Outline

Overview

This unit covers advanced topics in project management with an emphasis on contemporary issues in the delivery of complex Information Systems solutions for businesses. The topics include alternative project management methodologies and techniques, the human and organisational aspects of project management, the importance of project governance, the changing nature of project management in the digital era, as well as the evolving role of the project manager in the global business environment.

Unit details and rules

Academic unit	Business Information Systems
Credit points	6
Prerequisites ?	Completion of 48 credit points
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	INFS1000 and INFS2040
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Chenxu Zheng, chenxu.zheng@sydney.edu.au

Assessment

The census date for this unit availability is 1 September 2025

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Written exam ?	Final Exam Final exam	35%	Formal exam period	2 hours	AI prohibited
Outcomes assessed:
Contribution	Participation and Attendance In-class participation and attendance	5%	Ongoing	N/A	AI allowed
Outcomes assessed:
Practical skill	Individual assignment In parallel to the group assignment, there will be individual tasks (Weekly Homework?)	20%	Week 12	Series of individual tasks	AI allowed
Outcomes assessed:
Written work	Group Project Proposal Written report	25%	Week 13 Due date: 07 Nov 2025 at 23:59 Closing date: 17 Nov 2025	3000 words	AI allowed
Outcomes assessed:
Presentation	Group Project Proposal Written report	10%	Week 13	-	AI allowed
Outcomes assessed:
Evaluation	In-group peer review In-group peer review	5%	Week 13	N/A	AI allowed
Outcomes assessed:
= group assignment ?

Assessment summary

The assessment item requires students to work within their project groups to analyse and provide recommendations for resolving an assigned problem. The problem will be developed by a ‘business organisation’ that will serve as the project sponsor.
The deliverables of the project include
- In-class Attendance and Participation (5%)
- Group Project Proposal (40%) consisting of a presentation (10%), written report (25%) and in-class peer review (5%)
- Individual Assignment (20%) consisting of a series of individual tasks
- Final Exam (35%)

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100	Awarded when you demonstrate the learning outcomes for the unit at an exceptional standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Distinction	75 - 84	Awarded when you demonstrate the learning outcomes for the unit at a very high standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Credit	65 - 74	Awarded when you demonstrate the learning outcomes for the unit at a good standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Pass	50 - 64	Awarded when you demonstrate the learning outcomes for the unit at an acceptable standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see sydney.edu.au/students/guide-to-grades.

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
Week 01	Introduction and Unit Overview	Lecture (3 hr)
Week 02	The Agile Environment	Lecture (3 hr)
Week 03	Discovery - Immersion in Customer Experience	Lecture (3 hr)
Week 04	Defining the Problem - Context, Cause and Effect and Root Causes	Lecture (3 hr)
Week 05	Generate Ideas - Explore Possible Solutions	Lecture (3 hr)
Week 06	Build Prototypes - Mock-up Potential Solutions	Lecture (3 hr)
Week 07	Test Prototypes - Validate and Iterate	Lecture (3 hr)
Week 08	Design for Humans - How Humans Experience Change	Lecture (3 hr)
Week 09	Agile Principles in Action - Simplicity and Continuous Delivery	Lecture (3 hr)
Week 10	Design Lab 1 - Finalise Solution Design	Lecture (3 hr)
Week 11	Design Lab 2 - Finalise Solution-Human Ecosystem	Lecture (3 hr)
Week 12	Proposal Pitch	Lecture (3 hr)
Week 13	Finalise Group Proposal	Lecture (3 hr)

Attendance and class requirements

Active attendance and in-class participation is expected in this unit.

Typically, for a 6-credit point unit, you are expected to commit about 120-150 hours of effort in total over a full 13-week semester. Consider carefully your overall study workload and other commitments such as part-time or full-time work before you register for this unit.

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 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

Recommended Texts.

The Agile Practice Guide by Project Management Institute
The UX Book 2 by Rex Hartson & Pardha Pyla.

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. apply and relate information systems theories and concepts in the context of an actual business organisation
LO2. analyse open-ended business scenarios and evaluate the implications of information systems decisions
LO3. apply techniques for organisational and business process analysis to resolve an actual business problem
LO4. communicate in a professional and confident manner, both orally and in writing, with actual business professionals
LO5. apply team management concepts and theories to effectively work in, and manage, cross-functional teams
LO6. analyse and reflect critically on the ethical and social implications of information systems.

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.

Adjustments have been made to align the content with the 12 Principles of Agile with a focus on delivering continuous value in an Agile implementation environment.

Additional information

More information can be found on Canvas.

Business School Policies

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

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

Disclaimer

On this page

Useful links

INFS3080: Implementing Agile Design

Semester 2, 2025 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

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

Disclaimer

On this page

Useful links