Outline

Overview

Computer-Aided Project Management builds a bridge from the genesis of project management principles through today's software, developing a postmodern project management systems paradigm for the twenty-first century. This Unit of Study demonstrates how fundamental project management principles work in the software environment. It equips students with the effective application-based introduction to create WBS (Work Breakdown Structure), OBS (Organizational Breakdown Structure) and human resources planning and scheduling for different project types.

Unit details and rules

Academic unit	Project Management
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Marshal Hammam Alkouz, hammam.alkouz@sydney.edu.au
Lecturer(s)	Marshal Hammam Alkouz, hammam.alkouz@sydney.edu.au

Assessment

The census date for this unit availability is 2 April 2024

Details
Criteria

Type	Description	Weight	Due	Length
Assignment	Scrum Project Plan in Jira Develop project plan in Jira	10%	Week 05 Due date: 31 Mar 2024 at 23:59	One Week
Outcomes assessed:
Presentation	Group Presentation Students will present on a selected PPM tool	10%	Week 07 Due date: 11 Apr 2024 at 23:59	10-12 minutes.
Outcomes assessed:
Assignment	Kanban Project Plan in Trello Develop project plan in Trello	10%	Week 07 Due date: 14 Apr 2024 at 23:59	One week
Outcomes assessed:
Assignment	Traditional project plan in MS Project Develop project plan in MS Project	10%	Week 13 Due date: 26 May 2024 at 23:59	one week
Outcomes assessed:
Online task	Final Quiz The online final quiz. 45 multiple-choice questions.	20%	Week 13 Due date: 23 May 2024 at 20:59	45 minutes
Outcomes assessed:
Small continuous assessment	Weekly Quiz Weekly online quizzes will cover the topic discussed the week before	20%	Weekly	5 minutes
Outcomes assessed:
Participation	Workshop participation Participation in problem-solving sessions scheduled within the workshops	10%	Weekly	All the semester
Outcomes assessed:
Small continuous assessment	Online Discussions Weekly discussion in Canvas	10%	Weekly	100 -200 words
Outcomes assessed:
= group assignment ?

Assessment summary

· Class participation: Class participation is marked based on the student’s involvement during lectures and tutorial

· Weekly Quiz: Weekly online quizzes will cover the topic discussed the week before

· Assignment 1: In this group assignment, students will be asked to find a sample project from the literature, or industry. Students will then develop a product backlog and Sprits planning which they will set up in Jira Software.

· Assignment 2: In this group assignment, students will be asked to find a sample project from the literature, or industry. Students will then develop a project plan which they will set up in Trello.

· Assignment 3: In this group assignment, students will be asked to find a sample project from the literature, or industry. Students will then develop a project plan which they will set up in MS Project.

· Group Presentation: Students will present ton a selected PPM tool that they learned during this course

· Final Quiz: The online quiz will comprise multiple-choice questions. The quiz will cover topics from in-class presentations, tutorials and in-class discussion materials

· Online Discussions: This is a weekly discussion in Canvas.

Important Note:

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.

Text-matching software for Assignment Submission:

As part of the assessment process, text-matching software such as Turnitin will be used to identify plagiarism and/or be used for providing feedback.

Confidential Peer Evaluation:

As part of the group contribution assessment process, collaborative & self-peer evaluation tools (e.g. SparkPlus, CATME, etc.) may be used, either on a confidential or non-confidential basis, to understand contributions and interactions amongst group members. Marks may be adjusted for an individual team member, following on from the peer evaluation process.

Mark Moderation:

Mark moderation: There may be statistically defensible moderation when combining the marks from each component to ensure consistency of marking between markers, and alignment of final grades with unit outcomes.

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.

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:

Late Penalty: For every calendar day up to and including ten calendar days after the due date, a penalty of 5% of the maximum awardable marks will be applied to late work. The penalty will be calculated by first marking the work, and then subtracting 5% of the maximum awardable mark for each calendar day after the due date. Example: Consider an assignments maximum awardable mark is 10; the assignment is submitted 2 days late; and the assignment is marked as 7/10. After applying the penalty, marks will be: 7 - (0.5 x 2) = 6/10. For work submitted more than ten calendar days after the due date a mark of zero will be awarded. The marker may elect to, but is not required to, provide feedback on such work. Refer to section 7A of Assessment procedures policy available at: http://sydney.edu.au/policies/showdoc.aspx?recnum=PDOC2012/267&RendNum=0 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. Text-matching software for Assignment Submission: As part of the assessment process, text matching software such as Turnitin will be used to identify plagiarism and/or be used for providing feedback. Confidential Peer Evaluation: As part of the group contribution assessment process, collaborative & self-peer evaluation tools (e.g. SparkPlus, CATME, etc.) may be used, either on a confidential or non-confidential basis, to understand contributions and interactions amongst group members. Marks may be adjusted for an individual team member, following on from the peer evaluation process. Mark Moderation: Mark moderation: There may be statistically defensible moderation when combining the marks from each component to ensure consistency of marking between markers, and alignment of final grades with unit outcomes.

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.

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
Ongoing	Independent study before and after the workshops Average of 8 hours per week	Independent study (104 hr)
Week 01	Introduction to PMGT5887	Workshop (2 hr)
Week 02	Project Integration tools + Jira	Workshop (2 hr)
Week 03	Scrum with Jira software-2	Workshop (2 hr)
Week 04	Scrum with Jira software-3	Workshop (2 hr)
Week 05	Kanban with Jira & Trello	Workshop (2 hr)
Week 06	Student presentation	Workshop (2 hr)
Week 07	PM collaborative tools (Miro)	Workshop (2 hr)
Week 08	Starting a project with MS project	Workshop (2 hr)
Week 09	Scheduling in MS Project	Workshop (2 hr)
Week 10	Cost & Resource Management in MS Project	Workshop (2 hr)
Week 11	Project Tracking & Control in MS Projects	Workshop (2 hr)
Week 12	Using MS Excel and Power BI in Projects	Workshop (2 hr)
Week 13	Final Quiz	Workshop (2 hr)

Attendance and class requirements

Attendance is encouraged for all workshop sessions. Absenteeism may affect in class individual and team performance and assessments.

Special considerations applications must be made in advance for approvals. Any absenteeism and appeals must be supported by a valid reason evidenced through official documents e.g. medical certificate or company documentation.

Study commitment

Required readings

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

Carl Chatfield and Timothy Johnson – Microsoft Project 2016 Step-by-Step. Microsoft Press, 2016. 978-0-7356-9874-1

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. Understand the key systems and processes of project management
LO2. Understand the application of appropriate information-communication technology tools available at various stages of the project
LO3. Understand the concepts, framework and structure within which the computer application works in although computer applications change over time
LO4. Apply the use of the right technology for the right task in the project phase
LO5. Demonstrate knowledge of common tools used by professionals in the industry
LO6. Demonstrate the skill to learn, use and adapt new technologies effectively and efficiently.

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.

Change made to move from 12 to 13-week semester.

Additional information

Late Penalty:

For every calendar day up to and including ten calendar days after the due date, a penalty of 5% of the maximum awardable marks will be applied to late work. The penalty will be calculated by first marking the work, and then subtracting 5% of the maximum awardable mark for each calendar day after the due date. Example: Consider an assignment's maximum awardable mark is 10; the assignment is submitted 2 days late; and the assignment is marked as 7/10. After applying the penalty, marks will be: 7 - (0.5 x 2) = 6/10. For work submitted more than ten calendar days after the due date a mark of zero will be awarded. The marker may elect to, but is not required to, provide feedback on such work. Refer to section 7A of Assessment procedures policy available at: http://sydney.edu.au/policies/showdoc.aspx?recnum=PDOC2012/267&RendNum=0

Study Commitment:

Text-matching software for Assignment Submission:

As part of the assessment process, text matching software such as Turnitin will be used to identify plagiarism and/or be used for providing feedback.

Confidential Peer Evaluation:

Mark Moderation:

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

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

Media

Student links

About us

Connect

Current students

PMGT5887: Computer Applications

Semester 1, 2024 [Normal evening] - Camperdown/Darlington, Sydney

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

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

Media

Student links

About us

Connect