Outline

Overview

The Job Smart Edge unit is designed to provide students with the employability skills and tools to work effectively in an organisation. The unit features a client project bootcamp jointly delivered by careers and employability practitioners and educators. The focus is on preparing students to successfully undertake industry-focused problem-solving work in diverse teams. The learning journey includes an intensive 2-week virtual Digital Industry Project with a real client, with pre- and post-project employability workshops to provide students with the skills, models and tools to allow them to navigate and secure further employability opportunities. Workshops cover learning how to plan a project, launch a project, ensure project engagement, wrap up a project and communicate about a project. The assessments are designed to assist students with setting personal, team and project goals, with working on a project challenge and preparing a report for a client, and with developing and reflecting on individual employability capabilities developed through the program (including innovative problem solving and interpersonal leadership skills). By the end of the unit it is expected that students will be more equipped and prepared to face the world of employment.

Unit details and rules

Academic unit	Work and Organisational Studies
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	BUSS6102
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Jessica Tyrrell, jessica.tyrrell@sydney.edu.au

Assessment

The census date for this unit availability is 2 October 2026

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Written work	Assessment 1: Project report Client report for the Digital Industry Project.	40%	Week 03 Due date: 11 Oct 2026 at 23:59 Closing date: 25 Oct 2026	2000 words	AI allowed
Outcomes assessed:
Portfolio or journal	Assessment 2: E-portfolio Compiling and presenting evidence of employability skills development.	30%	Week 05 Due date: 25 Oct 2026 at 23:59 Closing date: 08 Nov 2026	1000 Words / 5 web pages	AI allowed
Outcomes assessed:
Interactive oral	Assessment 3: Mock interview Students respond to mock interview questions about their employability and E-portfolio.	30%	Week 07 Due date: 02 Nov 2026 at 08:00 Closing date: 20 Nov 2026	10 minutes	AI prohibited
Outcomes assessed:
= group assignment ?

Assessment summary

The three assessments in this unit are linked to one another and are designed to develop students' employability skills through experiential and team-based learning. Student teams firstly engage in an industry project with a real client, followed by individual reflection on and communication of the employability capacities developed through the teamwork and client consultation process, and across the unit.

Assessment 1: Project report

Students will be required to work in teams to produce a 2,000 word report in response to their specific client's brief and requirements as part of the Digital Industry Project. Teams will have the opportunity to submit a draft report to the client for feedback before the final graded submission.

Assessment 2: E-portfolio

Students will be required to reflect on their developing employability capabilities in relation to the Digital Industry Project and present these in an individual E-portfolio that showcases their employability and professional identity.

Assessment 3: Mock interview

Students will be required to engage in an individual verbal Q&A with their tutor, conducted in the week following the final tutorial. Students will respond to interview-style questions about their employability capabilities and professional identity, which may relate to their submitted e-portfolio, their experience of the Digital Industry Project, and their employability development in the unit more broadly.

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.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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:

Assessment 3 (Mock interview) is a secure, in-person assessment scheduled individually with the tutor in Week 7 (S2 Week 13). Students who are unable to attend their scheduled interview must apply for Special Consideration. Assessment 2 (E-portfolio) should be submitted by the due date for the student to gain the fullest learning experience from Assessment 3, as these assessments are linked. Assessment 1 (Project report) is a group assessment. Simple extensions are not available for group assessments; students or teams affected by illness, injury or misadventure should apply for Special Consideration as early as possible so that appropriate arrangements can be made. Late submissions may not receive client feedback on the draft report. Students who anticipate difficulty meeting any deadline should contact the Unit Coordinator at the earliest opportunity.

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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 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. 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
Week 01	Week 1 - Planning a project (S2 Week 8). Introduction to the unit and client brief, the experiential and reflective project-based approach, assessments, and project teams. Models, skills and tools for framing a business challenge and planning accordingly. Note: each week includes a Lecture (1hr) + Tutorial (2hrs). The Week 1 lecture will be held on Zoom to facilitate client briefings across the cohort. Digital Industry Project (WK 1) - meet the client and begin report.	Lecture (10 hr)
Week 02	Week 2 - Launching a project (S2 mid-sem break). Models, skills and tools for identifying original, well-structured and strategic approaches for project work on business challenges. Digital Industry Project (WK 2) - draft report due 28 September @ 11:59pm for client feedback. Team 360 reflection due 29 September @ 5pm. Note: the Week 2 lecture is face-to-face.	Lecture (10 hr)
Week 03	Week 3 - Project engagement (S2 Week 9). Models, skills and tools for engaging project stakeholders and teams in effective collaborative processes. Digital Industry Project (WK 3) - Final report due to client. Note: due to the public holiday, there will be no live lecture on Monday. Instead, the Week 3 lecture will be pre-recorded and available for viewing on Canvas.	Lecture (10 hr)
Week 04	Week 4 - Wrapping a project (S2 Week 10). Models, skills and tools for evaluating project success and highlighting employability learnings. Note: the Week 4 lecture is face-to-face.	Lecture (3 hr)
Week 05	Week 5 – Showcasing professional identity (S2 Week 11). Exploring professional identity and the concept of professional practice. Developing professional written and visual communication skills for presenting your employability capabilities, evidence and experience. Building and refining the e-portfolio as a professional digital artefact. Note: the Week 5 lecture is face-to-face.	Lecture (3 hr)
Week 06	Week 6 – Communicating employability (S2 Week 12). Developing professional verbal communication and interview skills for articulating employability in a simulated recruitment context. The final tutorial comprises a formative interview activity in preparation for A3. Note: the Week 6 lecture is face-to-face.	Lecture (3 hr)
Week 07	Non-teaching assessment week (S2 Week 13). No lecture or tutorial. Individual mock interview (A3) conducted with the tutor by scheduled appointment.	Assessment (0.08 hr)

Attendance and class requirements

Attendance is required at all classes. Due to the intensive design of this unit of study with a fast-paced team project focus, students are required to attend and actively participate in at least 80% of the lectures and tutorials in order to pass the unit. Where there is an unavoidable reason for non-attendance, the student must apply for Special Consideration or a Simple Extension through the university system.

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

OECD Employment Outlook 2025. https://www.oecd.org/en/publications/2025/07/oecd-employment-outlook-2025_5345f034.html

Siivonen, P., Isopahkala-Bouret, U., Tomlinson, M., Korhonen, M., & Haltia, N. (2023). Rethinking Graduate Employability in Context: Discourse, Policy and Practice (M. Korhonen, N. Haltia, P. Siivonen, M. Tomlinson, & U. Isopahkala-Bouret, Eds.; 1st ed.). Springer Nature. https://doi.org/10.1007/978-3-031-20653-5

Tomlinson, M. (2017). Forms of graduate capital and their relationship to graduate employability. Education & Training (London), 59(4), 338–352. https://doi.org/10.1108/ET-05-2016-0090

World Economic Forum, Future of Jobs Report 2025. https://www.weforum.org/publications/the-future-of-jobs-report-2025/

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. Identify and develop innovative problem-solving capabilities and skills to enhance employability.
LO2. Cultivate the ability to work effectively and professionally with others from diverse disciplinary backgrounds.
LO3. Develop oral and written communication skills through interactions with various stakeholders, including industry and peers.
LO4. Evaluate issues related to employability and professional development by reflecting on experiential learning opportunities and research.

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.

Assessments have been updated to align with the new USyd assessment framework and to focus on more formative feedback.

Additional information

Business School Policies

Disclaimer

Important: the University of Sydney regularly reviews units of study and reserves the right to change the units of study available annually. To stay up to date on available study options, including unit of study details and availability, refer to the relevant handbook.

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

Use of generative artificial intelligence (AI)

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

BWIL6573: Job Smart Edge

Intensive September - October, 2026 [Block mode] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

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