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Unit outline_

INFO4001: Thesis A

Semester 2, 2022 [Supervision] - Remote

Students enrolled in the Bachelor of Advanced Computing (BAdvComp) programs study various advanced aspects of Information Technology. The program may include lectures, tutorials, seminars and practicals. They will undertake a capstone project. Assessment will include the project and may include examinations and classwork.

Unit details and rules

Academic unit Computer Science
Credit points 6
Prerequisites
? 
INFO3333 and {completion of the requirements of a major in Computational Data Science [DATA3888 AND 12cp of (COMP3027 OR COMP3927 OR COMP3308 OR COMP3608 OR DATA3404 OR DATA3406)] or Computer Science [(COMP3027 OR COMP3927) AND (COMP3888 OR COMP3988) AND 6cp of (COMP3109 OR COMP3221 OR COMP3308 OR COMP3608 OR COMP3419 OR COMP3520)] or Cybersecurity (CSEC3616 AND ELEC3506 AND COMP3221 AND CSEC3888) or Information Systems (ISYS3401 AND (ISYS3402 OR INFS3050) AND ISYS3888) or Software Development [SOFT3202 AND (SOFT3410 OR INFO3315) AND SOFT3888]}
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

None

Available to study abroad and exchange students

No

Teaching staff

Coordinator Sue Chng, sue.chng@sydney.edu.au
Type Description Weight Due Length
Honours thesis Thesis
Project work contributes to final thesis.
100% Progressive N/A
Outcomes assessed: LO1 LO2 LO3
Assignment Project Analysis Brief
Your analysis and plans to conduct the project.
0% Week 06
Due date: 11 Sep 2022 at 23:59
5 pages
Outcomes assessed: LO1 LO2
Assignment Progress Report
An initial draft of the thesis.
0% Week 13
Due date: 06 Nov 2022 at 23:59
20 pages
Outcomes assessed: LO3

Assessment summary

Project analysis Brief: A document to present findings and plans for the project. This document is to be presented to your supervisor during a supervision meeting and submitted to Canvas. The latest date to complete this task is Week 6.

Progress Report: The initial draft of your thesis that presents your chosen approach, preliminary findings and plans for the remaining weeks of the project, including INFO4002.  This should be presented to your supervisor during a supervision meeting and submitted to Canvas. The latest date to complete this task is Week 13.

Thesis: Each report is assessed by two people who meet the following requirements:

  1. neither of them have played a supervisory role in the project
  2. at least one of them is an academic staff from the School of Computer Science (usually both examiners meet this requirement)
  3. one of them is from the area of the project and is knowledgeable about the topic of the report
  4. one of them is from outside the project topic area

Detailed information is available in Canvas. 

Students who commence their degree in 2019 or earlier: You need to also complete INFO4002, and the same mark applies to both INFO4001 and INFO4002.

Students who commence their degree in 2020 or later AND are NOT enrolled in the Honours program: You need to also complete INFO4002, and the same mark applies to both INFO4001 and INFO4002

Students who commence their degree in 2020 or later AND are enrolled in the Honours program: You will need to complete INFO4911 instead of INFO4001. See the unit outline for INFO4911 for more information.

 

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.

Penalty clause:

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

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
Weekly Project work - own time. Project (12 hr) LO1 LO2 LO3

Attendance and class requirements

Students are expected to update their supervisor on their progress regularly.

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

Berndtsson, Hansson, J., Olsson, B., & Lundell, B. (2008). Thesis Projects: A Guide for Students in Computer Science and Information Systems. Springer London, Limited.

 

All readings for this unit can be accessed through the Reading List, available on Canvas. 

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. Make an original contribution to the field
  • LO2. Carry out an extended supervised capstone project
  • LO3. Write a thesis presenting and evaluating one's original contribution, in a style suitable for the academic literature

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 significant changes were made to the structure of the unit.

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.