- Weight
- 25%
- Due date
12/05/2026 2:00 pm
- Learning outcomes
- L01, L04, L05
Task description
Students are to work as individuals to write a report of approximately 800 words (including illustrations, figures, and references). This report should present an analysis of the decision problem from the perspective of at least two stakeholder groups based on the consequence table provided, further it will articulate recommendations and conclusions based on this analysis. The same case study will be used for this report (Assessment 3) as used in the group assessment (Assessment 1). Using an alternative case study will result in a mark of zero.
Suggested structure for project report
- Title and case study
- Provided consequence table
- Description of at least two stakeholders and how they have been included in analysis (~200 words)
- Decision analysis (with the application of appropriate tools) including excel spreadsheet of calculations (as separate file) and figures of results (150 words in figure legends)
- Discussion of results (~300 words)
- Recommendations (~150 words)
- Cited Literature (if any)
Use of Artificial Intelligence (AI) and Machine Translation (MT)
Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT in completing this assessment task. Students must clearly reference any use of AI or MT in each instance. A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Each student is required to submit a report. Instructions for submission will be provided closer to the due date.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 28 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.
You are required to submit assessable items on time. If you fail to meet the submission deadline for any assessment item, then 10% of the maximum possible mark for the assessment item (assessment ‘marked from’ value) will be deducted as a late penalty for every day (or part day) late after the due date. For example, if you submit your assignment 1 hour late, you will be penalised 10%; if your assignment is 24.5 hours late, you will be penalised 20% (because it is late by one 24-hour period plus part of another 24-hour period).
End of Semester Exam
- Hurdle
- Identity Verified
- In-person
- Mode
- Written
- Category
- Examination
- Weight
- 45%
- Due date
End of Semester Exam Period
6/06/2026 - 20/06/2026
- Learning outcomes
- L01, L02, L03, L04, L05, L06
Task description
There will be an exam worth 45% of total marks at the end of semester during the central exam period. The exam will consist of multiple choice, short answer and problem solving based on what we learn through weeks 1 to 12.
This exam requires attendance on campus, or at an approved off-campus exam centre. You must be able to attend one of these venues. Please refer to the Off-Campus exams information page for further information. Please note a digital exam is not available for this assessment.
Use of Artificial Intelligence (AI) and Machine Translation (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.
Hurdle requirements
See Additional Course Grading Information for the hurdle information relating to this assessment item.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 | Description |
|---|---|
| 1 (Low Fail) |
Absence of evidence of achievement of course learning outcomes. Course grade description: Work of a very poor quality showing a very limited understanding of subject matter and a very low level of appreciation of issues covered in lecture and laboratory programs.ﾠ The minimum percentage required for a grade of 1 is: 0% |
| 2 (Fail) |
Minimal evidence of achievement of course learning outcomes. Course grade description: Work of poor quality showing a very limited understanding of subject matter and a low level of appreciation of issues covered in lecture and laboratory programs. The minimum percentage required for a grade of 2 is: 30% |
| 3 (Marginal Fail) |
Demonstrated evidence of developing achievement of course learning outcomes Course grade description: Fail: Falls short of satisfying all basic requirements for a Pass. The minimum percentage required for a grade of 3 is: 45% |
| 4 (Pass) |
Demonstrated evidence of functional achievement of course learning outcomes. Course grade description: Work of fair quality demonstrating a basic understanding of most aspects of subject matter and a modest appreciation of issues covered in lecture and laboratory programs, but with serious deficiencies in some areas, at least good laboratory skills and a sound ability to interpret experimental results. The minimum percentage required for a grade of 4 is: 50% |
| 5 (Credit) |
Demonstrated evidence of proficient achievement of course learning outcomes. Course grade description: Work of a good quality demonstrating a good understanding of most subject matter and a competent level of appreciation of issues covered in lecture and laboratory programs, although possibly with some lapses and inadequacies, at least good laboratory skills and a sound ability to interpret experimental results. The minimum percentage required for a grade of 5 is: 65% |
| 6 (Distinction) |
Demonstrated evidence of advanced achievement of course learning outcomes. Course grade description: Work of a very good quality demonstrating a strong understanding of a wide, but not complete, range of subject matter and a good level of appreciation of issues, although not necessarily of the finer points, covered in lecture and laboratory programs, very good laboratory skills and a very good ability to interpret experimental results. The minimum percentage required for a grade of 6 is: 75% |
| 7 (High Distinction) |
Demonstrated evidence of exceptional achievement of course learning outcomes. Course grade description: Work of exceptional quality showing a deep understanding of a wide range of subject matter and a clear appreciation of issues covered in lecture and laboratory programs, very good laboratory skills and a very good ability to interpret experimental results. The minimum percentage required for a grade of 7 is: 85% |
Additional course grading information
Assessment Hurdle
In order to pass this course, you must meet the following requirements (if you do not meet these requirements, the maximum grade you will receive will be a 3):
You must obtain 50% or more on the End of Semester Exam
Supplementary assessment
Supplementary assessment is available for this course.
Should you fail a course with a grade of 3, you may be eligible for supplementary assessment.
Refer to the link above for information on supplementary assessment and how to apply. Supplementary assessment provides an additional opportunity to demonstrate you have achieved all the required learning outcomes for a course.
If you apply and are granted supplementary assessment, the type of supplementary assessment set will consider which learning outcome(s) have not been met. Supplementary assessment can take any form (such as a written report, oral presentation, examination or other appropriate assessment) and may test specific learning outcomes tailored to the individual student, or all learning outcomes.
To receive a passing grade of 3S4, you must obtain a mark of 50% or more on the supplementary assessment.
Additional assessment information
Applications for Extensions to Assessment Due Dates
Read the information contained in the following links carefully before submitting an application for extension to assessment due date.
For guidance on applying for an extension, information is available here: https://my.uq.edu.au/information-and-services/manage-my-program/exams-and-assessment/applying-assessment-extension
For the policy relating to extensions, information is available here (Part D): https://policies.uq.edu.au/document/view-current.php?id=184
Please note the University's requirements for medical certificates here: https://my.uq.edu.au/information-and-services/manage-my-program/uq-policies-and-rules/requirements-medical-certificates
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
Library resources are available on the UQ Library website.
Additional learning resources information
Course Structure
This innovative course is delivered through an online learning platform with a mix of video and written content for students to follow each week and solidified through expert-led weekly workshops that include online content summary and practical implementation of learning modules.
Each week, classesﾠconsist of a three-hour interactive practical contactﾠ(we offer different time slots - please refer to the time table for optionsﾠin my.UQ).
There will be four differentﾠassessment items. Students will analyse an environmental problem, submitting a group report subsection and an individual final analysis. There is also a video quiz and a final exam.
Attendance and participation in the practicals in strongly encouraged,ﾠthey are a key aspect of the course and will help inform your assignments and build on onlineﾠcontent to help you get the best outcome in the exam.
Please note the weekly online content may change slightly depending on unexpected availability issues or external events. Announcements will be posted on the course Blackboard site if anything changes.
Other recommended readings, such as scientific articles or decision reports will be announced andﾠavailableﾠonline.ﾠ
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) |
Not Timetabled |
Week 1: Introduction and Context Introduction and overview to environmental problem solving Cognitive biases Decision types and processes The components of a decision problem The decision context and how to write a problem statement Workshop: Practise identifying key elements in a decision problem and writing a problem statement. Learning outcomes: L01, L02 |
Week 2 (02 Mar - 08 Mar) |
Not Timetabled |
Week 2: Values and objectives The role of values in decision making Types of objectives Targets and how they should be used Tools for capturing and clarifying objectives and engaging with stakeholders Workshop: Practise constructing means-ends diagrams and objectives hierarchies using case studies Learning outcomes: L01, L02 |
Week 3 (09 Mar - 15 Mar) |
Not Timetabled |
Week 3: Performance measures What makes a good performance measure for objectives Types of performance measures Understanding the pros and cons of scales Tools for identifying performance measures Workshop: Identify performance measures for objectives. Learn to construct influence diagrams from a case study. Learning outcomes: L03 |
Week 4 (16 Mar - 22 Mar) |
Not Timetabled |
Week 4: Alternatives Revisit means objectives and more on biases Strategy development as a creative process Developing alternatives ﾖ strategy tables and menu boards The use of influence diagrams Workshop: Identify objectives and drivers for a problem, and brainstorm actions to help achieve objectives. Learn to use a menu board to build a strategy table for a case study. Learning outcomes: L02 |
Week 5 (23 Mar - 29 Mar) |
Not Timetabled |
Week 5: Consequences Why it is important to link objectives to actions and approaches for doing this Consequence tables as a tool for making these connections and summarizing information The role of models Using a consequence table to simplify a problem Workshop: Practise analysing and reducing consequence tables (finding dominated alternatives, irrelevant objectives, and even swaps). Assessment due: Assessment 1 - Problem Plan (problem background, context components, objectives hierarchy, and group work participation) - see "Assessment" for more details. DUE 2pm Monday 24/03/2025 Learning outcomes: L02, L04 |
Week 6 (30 Mar - 05 Apr) |
Not Timetabled |
Week 6: Data and Experts Types of data Expert judgement and cognitive biases Expert elicitation Workshop: Practise writing expert elicitation questions and learn how an expert elicitation works. Assessment Due: Assessment 2 - Online Video Quiz on biases DUE 2pm Thursday 3/04/2025 Learning outcomes: L01, L02, L04, L05 |
Mid-sem break (06 Apr - 12 Apr) |
No student involvement (Breaks, information) |
Mid-semester break |
Week 7 (13 Apr - 19 Apr) |
Not Timetabled |
Week 7: Solutions - Multi-objective Tools for finding solutions to environmental problems, which often have multiple objectives Learn to apply multi-criteria decision analysis (MCDA) for environmental problems The importance of trade-offs and methods for understanding trade-offs and weighting outcomes Workshop: Construct and fill in a swing-weighting table in Excel. Conduct a MCDA and learn to display and interpret results. Discuss how differences in subjective values affect decision making. Learning outcomes: L03, L04 |
Week 8 (20 Apr - 26 Apr) |
Not Timetabled |
Week 8: Systems thinking ALL WORKSHOP CONTENT WILL BE ONLINE THIS WEEK - NO ACTIVITIES WILL BE HELD ON CAMPUS The importance of models, what types exist and what their purposes are Systems thinking and why is it important The relationship between system structure and system behaviour How to model system behaviour Workshop (Self Directed - Online Only): Build a simple system dynamics population model to simulate the stocks, flows and feedback loops controlling population behaviour over time. Learning outcomes: L02, L05 |
Week 9 (27 Apr - 03 May) |
Not Timetabled |
Week 9: Solutions - ROI and Cost-effectiveness The concept of return on investment (ROI) Cost-benefit versus cost-effectiveness analysis Prioritizing environmental actions given a set of constraints Workshop: Review cost-effectiveness concepts. Construct a cost-effectiveness analysis for a case study, in Excel. Learning outcomes: L05 |
Week 10 (04 May - 10 May) |
Not Timetabled |
Week 10: Solutions - Single-objective DUE TO THE PUBLIC HOLIDAY ON MONDAY (5th May) NO WORKSHOP CONTENT WILL BE DELIVERED THIS WEEK. Using single-objective tools to solve environmental problems Different types of single-objective tools Understand how single-objective tools are used in harvest management and stochastic settings. Learning outcomes: L02, L05 |
Week 11 (11 May - 17 May) |
Not Timetabled |
Week 11: Risk and uncertainty Understanding risk and uncertainty, what they are and how they differ. Understanding risk aversion and risk seeking decision-makers What are approaches for dealing with risk and uncertainty in decision-making, including risk assessment, maximin and minimax, and scenario analysis. Workshop: Calculate risk scores and understand the consequences of different risk attitudes. Assessment Due: Assessment 3 - Problem Analysis DUE 2pm Tuesday 13/05/2025 Learning outcomes: L05 |
Week 12 (18 May - 24 May) |
Not Timetabled |
Week 12: Monitoring and VOI Understand the different reasons to monitor and those that relate to decision-making Understand the economic theory of value of information and how to implement expected value of information analysis Workshop: Implement an expected value of information analysis. Discuss the outcomes and recommendations for monitoring. Learning outcomes: L02, L06 |
Week 13 (25 May - 31 May) |
Not Timetabled |
Week 13: Course recap Summary of weekly online content and key ideas Opportunity for Q&A during regular prac session Learning outcomes: L01, L03, L04, L05, L06 |
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.