INFS3600: Semester 1, 2025

Overview

This capstone unit bridges the gap between theory and practice by integrating knowledge and consolidating key skills developed across the Business Information Systems major. It aims to provide students with practical experience in identifying, analysing, and solving contemporary business problems. Much of this unit is dedicated to a problem-solving, experiential approach to learning. Students ensure their career-readiness by demonstrating their ability to apply concepts, theories, frameworks, methodologies, and skills to authentic problems and challenges faced in the field of information systems.

Unit details and rules

Academic unit	Business Information Systems
Credit points	6
Prerequisites ?	Students commencing from 2018: completion of at least 112 credit points including (INFS1000 or INFO1000 or INFO1003 or INFO1903) and INFS1020. Pre-2018 continuing students: completion of at least 112 credit points including (INFS1000 or INFO1000 or INFO1003 or INFO1903) and INFS2001 and INFS2020
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	All other requirements for the major or program associated with this capstone must be completed prior to or concurrently with (if enrolment rules permit) this unit of study. Capstones must be completed at the University of Sydney Business School only
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Raffaele Ciriello, raffaele.ciriello@sydney.edu.au
Lecturer(s)	Raffaele Ciriello, raffaele.ciriello@sydney.edu.au

Assessment

The census date for this unit availability is 31 March 2025

Details
Criteria

Type	Description	Weight	Due	Length
Assignment	Individual progress report (multiple) Written report - due dates vary based on student allocation	30%	Multiple weeks Closing date: 20 Jun 2025	1500 words + appendix
Outcomes assessed:
Assignment	Generative AI Strategy Plan and critically reflect on using GenAI and how it affects learning.	5%	Week 03 Due date: 12 Mar 2025 at 23:59	600 words
Outcomes assessed:
Assignment	Group assignment Written report	35%	Week 13 Due date: 28 May 2025 at 23:59 Closing date: 20 Jun 2025	6000 words
Outcomes assessed:
Presentation	Group project presentation In-class presentation of group work	5%	Week 13 Due date: 26 May 2025 at 12:00 Closing date: 26 May 2025	15 minutes (10mins presentation + Q&A)
Outcomes assessed:
Assignment	Reflective Journal Individual, continuous, reflective learning journal, stimulated by prompts.	25%	Week 13 Due date: 30 May 2025 at 23:59 Closing date: 20 Jun 2025	1500 words
Outcomes assessed:
= group assignment ? = AI allowed ? = early feedback task ?

Assessment summary

Individual assignment: This assignment is in the form of an individual progress report that corresponds to a specific section of the group project. The content of this report will vary depending on the student's designated role within the project team. The report comprises 1500 (± 10%) words and associated discussions during the group consultation sessions.
Group assignment: This assessment item requires students to work within their project groups to analyse and provide recommendations for resolving a business problem of an actual client. Each project group will be expected to look for and acquire their own client, and design a technology-enabled solution that will improve a substantive business process of the client. The deliverables of the project include a 15 minute presentation and a project report of 6000 (± 10%) words.
Reflective journal: Individual, continuous, reflective journal about the student’s authentic learning experience gleaned from the group project and the in-class activities. The student will draft the reflective journal continuously in Canvas and the teaching team will ask them 4-5 ‘provocative’ questions to prompt their critical reflection throughout the semester. The final deliverable is a written reflective journal of 1500 words (± 10%).
Generative AI Strategy: By developing a clear strategy for using GenAI tools in assignment work, students will enhance their ability to leverage GenAI for tasks such as identifying literature, structuring ideas, refining text, and fact-checking while ensuring ethical and effective practices. The goal is not just to ensure academic integrity but also to reflect on how GenAI tools shape analytical and critical thinking skills. The deliverable is a 600 word (± 10%) document.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy (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) and automated writing tools

Except for supervised exams or in-semester tests, you may use generative AI and automated writing tools in assessments unless expressly prohibited by your unit coordinator.

For exams and in-semester tests, the use of AI and automated writing tools is not allowed unless expressly permitted in the assessment instructions.

The icons in the assessment table above indicate whether AI is allowed – whether full AI, or only some AI (the latter is referred to as “AI restricted”). If no icon is shown, AI use is not permitted at all for the task. Refer to Canvas for full instructions on assessment tasks for this unit.

Your final submission must be your own, original work. You must acknowledge any use of automated writing tools or generative AI, and any material generated that you include in your final submission must be properly referenced. You may be required to submit generative AI inputs and outputs that you used during your assessment process, or drafts of your original work. Inappropriate use of generative AI is considered a breach of the Academic Integrity Policy and penalties may apply.

The Current Students website provides information on artificial intelligence in assessments. For help on how to correctly acknowledge the use of AI, please refer to the  AI in Education Canvas site.

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.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

A blanket simple extension of five days applies to all written assignments. This extension is valid without approval. Only after this period has passed, late penalties will apply in accordance with the Business School policy (unless formal Special Consideration is granted: If you have suffered illness, injury or misadventure and have been unable to complete an assignment task, you can apply for an extension of 5 calendar days from the due date with no penalty. Assignments can include: essay, report, case study, proposal, literature review, portfolio, or design. You cannot receive an extension for group work through this process.”).

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

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 2023 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 2023. 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	Unit Introduction	Lecture (3 hr)
Week 02	Case Study Research Methods	Lecture (3 hr)
Week 03	Business Problem Identification	Lecture (3 hr)
Week 04	Design Science Research Methods	Lecture (3 hr)
Week 05	Solution Objective	Lecture (3 hr)
Week 06	Prototyping and Storytelling	Lecture (3 hr)
Week 07	Outsourcing and Automation	Lecture (3 hr)
Week 08	IT Project Management	Lecture (3 hr)
Week 09	Usability Engineering	Lecture (3 hr)
Week 10	Design Ethics	Lecture (3 hr)
Week 11	Scientific Writing	Lecture (3 hr)
Week 12	Unit Review and Debriefing	Lecture (3 hr)
Week 13	Project presentations	Lecture (3 hr)

Attendance and class requirements

Lecture recordings: Lectures and seminars are not recorded but recordings from previous semesters will be available on Canvas for student use. Please note the Business School does not own the system and cannot guarantee that the system will operate or that every class will be recorded. Students should ensure they attend and participate in all classes.

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.

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 problem with societal relevance
LO2. analyse open-ended business scenarios and evaluate the implications of information systems decisions
LO3. apply techniques for organisational and business process analyses 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.

Sessional changes have been made based on the received student feedback.

Additional information

More information can be found on Canvas.

Disclaimer

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

This unit of study outline was last modified on 07 Feb 2025.

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) and automated writing tools

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

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

Media

Student links

About us

Connect

Current students

INFS3600: Business Information Systems in Practice

Semester 1, 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) and automated writing tools

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

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

Media

Student links

About us

Connect