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Unit outline_

ANSC3888: Production Systems Analysis

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

Our ever-changing world requires knowledge that extends across multiple disciplines. The ability to identify and explore interdisciplinary links in livestock production is a crucial skill for emerging professionals and researchers alike. This unit presents the opportunity to bring together the concepts and skills you have learnt in livestock production and agriculture, and apply them to a real-world problem. For example, you will work on a project analysing a selected livestock production system following a whole system approach, and understanding drivers and trends shaping the business. This will allow you to identify limitations to livestock productivity, sustainability and profitability which can then be put in a business plan to reduce or overcome the impact of these limitations. Working on a multidisciplinary team will allow you to solve these limitations with a holistic approach proposing improvements across the system's components (soils, pastures, crops, animals, economics, technological advances, amongst others). In this unit, you will continue to understand and explore disciplinary knowledge around Animal Production, while also meeting and collaborating with students from across the University through project-based learning; identifying and solving problems of livestock production systems, collecting and analysing data and communicating your findings to a diverse audience. All of these skills are highly valued by employers. This unit will foster the ability to work in interdisciplinary teams, and this is essential for both professional and research pathways in the future.

Unit details and rules

Academic unit Life and Environmental Sciences Academic Operations
Credit points 6
Prerequisites
? 
AVBS2004 and GEGE2X01
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

Familiarity with data analysis and animal handling.

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Luciano Gonzalez, luciano.gonzalez@sydney.edu.au
Lecturer(s) Wendy Muir, wendy.muir@sydney.edu.au
Sonia Liu, sonia.liu@sydney.edu.au
Sergio Garcia, sergio.garcia@sydney.edu.au
Jeffrey Downing, jeff.downing@sydney.edu.au
Type Description Weight Due Length
Assignment group assignment Consultant's report
Written assignment, final consultant's report
30% Formal exam period 2000-3000 words
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7
Skills-based evaluation Viva voice exam
Viva voice exam
30% Formal exam period 10 min
Outcomes assessed: LO1 LO7 LO6 LO5 LO4 LO3 LO2
Assignment Problem/project conceptualisation
Status of the problem report: conceptualisation of project
20% Week 05 500-1000 words
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7
Presentation group assignment Consultant's presentation
Oral presentation
20% Week 12 30 minutes
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7
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 code

Result name

Mark range

Description

HD

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.

DI

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.

CR

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.

PS

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.

FA

Fail

0 - 49

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

AF

Absent fail

0 - 49

When you haven’t completed all assessment tasks or met the attendance requirements.

CN

Cancelled

No mark

When your enrolment has been cancelled.

DC

Discontinued not to count as failure

No mark

When you discontinue a unit after the relevant census date but before the DC deadline.

DF

Discontinue – fail

No mark

When you discontinue a unit after the DC deadline but before the DF deadline

FR

Failed requirements

No mark

When you don’t meet the learning outcomes to a satisfactory standard, for units which are marked as either Satisfied requirements or Failed requirements.

SR

Satisfied requirements

No mark

When you meet the learning outcomes to a satisfactory standard, for units which are marked as either Satisfied requirements or Failed requirements.

WD

Withdrawn

No mark

When you discontinue a unit before the relevant census date. WD grades do not appear on your academic transcript

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.

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 Holistic farm business management Online class (2 hr) LO1 LO3 LO4
Starting with consultancy and data collection Online class (3 hr) LO1 LO2 LO3 LO4
Week 02 Key performance indicators for the beef industry Online class (2 hr) LO1 LO3 LO4
Calculation of key performance indicators Online class (3 hr) LO1 LO2 LO3 LO4 LO5
Week 03 Key perfromance indicators for the poultry and egg industry Lecture (2 hr) LO1 LO2 LO3
Understanding the research question and Developing a consultant report Online class (3 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 04 Key performance indicators for the wool industry Online class (2 hr) LO1 LO2 LO3 LO4
Team formation and building Online class (3 hr) LO1 LO5
Week 05 Key performance indicators for the pork industry Online class (2 hr) LO1 LO3 LO4
Week 06 KPI’s for the dairy industry Online class (2 hr) LO1 LO3 LO4
Project work – assembling data Tutorial (3 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 07 Virtual field trip Online class (4 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 08 Project work Independent study (5 hr) LO3 LO4 LO5 LO6 LO7
Week 09 Project work Independent study (5 hr) LO1 LO2 LO3 LO4 LO5 LO6
Week 10 Project work Independent study (5 hr) LO5 LO6 LO7
Week 11 Project work Independent study (5 hr) LO3 LO4 LO5 LO6 LO7
Week 12 Consultant's presentation Online class (5 hr) LO5 LO6 LO7

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.

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. apply disciplinary knowledge to find and define problems in an interdisciplinary context
  • LO2. analyse data using modern information technologies and digital skills
  • LO3. create an investigation strategy, explore solutions, discuss approaches and predict outcomes
  • LO4. solve problems related to production systems based on evidence-based analysis
  • LO5. demonstrate integrity, confidence, personal resilience and the capacity to manage challenges, both individually and in teams
  • LO6. collaborate with diverse groups and across cultural and disciplinary boundaries
  • LO7. communicate project outcomes effectively to a broad audience

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.

This is the first time this unit has been 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.