Outline

Overview

We like to believe that decision making involves simply weighing up the pros and cons of the different options before selecting the best one, so when people fail to do this (as they often do) they are viewed as irrational. However this viewpoint has been shown to be inaccurate even for important decisions. This unit will provide an introduction to how short-cuts, biases and emotion are integral to human decision making. These factors are often systematic, so we are expectedly irrational. You will first learn to recognise the common heuristics (short-cuts) and biases that have been identified by evaluating existing research and through demonstrations. From this foundation you will explore decision making more deeply and develop an understanding of the broader frameworks for comprehending it. You will then focus on the implication this has for improving your own decision making and how we can better present information and options to improve other people's decision making. From a public policy point of view these insights can be used to help nudge people towards beneficial choices, though advertisers also capitalise on these biases to influence human behaviour.

Unit details and rules

Academic unit	Psychology Academic Operations
Credit points	2
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Bruce Burns, bruce.burns@sydney.edu.au

Assessment

The census date for this unit availability is 5 September 2025

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Out-of-class quiz	Module quizzes A mastery quiz at the end of each online Modules 1-12.	40%	Multiple weeks Due date: 05 Oct 2025 at 23:59 Closing date: 05 Oct 2025	Twelve quizzes of 3-5 questions each	AI allowed
Outcomes assessed:
Out-of-class quiz	Module 1 Quiz #earlyfeedbacktask	0%	Week 01	3-5 questions	AI allowed
Outcomes assessed:
Written work	Short-release Assignment Open book written assignment with details to be provided up to 24 hours before deadline.	60%	Week 05 Due date: 26 Sep 2025 at 23:59 Closing date: 26 Sep 2025	Approximately 2 hours	AI allowed
Outcomes assessed:
= hurdle task ? = early feedback task ?

Early feedback task

This unit includes an early feedback task, designed to give you feedback prior to the census date for this unit. Details are provided in the Canvas site and your result will be recorded in your Marks page. It is important that you actively engage with this task so that the University can support you to be successful in this unit.

Assessment summary

Below are brief assessment details. Further information will be found on the unit’s Canvas site when they are available.

Short-release Assignment: To fit with the pass/fail grading of this unit, the short-release assignment will be a set of short tasks that you should be able complete if you have obtained threshold knowledge of the material.
- This will be an open-book assignment and you will be given at least 24 hours to complete it, but I do not expect it to take more than two hours to complete it.
- The hurdle requirement is satisfactory completion of a majority of the tasks presented.
Module quizzes: These are at end of Modules 1-12. You need to obtain at least 60% on each quiz in order to proceed to the next module, but they can be done multiple times.
- Obtaining at least 60% on all quizzes is a hurdle requriement for passing the unit.

Assessment criteria

Result name

Mark range

Description

Pass

50 - 100

At PS level, a student demonstrates proficiency in the unit material. A ‘Pass’ reflects satisfactory achievement and is awarded to a student who has threshold knowledge.

Fail

0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Ongoing	Module 1. Thinking about decision making	Online class (1.5 hr)
	Module 2. Heuristics	Online class (1.5 hr)
	Module 3. Biases	Online class (1.5 hr)
	Module 4. Reasoning biases	Online class (1.5 hr)
	Module 5. Decision making and time	Online class (1.5 hr)
	Module 6. Prediction	Online class (1.5 hr)
	Module 7. Behavioral economics	Online class (1.5 hr)
	Module 8. Neuroscience: The brain, emotions, and decision making	Online class (1.5 hr)
	Module 9. Thinking: One system or two?	Online class (1.5 hr)
	Module 10. Data and decision making	Online class (1.5 hr)
	Module 11. Improving decision making	Online class (1.5 hr)
	Module 12. Improving our own decision making	Online class (1.5 hr)
Week 02	Tutorial 1. Decision making issues (During the week starting Monday 1/9/25)	Online class (1 hr)
Week 03	Tutorial 2. Tools for decision making (During the week starting Monday 8/9/25)	Online class (1 hr)
Week 04	Tutorial 3. Using decision trees (During the week starting 15/9/25)	Online class (1 hr)

Attendance and class requirements

Attendance is recorded at all tutorials and it is highly recommended you attend all timetabled activities. You will increase your risk of failing this unit if you do not attend more than 80% of timetabled activities.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 2 credit point unit, this equates to roughly 40-50 hours of student effort in total.

Required readings

There will be reading for each module and they will be listed as part of the module descriptions. All readings will be available from the library.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. reflect upon your own decision making.
LO2. describe and identify the major heuristics and biases that affect people's decision making
LO3. understand the implications these heuristics and biases have for how to present information to people making decisions
LO4. describe and explain the frameworks researchers have used to try to understand these heuristics and biases.
LO5. apply critical thinking to understanding how to improve the decision making of ourselves and others
LO6. be able to communicate competently about decision making and the implications of the evidence regarding heuristic and biases.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

Based on the feedback collected on module components we have adjusted the content of the modules.

Additional information

If you have an enquiry about this unit of study and you cannot find the answer to your question in this document, please contact the Psychology Education Support team: psychology.education@sydney.edu.au
You are strongly advised to log on to the course’s Canvas site as soon as possible. This contains more information and is also where you will complete and submit assessments. The Canvas portal is: https://canvas.sydney.edu.au/
Check your University email on a regular basis, or forward your University email to an address you do check regularly. All electronic University communication will be sent to your University email address. Always use your University email when contacting staff in this course. Find a login for your email, Canvas, Sydney Student (Enrolment) and Timetable and much more here: https://sydney.edu.au/students/
Data collection. Note that your participation in this unit of study permits us to use your learning analytics to improve your experience of learning.

Science student portal

Work, health and safety

We are governed by the Work Health and Safety Act 2011, Work Health and Safety Regulation 2011 and Codes of Practice. Penalties for non-compliance have increased. Everyone has a responsibility for health and safety at work. The University’s Work Health and Safety policy explains the responsibilities and expectations of workers and others, and the procedures for managing WHS risks associated with University activities.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Early feedback task

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links

OLET1644: How We Make Decisions

Intensive August - September, 2025 [Online] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Early feedback task

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links