Outline

Overview

This unit introduces students to the fundamental principles that underlie professional practice in computing. It lays the foundation for later studies, and presents to the students challenges common to a multidisciplinary IT environment. The subject also provides students with the opportunity to develop important attributes such as communication skills, an understanding of professional ethics, and of working as a part of a team. Tool use is an important aspect of this unit: students are required to learn to use tools for planning and completing work, managing artefacts including reports, and communicating within the team. A selection of guest speakers will address students on different career paths. Dalyell students may enrol in ENGD1000 Building a Sustainable World in place of INFO1111

Unit details and rules

Academic unit	Computer Science
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	ENGG1805 or ENGG1111 or ENGD1000 or INFO5990
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Simon Poon, simon.poon@sydney.edu.au
Lecturer(s)	Simon Poon, simon.poon@sydney.edu.au
	Hazem El-Alfy, hazem.elalfy@sydney.edu.au
	Eduardo Velloso, eduardo.velloso@sydney.edu.au
Tutor(s)	Daniel Friedrich, d.friedrich@sydney.edu.au
Tutor(s)	Skye Kim, skye.kim@sydney.edu.au

Assessment

The census date for this unit availability is 31 March 2025

Details
Criteria

Type	Description	Weight	Due	Length
Supervised exam ?	Knowledge Task 2A (Advanced) - Final exam Final exam (pre-req: Knowledge Task 1 = Strong)	0%	Formal exam period	1 hour
Outcomes assessed:
Oral exam ?	Knowledge Task 2B (Advanced) - Oral exam Oral exam (pre-req: Final Exam = OK)	0%	Formal exam period	20 minutes (oral)
Outcomes assessed:
Assignment	Skills Task 1 (Foundation) Group project with individual sections, (Foundation Skills, 3 submissions)	0%	Multiple weeks	13 weeks
Outcomes assessed:
Assignment	Skills Task 2 (Advanced) Group project with individual sections, (Advanced Skills, 3 submissions)	0%	Multiple weeks	13 weeks
Outcomes assessed:
Small test	Knowledge Task 1 (Foundation) - Online Quiz Mandatory exam to assess Knowledge stream	0%	Multiple weeks	20 mins
Outcomes assessed:
Small continuous assessment	Self-learning Task 1 (Foundation) Learning of selected technology (Self-Learning - Foundation, 3 submissions)	0%	Multiple weeks	13 weeks
Outcomes assessed:
Small continuous assessment	Self-learning Task 2 (Advanced) Learning of selected technology (Self-Learning - Advanced, 3 submissions)	0%	Multiple weeks	13 weeks
Outcomes assessed:
Participation	Weeks 1-3 participation rating Assessment of participation in class activities #earlyfeedbacktask	0%	Week 03	3 weeks
Outcomes assessed:
= hurdle task ? = group assignment ? = AI allowed ? = early feedback task ?

Early feedback task

This unit includes an early feedback task, designed to give you feedback prior to the census date for this unit. Details are provided in the Canvas site and your result will be recorded in your Marks page. It is important that you actively engage with this task so that the University can support you to be successful in this unit.

Assessment summary

The assessment in this unit is structured in an unusual way. There are three different assessment themes: Knowledge; Skills; and Self-Learning. For each theme, you will have multiple opportunities to submit an initial foundation task. If/when the foundation task is completed to a high level, you can move on to attempting the advanced task.

No marks are awarded for the tasks. Instead, they are each assessed as: not OK; OK; almost Strong; Strong. Your final result in the unit will then be determined based on the levels achieved in each task. e.g. Achieving an OK in the Knowledge and Skills foundation tasks will result in a 50P. Achieving a Strong in all three foundation tasks will result in a 70C.

No simple extension is applicable in this unit given multiple submissions are built-in for knowledge tests and assignment submissions.

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.

Use of generative artificial intelligence (AI) and automated writing tools

Except for supervised exams or in-semester tests, you may use generative AI and automated writing tools in assessments unless expressly prohibited by your unit coordinator.

For exams and in-semester tests, the use of AI and automated writing tools is not allowed unless expressly permitted in the assessment instructions.

The icons in the assessment table above indicate whether AI is allowed – whether full AI, or only some AI (the latter is referred to as “AI restricted”). If no icon is shown, AI use is not permitted at all for the task. Refer to Canvas for full instructions on assessment tasks for this unit.

Your final submission must be your own, original work. You must acknowledge any use of automated writing tools or generative AI, and any material generated that you include in your final submission must be properly referenced. You may be required to submit generative AI inputs and outputs that you used during your assessment process, or drafts of your original work. Inappropriate use of generative AI is considered a breach of the Academic Integrity Policy and penalties may apply.

The Current Students website provides information on artificial intelligence in assessments. For help on how to correctly acknowledge the use of AI, please refer to the  AI in Education Canvas site.

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:

The usual University policy is that you are penalised 5% per day for late submissions (up to a maximum of 10 days). Since the assessment tasks in this unit don't have marks awarded (instead you achieve progressively higher levels) applying a percentage penalty doesn't make sense. Instead, you are penalised 0.5 marks per day for late submissions. These penalties accrue through the semester, and are applied to your final grade.

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.

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	1. Nature of computing 2. Administration	Lecture and tutorial (3 hr)
Week 02	1. Core skills 2. CLIs and Scripts	Lecture and tutorial (3 hr)
Week 03	1. Communications 2. LaTeX	Lecture and tutorial (3 hr)
Week 04	1. Technology stacks 2. make	Lecture and tutorial (3 hr)
Week 05	1. Version control 2. github	Lecture and tutorial (3 hr)
Week 06	1. Problem Solving 2. Debugging	Lecture and tutorial (3 hr)
Week 07	1. IP and Ethics 2. Review	Lecture and tutorial (3 hr)
Week 08	Majors: Computer Science	Lecture and tutorial (3 hr)
Week 09	Majors: Software Development	Lecture and tutorial (3 hr)
Week 10	Majors: Cyber Security	Lecture and tutorial (3 hr)
Week 11	Majors: Data science	Lecture and tutorial (3 hr)
Week 12	Majors: Others....	Lecture and tutorial (3 hr)
Week 13	Review	Lecture and tutorial (3 hr)

Attendance and class requirements

It is expected that students attend all tutorials that occur during periods when group projects are underway.

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

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. analyse and evaluate situations where ethical issues arise within IT professional activities, and relate the choices to ethical frameworks as well as professional standards and requirements
LO2. explain the principles behind problem-solving in a professional IT environment and apply these to example problems
LO3. explain the theoretical concepts and principles of intellectual property and its protection
LO4. explain and give examples of the principles governing participation in a professional IT context including codes of practice, professional standards and legislative and statutory requirements
LO5. track issues, and manage group work and communication for a small scale project using project methodologies and tools, as well as evaluate the limits and capabilities of the project tools
LO6. negotiate and evaluate team responsibilities and team processes with respect to the various points of view of team members
LO7. execute defined project tasks within a predefined project context in small diverse teams
LO8. carry out the processes of the small team project according to professional codes and principles and then compare the process to what one would expect to find in a large-scale professional IT environment
LO9. confidently use IT specific language and concepts in communication
LO10. formulate queries about a particular topic, research, retrieve relevant information from digital and other sources, evaluate it for reliability and synthesise it for a task, as well as adapt communication to meet the format and needs of the audience (including producing a written report and delivering an oral presentation)
LO11. explain and give examples of the scope of activities and responsibilities of professionals working in the areas of information technology and how these are described by the degree major options
LO12. reflect on, and assess, own skills and attributes to create a professional development plan.

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.

The structure of the assessment (and hence much of the learning) in INFO1111 is somewhat different from most units, and was run as a trial in 2021 and then refined in 2022 and 2023. The feedback indicated that some aspects of this worked really well (for example, many students really appreciated the opportunity to focus on topics of interest to them in the self-learning) and other aspects didn't work as well (for example, many students felt that being able to submit work at various points in the semester meant that they didn't have a clear deadline). Based on feedback, a number of improvements will be made for 2024. - Simplify the assessment structure and how the result are then used to derive a final unit result; - Clearer rubrics associated with the level of performance required in each assessment task; - Provide more specific skills development associated with how to approach your own self-learning.

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

Early feedback task

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI) and automated writing tools

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

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

INFO1111: Computing 1A Professionalism

Semester 1, 2025 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Early feedback task

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI) and automated writing tools

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

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links