Skip to main content
Unit outline_

ISYS3888: Information Systems Project

Semester 2, 2020 [Normal day] - Camperdown/Darlington, Sydney

This unit will provide students an opportunity to apply the knowledge and practise the skills acquired in the prerequisite and qualifying units, in the context of a substantial information systems research or development project and to experience in a realistic way many aspects of analysing and solving information systems problems. Since information systems projects are often undertaken by small teams, the experience of working in a team is seen as an important feature of the unit. Students often find it difficult to work effectively with others and will benefit from the opportunity provided by this unit to further develop this skill.

Unit details and rules

Academic unit Computer Science
Credit points 6
Prerequisites
? 
(INFO2110 OR ISYS2110) AND (INFO2120 OR ISYS2120) AND (ISYS2140 OR ISYS2160)
Corequisites
? 
None
Prohibitions
? 
INFO3600 OR ISYS3207 OR ISYS3400
Assumed knowledge
? 

None

Available to study abroad and exchange students

No

Teaching staff

Coordinator Farnaz Farid, farnaz.farid@sydney.edu.au
Type Description Weight Due Length
Participation Participation
Individual participation in the project.
10% Multiple weeks week 1 - week 12
Outcomes assessed: LO2
Presentation Progress report (presentation)
Weekly progress report presentation
10% Multiple weeks week 2 - week 10
Outcomes assessed: LO2
Assignment group assignment Project plan
A document to guide the project. Need to submit the plan as a group.
10% Week 03 week 1 - week 3
Outcomes assessed: LO4
Assignment group assignment Project Proposal
Project Proposal - A detailed report on the project.
20% Week 05 week 3 - week 5
Outcomes assessed: LO4
Assignment group assignment Final Report
Final prototype and report
30% Week 11 week 6 - week 11
Outcomes assessed: LO3 LO5
Presentation group assignment Final Project Presentation
Each group will present their projects though a final group presentation.
20% Week 12 15 mins
Outcomes assessed: LO1 LO5 LO4 LO3 LO2
group assignment = group assignment ?

Assessment summary

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

 

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 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:

1) It is expected that unless an application for special consideration, special arrangement or previously arranged disability adjustment has approved an extension, students will submit all assessment for a unit of study on or before the due date specified. If the assessment is completed or submitted by the student before the due date or within the period of extension, no academic penalty will be applied to that piece of assessment. (2) If assessments are submitted after the due date or if an extension is not granted, or is granted but work is submitted by the student after the extended due date, the late submission of assessment will result in an academic penalty as follows: (a) any assessment submitted after the due time and date (or extended due time and date) will incur a late penalty of 5% of the total marks per 24 hour period, or part thereof, late (note that this is applied to the mark gained after the submitted work is marked). (b) assessments submitted after the "Closing Date" noted in the Unit of Study Outline will not be marked or assessed.

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.

WK Topic Learning activity Learning outcomes
Week 01 Finalising Projects, Teams and Supervisors Lecture (2 hr) LO3
Week 02 Problem exploration: strategies, methods, difficulties, good and bad experiences, outcomes. Lecture (2 hr) LO1 LO2 LO4
Week 03 Defining the Project: key issues, focus, exact formulation, objectives, team acceptance, approval. Assessment Due: Project Plan Lecture (2 hr) LO1 LO2 LO3
Week 04 Deciding on a Methodology: using the literature, tools, techniques and technologies, selection criteria, evaluation. Lecture (2 hr) LO1 LO2 LO3 LO4
Week 05 Confirmation of Project Proposal: selling the idea, negotiation, compromise, agreement, signing off. Assessment Due: Proposal Lecture (2 hr) LO1 LO2 LO3 LO4
Week 06 Development: specifics of the task - what, how, problems encountered, strategies adopted, execution, selection of tool/resources. Data Collection and Analysis/ Prototype Lecture (2 hr) LO1 LO2 LO3 LO4 LO5
Week 07 Progress and Findings: progress, literature cited & evaluation, products/tools selected & why, research/ development strategies, methods of recording/documenting. Lecture (2 hr) LO1 LO2 LO3 LO4 LO5
Week 08 Team Dynamics & the Group Culture: teamwork, strategies, problems, solutions, making use of individuals, team culture, comparison with theory. Lecture (2 hr) LO1 LO2 LO3 LO4 LO5
Week 09 Testing and Evaluation: identifying targets, determining performance/ satisfaction measures, test scenarios/ research evaluation, testing strategies Lecture (2 hr) LO1 LO2 LO3 LO4 LO5
Week 10 Achievement of Objectives: measuring success, gauging client/user satisfaction, evaluating benefits to client, next step for the client, project review. Lecture (2 hr) LO1 LO2 LO3 LO4 LO5
Week 11 Group Presentations Assessment Due: Report Lecture (2 hr) LO2
Week 12 Final Group Presentations Lecture (2 hr) LO2

Attendance and class requirements

  • Attendance at scheduled class meetings and team meetings is a course requirement. There are marks allocated for individual participation.
  • Students are expected to participate fully in their information systems projects. All members of the team are expected to be present at meetings and/or laboratory sessions arranged by the team and as well as any consultations arranged by the project supervisor.

 

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

Note: References are provided for guidance purposes only. Students are advised to consult these books in the university library. Purchase is not required.

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. communicate project success and failure, and personal contribution to the project
  • LO2. present complex ideas to a relatively large audience
  • LO3. work as a team to develop an IT solution for the sponsor through team work
  • LO4. translate the user's business requirements into specifications
  • LO5. design an IT solution and develop a prototype.

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

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

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

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.