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Unit outline_

COMP5206: Information Technologies and Systems

Semester 2, 2024 [Normal evening] - Camperdown/Darlington, Sydney

This unit will provide a comprehensive introduction to the field of information systems from organisational and managerial perspectives. The emergence of the digital firm and its implications will be studied. The critical role of information and knowledge management will be emphasised from both conceptual and practical standpoints. Key topics covered will include: Basic Information Systems Concepts; Systems Approach and Systems Thinking; E-Business and E-Commerce; IT Strategy and Competitive Advantage; Data and Knowledge Management; Information Systems Development and IS Management; Decision support systems, business intelligence and online analytical processing systems (OLAP); Enterprise Resource Planning (ERP) systems, Customer Relationship Management (CRM) systems, Enterprise Content Management and Supply Chain Management (SCM) systems; Ethical, Legal and Social Aspects of Information technologies.

Unit details and rules

Academic unit Computer Science
Credit points 6
Prerequisites
? 
None
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

None

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Hazem El-Alfy, hazem.elalfy@sydney.edu.au
Lecturer(s) Jose Meza, jose.meza@sydney.edu.au
The census date for this unit availability is 2 September 2024
Type Description Weight Due Length
Supervised exam
? 
Final exam
Final exam
50% Formal exam period 2 hours
Outcomes assessed: LO1 LO3
Participation workshop participation
Individual participation and completion of workshop / tutorial practices
15% Multiple weeks N/A
Outcomes assessed: LO1 LO3
Small test Knowledge Test
Written test
15% Week 07 N/A
Outcomes assessed: LO1 LO3
Small continuous assessment group assignment Group Assignment
Group Assignment
10% Week 10
Due date: 13 Oct 2024 at 23:59
N/A
Outcomes assessed: LO1 LO2 LO3 LO4
Presentation group assignment Group Presentation
Group Presentation
10% Week 12 N/A
Outcomes assessed: LO1 LO2 LO3 LO4
group assignment = group assignment ?

Assessment summary

Knowledge Test
It is a small class test. The details of the format and coverage will be provided in lectures.


Group Project
The group project will be completed by groups of approximately 4 students. The project will involve the application of many of the concepts covered in lectures. It will require extensive collaboration between group members. The assessment submission will be in the form of a detailed written report. Students will also be asked to submit individual peer assessments that will be used to moderate marks within the group. Further details of the assignment will be available on Canvas. 


Presentation
It is a group presentation based on the Group Project.

Final Exam
Supervised final exam. All of the materials in the unit will be examinable. Further details, including the format and expectations regarding the final examination will be provided in lectures.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2021 (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

 

Distinction

75 - 84

 

Credit

65 - 74

 

Pass

50 - 64

 

Fail

0 - 49

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

It is a policy of the School of Computer Science that in order to pass this unit, a student must achieve at least 40% in the written examination. For subjects without a final exam, the 40% minimum requirement applies to the corresponding major assessment component specified by the lecturer. A student must also achieve an overall final mark of 50 or more. Any student not meeting these requirements may be given a maximum final mark of no more than 45 regardless of their average.

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

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.

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:

In accordance with University policy, these penalties apply when written work is submitted after the due date: (1) Deduction of 5% of the maximum mark for each calendar day after the due date. (2) 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: No late submission will be accepted for in-class discussion.

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.

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

WK Topic Learning activity Learning outcomes
Week 01 Introduction to information systems Lecture (2 hr) LO1
Week 02 Information systems for competitive advantage Lecture and tutorial (3 hr) LO1 LO3
Week 03 IS infrastructure and services, and ethics Lecture and tutorial (3 hr) LO1 LO3
Week 04 E-business and e-commerce Lecture and tutorial (3 hr) LO1 LO3
Week 05 Mobile commerce Lecture and tutorial (3 hr) LO1 LO3
Week 06 Enhancing Business Intelligence using Big Data, Analytics, and Artificial Intelligence Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4
Week 07 Knowledge Test Lecture and tutorial (3 hr) LO1 LO2
Week 08 Digital marketing and social media Lecture and tutorial (3 hr) LO1 LO3
Week 09 IS security and risk management Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4
Week 10 Enterprise systems Lecture and tutorial (3 hr) LO1 LO3
Week 11 IS acquisition and development Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4
Week 12 Presentation Lecture and tutorial (3 hr) LO1 LO3 LO4
Week 13 Review Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4

Attendance and class requirements

Attendance is compulsory

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

All readings for this unit can be accessed through the Library eReserve, available on Canvas.

Joseph Valacich, Christoph Schneider – Information Systems Today: Managing in the Digital World.

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.

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

  • LO1. identify important IS/IT issues, analyse the problems involved, and develop comprehensive solutions that address the issues effectively
  • LO2. conduct independent research and analysis on various IS/IT issues using appropriate information obtained from diverse sources
  • LO3. present ideas and arguments effectively, engage the audience, and stimulate intellectual discussion
  • LO4. deliver a comprehensive and integrated IS/IT solutions that reflects a collective effort from a professional project team.

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
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9
LO1         
LO2         
LO3         
LO4         

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

No significant changes have been made since this unit was last offered.

IMPORTANT: School policy relating to Academic Dishonesty and Plagiarism.

In assessing a piece of submitted work, the School of Computer Science may reproduce it entirely, may provide a copy to another member of faculty, and/or to an external plagiarism checking service or in-house computer program and may also maintain a copy of the assignment for future checking purposes and/or allow an external service to do so.

Computer programming assignments may be checked by specialist code similarity detection software. The Faculty of Engineering currently uses the MOSS similarity detection engine (see http://theory.stanford.edu/~aiken/moss/), or the similarity report available in ED (edstem.org). These programs work in a similar way to TurnItIn in that they check for similarity against a database of previously submitted assignments and code available on the internet, but they have added functionality to detect cases of similarity of holistic code structure in cases such as global search and replace of variable names, reordering of lines, changing of comment lines, and the use of white space.

All written assignments submitted in this unit of study will be submitted to the similarity detecting software program known as Turnitin. Turnitin searches for matches between text in your written assessment task and text sourced from the Internet, published works and assignments that have previously been submitted to Turnitin for analysis.

There will always be some degree of text-matching when using Turnitin. Text-matching may occur in use of direct quotations, technical terms and phrases, or the listing of bibliographic material. This does not mean you will automatically be accused of academic dishonesty or plagiarism, although Turnitin reports may be used as evidence in academic dishonesty and plagiarism decision-making processes.

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.