Course overview
- Study period
- Semester 1, 2025 (24/02/2025 - 21/06/2025)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Psychology School
Every day we make decisions by relying on our personal theories about how things are supposed to work. But our reliance on these rules is paid for at the cost of accuracy. We tend to see what we expect to see and believe what we're told. One goal of this course is to figure out how everyday decision making can be improved.
How do people make choices—sometimes brilliantly, sometimes disastrously? In PSYC3052, you will explore the science behind human judgement and decision making, from the role of cognitive shortcuts and social influence to the emerging power of artificial intelligence. Through 13 classes, you will examine the foundations of heuristics and biases, dive into metacognition and expertise, and discover how decision-making processes adapt—or fail—under uncertainty. You will also learn to harness generative AI tools for research, discussion, and study, while carefully evaluating both their potential and pitfalls.
Throughout the semester, you will master strategies for identifying hidden influences on thinking, from everyday choices in personal finance to high-stakes decisions in medicine, law, and education. You will practice distinguishing credible information from misinformation, understand how group dynamics and nudging affect collective outcomes, and reflect on the ethical implications of shaping others’ choices. Engaging with real-world case studies and completing AI-supported exercises, you will develop evidence-based thinking skills that will help you navigate complex information landscapes and collaborate effectively with intelligent systems.
Frequent in-class quizzes and exercises will solidify your grasp of core concepts, while integrative projects and a final examination encourage you to apply cognitive science principles to contemporary challenges. By the end of this course, you will have a thorough understanding of how—and why—humans think, decide, and occasionally err, and you will be equipped to make more informed and rational decisions in an increasingly AI-infused world.
Course requirements
Recommended prerequisites
We recommend completing the following courses before enrolling in this one:
PSYC1040 + PSYC2010 + PSYC2050
Course contact
Course staff
Lecturer
Timetable
The timetable for this course is available on the UQ Public Timetable.
Aims and outcomes
To develop an in-depth and integrative understanding of how approaching judgment and decision making from a psychological perspective improves our understanding of human behaviour.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Gain a thorough understanding of the fundamental concepts and theories in judgement and decision making, including biases and heuristics, dual-process theories, non-human feats of intelligence, reasoning and problem solving, insight and metacognition, and decision making under uncertainty.
LO2.
Analyse and apply these theories to real-world situations (e.g., high-stakes decision making in medicine, law, or education), using generative AI tools to enhance decision-making abilities and critically evaluate decision-making processes.
LO3.
Strengthen the ability to identify and mitigate common biases and heuristics, building strategies through exposure to weekly AI-based explorations that foster the development of effective decision-making approaches.
LO4.
Evaluate and analyse decision-making strategies, including group decision making and nudging, and understand the impact of brain training, transfer, and mental representations on expertise, applying the critical thinking and feedback skills honed during AI-related tasks.
LO5.
Communicate understanding of judgement and decision making effectively—both in writing and discussion—while persuading others to adopt evidence-based approaches to decision making, drawing on the communication skills developed throughout the course’s activities.
LO6.
Understand and critically assess research methods used to study judgement and decision making in laboratory and real-world settings, evaluating the quality, rigour, and applicability of existing studies and data.
LO7.
Collect, synthesise, and present information from multiple sources clearly and objectively, demonstrating effective academic writing and documentation skills in the process.
LO8.
Formulate and defend a position on debates surrounding cognitive processes and the methods used to investigate them, applying advanced reasoning and persuasive communication skills cultivated through the course content and assessments.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Quiz |
Weekly In-Class Quizzes
|
50% |
6/03/2025 - 29/05/2025 |
| Reflection |
Weekly AI Explorations
|
20% |
6/03/2025 - 29/05/2025
The Weekly AI Exploration exercises are due before class each Tuesday at 5pm—this gives us time to review submissions before our class on Thursday. |
| Examination |
Final Examination
|
30% |
End of Semester Exam Period 7/06/2025 - 21/06/2025 |
Assessment details
Weekly In-Class Quizzes
- In-person
- Mode
- Written
- Category
- Quiz
- Weight
- 50%
- Due date
6/03/2025 - 29/05/2025
- Other conditions
- Time limited.
Task description
Each week in class, you’ll complete a pencil-and-paper quiz using traditional bubble sheets. These quizzes build on the assigned readings and activities—such as scientific papers, book chapters, videos, and live demonstrations—and help solidify your grasp of the material. Research shows that frequent testing promotes better long-term retention than studying alone (Roediger et al., 2011), so you’ll have regular opportunities to recall and apply key concepts.
There are 12 quizzes in total, each worth 5%. Only your top 10 scores will be counted, making up 50% of your overall grade. You can expect to see your quiz results on Blackboard within a week or two; if you have any questions or concerns about your marks, feel free to contact the tutors.
No AI Allowed
These quizzes measure your understanding of the material without assistance from artificial intelligence. Using AI tools or any other form of unauthorised help may be treated as academic misconduct under the Student Code of Conduct.
Submission guidelines
Deferral or extension
You cannot defer or apply for an extension for this assessment.
Each week, you'll complete an in-class quiz worth 5% of your final grade. To accommodate unexpected circumstances like illness or emergencies, only your top 10 out of 12 quiz scores will count toward your final grade. This built-in flexibility eliminates the need for make-up quizzes while ensuring fairness and academic integrity. Missing one or two quizzes results in these zeros being automatically dropped as your lowest scores. For three documented absences, your quiz component will be reweighted across your best nine scores (5.56% each). Students who miss four or more quizzes due to documented serious circumstances will have their situation reviewed individually by the course coordinator.
Weekly AI Explorations
- Online
- Mode
- Written
- Category
- Reflection
- Weight
- 20%
- Due date
6/03/2025 - 29/05/2025
The Weekly AI Exploration exercises are due before class each Tuesday at 5pm—this gives us time to review submissions before our class on Thursday.
Task description
Each week, you’ll be assigned a specific short exercise using a generative AI tool, directly tied to that week’s content. You’ll produce an AI-generated output (earning 1%) and then write a brief reflection (another 1%) describing what you tried, what you learned, and whether the AI proved helpful or misleading. Note that you must submit the AI output to earn marks for the reflection. Over the semester, there are 12 such tasks; your best 10 count toward a total of 20%.
Allowed Generative AI
In line with UQ’s goal of preparing you for responsible AI use, you may choose any appropriate generative AI tool to complete each exercise. While we’ll define the weekly tasks in detail, potential examples range from critiquing a cognitive bias or creating an infographic on dual-process thinking to drafting a mini research proposal or outlining a high-stakes crisis response scenario.
Rationale
By pairing hands-on AI practice with thoughtful reflection, you’ll sharpen your critical thinking about the capabilities and limits of AI—skills you can carry forward into real-world decision-making contexts.
Submission guidelines
Deferral or extension
You cannot defer or apply for an extension for this assessment.
Each week, you'll complete a structured exercise using generative AI, directly tied to that week's content. Each task consists of an AI-generated output (1%) and your brief reflection (1%) analysing what you tried, learned, and whether the AI proved helpful or misleading. To accommodate unexpected circumstances, only your top 10 out of 12 task scores will count toward your final grade. This built-in flexibility eliminates the need for make-up tasks while ensuring fairness and academic integrity. Missing one or two tasks results in these zeros being automatically dropped as your lowest scores. For three documented absences, your task component will be reweighted across your best nine scores. Students who miss four or more tasks due to documented serious circumstances will have their situation reviewed individually by the course coordinator. You must submit the AI output to receive marks for the reflection, as this hands-on practice develops critical thinking about AI's capabilities and limitations.
Final Examination
- In-person
- Mode
- Written
- Category
- Examination
- Weight
- 30%
- Due date
End of Semester Exam Period
7/06/2025 - 21/06/2025
- Other conditions
- Time limited.
Exam details
| Planning time | 10 minutes |
|---|---|
| Duration | 120 minutes |
| Calculator options | No calculators permitted |
| 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 - 23.99 |
Absence of evidence of achievement of course learning outcomes. |
| 2 (Fail) | 24 - 46.99 |
Minimal evidence of achievement of course learning outcomes. |
| 3 (Marginal Fail) | 47 - 49.99 |
Demonstrated evidence of developing achievement of course learning outcomes |
| 4 (Pass) | 50 - 64.99 |
Demonstrated evidence of functional achievement of course learning outcomes. |
| 5 (Credit) | 65 - 74.99 |
Demonstrated evidence of proficient achievement of course learning outcomes. |
| 6 (Distinction) | 75 - 84.99 |
Demonstrated evidence of advanced achievement of course learning outcomes. |
| 7 (High Distinction) | 85 - 100 |
Demonstrated evidence of exceptional achievement of course learning outcomes. |
Supplementary assessment
Supplementary assessment is available for this course.
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
Please remain mindful of the importance of the library resources for the academic work of others, and report any damage or missing items to Library staff as soon as possible.
Access to a high speed internet connection is highly recommended for downloading of materials and to perform literature searches.
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
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| Learning period | Activity type | Topic |
|---|---|---|
Week 1 (24 Feb - 02 Mar) |
Workshop |
Class 1: Making AI Your Study Partner This first class shows you how to use generative AI tools (such as ChatGPT) effectively to succeed in your weekly assignments and quizzes. You will learn strategies for organising ideas, summarising key readings, generating self-test questions, and receiving immediate feedback on practice writing. By establishing good practices early, you'll be better equipped to engage deeply with Judgement and Decision Making concepts in the weeks to come. |
Week 2 (03 Mar - 09 Mar) |
Workshop |
Class 2: Foundations of Judgement and Decision Making Provides a high-level overview of the key questions and methods in cognitive science that underpin JDM research. Covers foundational theories, dual-process frameworks (System 1 vs. System 2), and introduces the major figures and classic studies in JDM (e.g., Tversky and Kahneman). Emphasis is placed on robust, reproducible findings. |
Week 3 (10 Mar - 16 Mar) |
Workshop |
Class 3: Heuristics, Biases, and Cognitive Shortcuts Explores the core heuristics (availability, representativeness, anchoring) and the biases that arise from them. Students learn how these mental shortcuts can be adaptive but also lead to systematic errors. Contemporary and historical research illustrates how biases operate in everyday judgement. |
Week 4 (17 Mar - 23 Mar) |
Workshop |
Class 4: Thinking, Reasoning, and Problem-Solving Dives deeper into the cognitive processes that govern how we reason and solve problems, from mental models to mental logic. Also examines how AI-driven approaches can shed new light on problem-solving strategies. Students compare human and AI approaches to solving the same problems, refining their own reasoning in the process. |
Week 5 (24 Mar - 30 Mar) |
Workshop |
Class 5: Metacognition, Insight, and the Nature of Expertise Focuses on how we monitor our own thought processes (metacognition) and how moments of insight arise. Examines mental representations, chunking, and the role of deliberate practice in developing expertise. Students consider how experts differ from novices in how they perceive and solve problems, and how generative AI might augment or mislead expert judgement. |
Week 6 (31 Mar - 06 Apr) |
Workshop |
Class 6: Decision Making Under Uncertainty Addresses how humans assess probabilities, manage risks, and navigate ambiguity. Reviews classical models (e.g., Subjective Expected Utility) and alternative approaches (e.g., bounded rationality, prospect theory). Interactive activities demonstrate how AI tools can assist in risk analysis and probability estimations—while underscoring the need for critical oversight. |
Week 7 (07 Apr - 13 Apr) |
Workshop |
Class 7: Non-Human Intelligence and Comparative Cognition Investigates non-human feats of intelligence in animals and AI systems, asking what we can learn about judgement and decision making from these comparative perspectives. Explores how different forms of cognition solve complex tasks, and what that implies about the boundaries and uniqueness of human thinking. |
Week 8 (14 Apr - 20 Apr) |
Workshop |
Class 8: Group Decision Making and Social Influences Examines how decisions change in group settings, covering phenomena like groupthink, polarisation, and social influence. Students learn about consensus-building, the "wisdom of crowds," and how AI-driven platforms can amplify or reduce biases in group contexts. Emphasis is placed on practical strategies to avoid common group pitfalls and harness positive collaboration. |
Mid-sem break (21 Apr - 27 Apr) |
Workshop |
Mid-semester Break |
Week 9 (28 Apr - 04 May) |
Workshop |
Class 9: Nudging, Choice Architecture, and Behaviour Change Dives into how subtle changes in context—"choice architecture"—can influence decisions. Reviews the evidence base for nudging and other behaviour-change interventions. Students discuss ethical implications and practise using AI to design or evaluate real-life nudges in areas such as health, education, or environmental policy. |
Week 10 (05 May - 11 May) |
Workshop |
Class 10: Brain Training, Transfer, and the Limits of Expertise Investigates claims around brain training, deliberate practice, and cognitive transfer. Explores how memory, attention, and mental representations develop with training, and whether expertise in one domain can transfer to another. Focuses on evaluating the rigour and reproducibility of studies, encouraging students to critically assess sensational claims. |
Week 11 (12 May - 18 May) |
Workshop |
Class 11: Fact vs. Fiction: Misinformation and Cognitive Resilience Focuses on cognitive strategies to detect and resist misinformation in everyday life. Discusses confirmation bias, motivated reasoning, and the distinction between evidence-based claims and pseudoscience. Demonstrations with AI-generated content highlight how quickly misinformation can spread—and the vigilance needed to maintain critical thinking. |
Week 12 (19 May - 25 May) |
Workshop |
Class 12: Synthesis and Future Directions in Judgement and Decision Making Integrates the concepts covered throughout the course, with a look at emerging areas such as AI-assisted decision making in real-world contexts. Students consolidate their understanding of core JDM theories, reflecting on how these can be applied beyond the classroom. This class also examines ongoing challenges in the field, including reproducibility and open science initiatives. |
Week 13 (26 May - 01 Jun) |
Workshop |
Class 13: High-Stakes Decision Making Concludes the course by exploring how JDM research can inform decisions with significant real-world consequences—from medical diagnostics and legal judgements to large-scale corporate or governmental strategies. Students synthesise course concepts to evaluate risk management, mitigating cognitive biases, and adapting to pressure in critical scenarios. This final class encourages them to translate their newly honed insights into high-stakes professional and personal settings. |
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 - Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.
School guidelines
Your school has additional guidelines you'll need to follow for this course: