Outline

Overview

Projects typically need to be delivered within a defined timescale. Providing robust estimates, monitoring and controlling project duration are crucial to understand the ongoing viability of the investment made in a project. This Unit provides students with a background in advanced scheduling and estimation techniques, supported by project management software.

Unit details and rules

Academic unit	Project Management
Credit points	6
Prerequisites ?	[24 cp of BPM core 2000 level units] or [30 cp of any 2000 level units of study]
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Fatima Afzal, fatima.afzal@sydney.edu.au
Lecturer(s)	Jeffrey Scales, jeffrey.scales@sydney.edu.au

Type	Description	Weight	Due	Length
Assignment	Assignment 1 You will research and write an essay on an area related to scheduling.	30%	Week 06 Due date: 11 Sep 2022 at 23:59	2000-word Essay
Outcomes assessed:
Tutorial quiz	Quiz 1 Multiple Choice Questions	10%	Week 08 Due date: 23 Sep 2022 at 23:59	30 minutes
Outcomes assessed:
Creative assessment / demonstration	Assignment 2 You will submit a project schedule using MS Project based on the scenario.	10%	Week 09 Due date: 09 Oct 2022 at 23:59	Schedule in MS Project file format
Outcomes assessed:
Assignment	Group Assignment Students will work in small groups to develop a project report and schedule	20%	Week 10 Due date: 16 Oct 2022 at 23:59	3000 words
Outcomes assessed:
Assignment	Group Presentation Students will present their report and schedule in class	10%	Week 11 Due date: 17 Oct 2022 at 18:00	5 minutes
Outcomes assessed:
Tutorial quiz	Quiz 2 Multiple Choice Questions	10%	Week 13 Due date: 01 Nov 2022 at 23:59	30 minutes
Outcomes assessed:
Assignment	Reflective Students will write a reflection	10%	Week 13 Due date: 06 Nov 2022 at 23:59	1000 words
Outcomes assessed:
= group assignment ?

Assessment summary

Detailed information for each assessment can be found on Canvas.

Assessment Name	Team-Based?	Weight	Due in
Academic Writing	No	30%	Week 6
Quiz 1	No	10%	Week 8
Skills Based (MS Project)	No	10%	Week 9
Project Report	Yes	20%	Week 10
Presentation	Yes	10%	Week 11
Quiz 2	No	10%	Week 13
Reflection	No	10%	Week 13

Assessment criteria

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 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: 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.

Weekly schedule

WK	Topic	Learning activity
Week 01	Course Introduction, Project Management, Scheduling and Administrative matters	Workshop (2 hr)
Week 02	Scheduling approaches	Workshop (2 hr)
Week 03	Scope, WBS and Tasks	Workshop (2 hr)
Week 04	Time, Effort and Duration of Tasks	Workshop (2 hr)
Week 05	Direct and Other Costs in schedule	Workshop (2 hr)
Week 06	MS Project for Scheduling	Workshop (2 hr)
Week 07	Resource Management in Scheduling	Workshop (2 hr)
Week 08	Online Quiz	Individual study (2 hr)
Week 09	Schedule Reporting	Workshop (2 hr)
Week 10	Schedule Exercise	Workshop (2 hr)
Week 11	Group Presentations	Workshop (2 hr)
Week 12	Scheduling in Agile Projects	Workshop (2 hr)
Week 13	Agile concepts with Jira	Workshop (2 hr)
Weekly	Self Study - Every week 6 hours self study is expected from students	Independent study (90 hr)

Attendance and class requirements

Students are expected to attend a minimum of 90 percent of timetabled activities for a unit of study unless granted exemption by the Dean or Head of School most concerned.

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

There are no prescribed readings, however, we will provide reading material in the class moduels.

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. Select appropriate planning and scheduling techniques for different project types
LO2. Demonstrates effective interpersonal and team leadership skills at small group scale, including routine internal problem-solving and conflict resolution situations.
LO3. Understand different formats of project schedules such as precedence diagram and Gantt chart.
LO4. Learn how to competently create project schedules manually and by using commonly used computer software.
LO5. Learn to identify and understand task relationships and dependencies and understand how to effectively allocate project resources and update and monitor project schedules.
LO6. Learning basic techniques to crash/ fast track project schedules.
LO7. Apply the concept of risk and probability scheduling techniques.

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.

No significant 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.

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

Disclaimer

On this page

Useful links

PMGT3623: Scheduling

Semester 2, 2022 [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

Disclaimer

On this page

Useful links