Outline

Overview

Accountants are extensive users of business information systems (BIS). They also play a critical advisory and managerial role in relation to the design, adoption, evaluation and assurance of BIS to ensure that information and systems are properly governed to manage and mitigate risk, are used ethically and contribute to business value. This unit provides an introduction to current and emerging information technologies (IT) that support and enable business processes, information management, decision-making, data analysis and reporting of critical business information in accounting. In addition, associated governance, risk and compliance challenges are explored. Relationships between business processes and accounting information systems are examined to develop an understanding of the complex and changing business information environment from the perspective of different stakeholders. Students use a variety of tools, frameworks and models that assist in identifying opportunities for business value creation to ensure that strategies meet business needs.

Unit details and rules

Academic unit	Accounting, Governance and Regulation
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Ravi Seethamraju, ravi.seethamraju@sydney.edu.au

Assessment

The census date for this unit availability is 31 March 2025

Details
Criteria

Type	Description	Weight	Due	Length
Supervised exam ?	Final exam Written exam	40%	Formal exam period	2 hours
Outcomes assessed:
Skills-based evaluation	Skills assessment (technology tools) Demonstration of technology skills	15%	Week 10	90 minutes
Outcomes assessed:
Assignment	Group assignment Written reports and presentation	30%	Week 11 Due date: 16 May 2025 at 23:59 Closing date: 23 May 2025	Equate to 3000 words
Outcomes assessed:
Assignment	Individual assignment and class-work Written report and in-class technology work	15%	Weekly	1500 words equivalent
Outcomes assessed:
= hurdle task ? = group assignment ? = AI allowed ?

Assessment summary

Individual assignment: Students are required to complete the weekly class-work activities and submit online and/or demonstrate completion of the task in the system (technology platform) when technology is used. It requires students to demonsrate proficiency in the technical skills and understanding of concepts learnt every week. Further details will be provided in Canvas.
Group assignment: Students, as a group of 4 to 5, are required to research and examine key facts and important issues related to the selected topic and/or case study applying the concepts and selection criteria, and evaluating the ethical, social and cultural issues in the adoption and assurance of accounting information systems. A written report and an oral presentation are required. Further details will be provided in Canvas.
Skills assessment: Students are required to demonstrate their specialist software/technology skills in mapping, designing and execution of accounting information system parameters for a given business scenario in a supervised environment. Further details will be provided in Canvas.
Final exam: This is a closed-book exam in a supervised environment and covers all the content covered throughout the semester including all the associated readings and unit materials. Further details will be provided in Canvas. The final exam is listed as a HURDLE TASK, which means you must undertake the assessment andachieve a mark above the minuimum standard. Students who fail to achieve this minimum standard in this assessment, even when their aggregate mark for the entire unit is above 50%, will be given a FAIL grade for the unit. As a result, the student's academic transcript will show a fail grade and the actual mark achieved is between 0-49 and fail grade and a capped moderated mark of 49 for all other marks. The hurdle mark for this assessment is 45%.

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 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.

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 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 to the unit: Accounting Information Systems (AIS) components, impact of current & emerging technologies on AIS	Lecture (3 hr)
Week 02	Database concepts I	Lecture (3 hr)
Week 03	Database concepts II	Lecture (3 hr)
Week 04	Business processes 1 - concepts, significance, mapping/modelling, data flows and controls	Lecture (3 hr)
Week 05	Business processes 2 - mapping/modelling processes and data flows and controls continued.	Lecture (3 hr)
Week 06	Enterprise systems and transaction cycles: the expenditure cycle	Lecture (3 hr)
Week 07	Enterprise systems and transaction cycles: the revenue cycle	Lecture (3 hr)
Week 08	Enterprise Systems and transaction cycles - financial reporting and other cycles	Lecture (3 hr)
Week 09	Enterprise systems and business intelligence	Lecture (3 hr)
Week 10	Enterprise systems and business intelligence 2	Lecture (3 hr)
Week 11	Enterprise risk management and control challenges in the digital age	Lecture (3 hr)
Week 12	Group presentations and exam preparation	Lecture (3 hr)
Week 13	Group presentations, wrap up and exam preparation	Lecture (3 hr)

Attendance and class requirements

Attendance: Each student must attend one three hour workshop per week for 13 weeks as per the timetable. Students must check their individual time table and find out the locations and timings.
Lecture recordings: One lecture stream will be recorded and 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 successfully. Students should ensure they follow the Canvas modules and associated learning materials provided for online learners.
NO Group presentation recording: Additionally, group presentation recordings will not be made available. You are not permitted to record any group presentation with any device.
Public Holidays in teaching weeks this semester are: Good Friday 18 April 2025, Easter Monday 21 April 2025 and Anzac day 25 April 2025. There are no classes on public holidays.
The mid-semester break (AVCC Week) immediately follows Week 8. The break is Monday 21 April to Friday 25 April 2025. There are no classes or consultations held during AVCC week.
Weeks 12 and 13 are group presentations and require compulsory attendance for all students. An approved Special Consideration is required if a student is unable to attend one of these weeks.

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

Prescribed Text Book:

Parkes, A., Considine, B., Oleson, K., Blount, Y. (2016). Accounting Information Systems 5th Edition John Wiley & Sons Australia Ltd

The publisher now offers an improved access and cost opportunity for students to access the text book. It is suggested that students access the Wiley website for further details
Students will need to have access to the text book to complete prescribed readings for this unit
An e-text is available in Fisher Library
All other readings for this unit will be provided in the Learning Materials on Canvas as required

Additional text readings may be offered and these texts will be available from Fisher 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. Identify and explain the impact of information technology in an accounting and business context, on the organisation's business model and critical business activities
LO2. Examine and summarise concepts of enterprise risk management, organisational governance and internal control, and the importance of these for accountants in relation to identifying, reporting and managing risk within the organisation
LO3. Analyse different roles of stakeholders and evaluate key social, ethical and cultural issues involved in the design, implementation and assurance of accounting information systems
LO4. Demonstrate knowledge of key concepts and tools for designing, documenting, and analysing business processes and internal controls using BPMN notation, basic data models, and two software packages. Practice an approach through class activities and other assigned tasks
LO5. Develop and support arguments through reading and library research
LO6. Communicate persuasively and collaborate effectively with different personalities, individually and in group settings, to achieve professional outcomes

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.

Intend to continue with the group presentation and additional support to technology skills.

Additional information

Study commitment: Typically there is a minimum expectation of 1.5 to 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 roughtly 120 to 150 hours of student effort in total in a semester.

Consultation and discussion forum: Consultation times will be posted in Canvas. Students are encouraged to use Canvas discussion forums for clarification about the unit including the content, workshops, assessments and others.

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) 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

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

INFS5000: Accounting Information Systems

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

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