Outline

Overview

The Digital Economy, with its focus on information as a key business resource, has changed the way Business Information Systems (BIS) is viewed in organisations. BIS are now seen as enablers of innovation in which people, supported by powerful technology, are considered to be the most important component. This is because problem-solving, innovation and critical thinking skills cannot be outsourced or easily acquired by competitors. This unit is designed to develop your understanding of how businesses operate. It shows how information systems support business operations and management through integration of people, business processes and systems. You will be provided with an introduction to state-of-the-art business analysis techniques, frameworks and models to assist in understanding the nature and contribution of BIS in a range of business contexts. With its emphasis on business rather than IT, this unit does not require prior IT-related experience. In this unit, you will learn about the increasingly important role of IT in business and acquire valuable business analysis and problem-solving skills.

Unit details and rules

Academic unit	Business Information Systems
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	ISYS1003 or INFO1000
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Evelyn Ng, evelyn.ng@sydney.edu.au

Type	Description	Weight	Due	Length
Supervised exam ?	Final exam Written exam	40%	Formal exam period	2 hours
Outcomes assessed:
Assignment	Group work Practical task	10%	Multiple weeks	n/a
Outcomes assessed:
Assignment	Group project Presentation and report	25%	Multiple weeks	3000 words
Outcomes assessed:
Supervised test ?	Mid-semester exam Written exam	25%	Week 06 Due date: 01 Apr 2023 at 10:00	1 hour
Outcomes assessed:
= hurdle task ? = group assignment ?

Assessment summary

Group work: Team-based learning (TBL) is a set of group-based activities designed to help students to acquire higher-level learning skills in this context, including creativity, lateral and reflective thinking, problem-solving and critical analysis as well as the applied and experiential BIS knowledge. This assessment component will consider group homework preparation for the TBL sessions as well as their work and participation in, and outcomes of collaborative in-class activities in finalising their homework submissions. The TBL activity sheets will be uploaded on Canvas.
Group project report: The objective of this task is to use the knowledge and practical skills acquired in this unit of study to investigate and solve a real-life business problem. Students are expected to create and describe their own business idea for a pre-defined scenario, which they will receive through Canvas.
Mid-semester exam: This exam will focus on the fundamental concepts, and applied and experiential knowledge acquired in weeks 1-5 of the unit. Note: This assessment will take the form of a supervised exam. It is a closed-book exam with no materials allowed.
Final exam: This exam will focus on the fundamental concepts, and applied and experiential knowledge acquired in weeks 1-12, including the practical assignment. Note: This assessment will take the form of a supervised exam. It is a closed-book exam with no materials allowed. The final exam is listed as a HURDLE TASK. This means you must undertake the assessment and achieve a mark above a minimum 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 if between 0-49 and a fail grade and a capped moderated mark of 49 for all other marks. The hurdle mark for this assessment will be advised on Canvas.

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 guide to grades.

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.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

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.

Weekly schedule

WK	Topic	Learning activity
Week 01	Unit overview and introduction to information systems	Lecture (2 hr)
Week 02	Introduction to business processes	Lecture (2 hr)
Week 03	Strategy and competitive advantage	Lecture and tutorial (3 hr)
Week 04	Databases and information design	Lecture and tutorial (3 hr)
Week 05	Data modelling	Lecture and tutorial (3 hr)
Week 06	Mid-term exam	Practical (1 hr)
Week 07	Business information systems ethics	Lecture and tutorial (3 hr)
Week 08	Business process management	Lecture and tutorial (3 hr)
Week 09	Business process modelling (BPMN)	Tutorial (3 hr)
Week 10	Business process analysis and improvement	Lecture and tutorial (3 hr)
Week 11	Social media information systems	Lecture and tutorial (3 hr)
Week 12	Business intelligence systems	Lecture and tutorial (3 hr)
Week 13	Exam briefing and unit review	Lecture (2 hr)

Attendance and class requirements

Lecture recordings:
- The TBL workshop is recorded using the system available on the venue and made available after the class. Please note that this recording will only capture the lecture parts of the TBL session, but not the group activity components.
- 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.
Attendance and participation:
- Students should ensure they attend and participate in ALL classes that are delivered face to face only during this Intensive Session.
- Participation in the TBL activities is essential for your learning progress and cannot be substituted in any other way.

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

Experiencing MIS, Global Edition MyLab Mathematics with Pearson eText 8th edition

David M. Kroenke, Randall J. Boyle

ISBN-13: 9781292270074

Please also refer to Canvas for any additional readings.

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. make judgments about ways in which Information Technology can enable innovation and improvement in business
LO2. demonstrate basic business analysis skills, such as strategic analysis, data modelling, and business process modelling
LO3. create and understand visual representations of business processes using BPMN notation, as well as basic data models as the basis for information systems design
LO4. create databases in MS Access software
LO5. understand and address basic issues pertaining to information ethics
LO6. work as an effective team in a problem-solving environment
LO7. display an understanding of business design in an end-to-end manner from business idea to business execution.

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.

The exam type has changed from Type C to Type B.

Additional information

More information can be found on Canvas.

The full schedule of the unit is available via the Timetable.

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

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

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

Media

Student links

About us

Connect

Current students

INFS1000: Digital Business Innovation

Semester 1, 2023 [Normal day] - Remote

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

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

Media

Student links

About us

Connect