Outline

Overview

This unit is an essential starting point for software developers, IT consultants, and computer scientists to build their understanding of principle computer operation. Students will obtain knowledge and skills with procedural programming. Crucial concepts include defining data types, control flow, iteration, functions, recursion, the model of addressable memory. Students will be able to reinterpret a general problem into a computer problem, and use their understanding of the computer model to develop source code. This unit trains students with software development process, including skills of testing and debugging. It is a prerequisite for more advanced programming languages, systems programming, computer security and high performance computing.

Unit details and rules

Academic unit	Computer Science
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	INFO1910 or INFO1103 or INFO1903 or INFO1105 or INFO1905 or ENGG1810
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Ashlee Pearson, ashlee.pearson@sydney.edu.au
Lecturer(s)	Bob Kummerfeld, bob.kummerfeld@sydney.edu.au
	Ashlee Pearson, ashlee.pearson@sydney.edu.au
	Hazem El-Alfy, hazem.elalfy@sydney.edu.au

Assessment

The census date for this unit availability is 2 September 2024

Details
Criteria

Type	Description	Weight	Due	Length
Supervised exam ?	Final Examination (Advanced Task) Advanced Task 2. (pre-req: >C on Assignment Part C/Extension Task)	0%	Formal exam period	2 hours
Outcomes assessed:
Tutorial quiz	Quiz 1 (Essentials Task) Online invigilated quiz in week 4 & 6 labs.	0%	Multiple weeks	30 minutes each.
Outcomes assessed:
Tutorial quiz	Quiz 2 (Essentials Task) Online invigilated quiz in week 10 & 12 labs. (pre-req: >C on Quiz 1)	0%	Multiple weeks	45 minutes each.
Outcomes assessed:
Assignment	Assignment Part D (Advanced Task) Computer programming problems (1 submission, pre-req = >C in Part C)	0%	Multiple weeks	4 weeks
Outcomes assessed:
Assignment	Assignment Part C (Extension Task) Computer programming problems (up to 3 submissions, pre-req = >C in Part B)	0%	Multiple weeks	7 weeks
Outcomes assessed:
Assignment	Assignment Part B (Essentials Task) Computer programming problems (Up to 3 submissions, pre-req = >C in Part A)	0%	Multiple weeks	10 weeks
Outcomes assessed:
Assignment	Assignment Part A (Essentials Task) Computer programming problems (Up to 4 submissions)	0%	Multiple weeks	10 weeks
Outcomes assessed:
Participation	Early Feedback Task #earlyfeedbacktask Completion of online modules and lab participation	0%	Week 03	3-5 hours
Outcomes assessed:
= hurdle 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 3 different assessment types – quizzes, assignments and early feedback task.

For each quiz (quiz 1 and quiz 2), we will count your best attempt of 2 towards your final grade.

There are 4 assignments, Part A, Part B, Part C and Part D. Each assignment must be awarded a competent before you can move onto the next assignment. E.g. You must achieve competent in Part A before you may submit Part B. You will have multiple opportunities to submit a task until you are deemed competent.

No marks are awarded for any quiz or assessment. Instead, they are assessed as: NSI – needs significant improvement, NI – needs improvement, C – competent, or C* - above competent. Your final result in the unit will then be determined based on the levels achieved in the tasks completed. A 50P Pass is equivalent to a C – competent in Quiz 1 + Quiz 2 + Assignment Part A + Assignment Part B.

To pass this unit, students must

Complete all Essentials tasks to a minimum standard of ‘Competent’ (Quiz 1, Quiz 2, Assignment Part A, Assignment Part B) .

Attend and actively participate in a minimum of 8 lab classes.

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.

For more information see sydney.edu.au/students/guide-to-grades.

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:

The usual University policy is that you are penalized 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. After ten calendar days late, a feedback band of unsatisfactory (equivalent to a zero for the assignment) will also be awarded. 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.

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.

Support for students

The Support for Students Policy 2023 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 2023. 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	What is a computer program?	Computer laboratory (2 hr)
Week 02	Variables and data types, operators and expressions, comments, input() function, files and folders.	Computer laboratory (2 hr)
Week 03	The if statement, indented blocks, testing and debugging	Computer laboratory (2 hr)
Week 04	Python Containers (list, tuples, dictionaries), testing and debugging	Computer laboratory (2 hr)
Week 05	For loops	Computer laboratory (2 hr)
Week 06	While loops, handling errors	Computer laboratory (2 hr)
Week 07	Python functions and scope	Computer laboratory (2 hr)
Week 08	Input and output	Computer laboratory (2 hr)
Week 09	Classes	Computer laboratory (2 hr)
Week 10	Characters and list comprehensions	Computer laboratory (2 hr)
Week 11	Function parameters, Sets	Computer laboratory (2 hr)
Week 12	Recursive functions	Computer laboratory (2 hr)
Week 13	Numerical python	Computer laboratory (2 hr)
Weekly	Weekly Ed Lessons weeks 1-13. Details in Canvas. This unit of study is designed flexibly to respond to student progress. Each week there will be a series of Ed Lessons posted via Canvas that detail which lessons students should work through in that week to stay 'on track'. The schedule for 'on track' is included below.	Independent study (3 hr)
	Weekly Question and Answer Sessions. 3 options weekly depending on students' progress through Ed Lessons. Details via Canvas.	Seminar (2 hr)
	Each lab will feature a group activity and time to work through exercises from the week's Ed Lessons either as a group or individually. The 'on track' focus of each week is outlined below. Further details via Canvas.	Computer laboratory (2 hr)

Attendance and class requirements

Lab classes are designed to assist students with progressing through the unit and demonstrating competence required to gain marks in this unit. You MUST attend a minimum of 8 out of 13 lab classes. Absence from the class impacts your ability to pass this unit. Failure to meet the attendance requirement will result in a maximum of 45% of the available marks.

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.

At the completion of this unit, you should be able to:

LO1. employ programming style conventions for writing consistently readable code
LO2. design and construct new functionality to existing procedural program or function
LO3. compose a structured algorithmic design to solve the descriptive problem specification
LO4. compose an entire procedural program from descriptive problem specification
LO5. demonstrate an understanding of programming principles, data types, variables and operators, control-flow: simple statement, sequence, if-then-else, while, functions: stack, input/output, reference memory model
LO6. compose, analyse and trace procedural code, scoping/variable lifetime, memory of the stack, references and globals, data types, operations on data types
LO7. construct code cliches for input and manipulating arrays, including maximum, minimum, search or traverse, with actions on each element for counting or summation
LO8. construct and assess code for recursively-defined numerical functions, and for recursively described array manipulations
LO9. apply testing methods and assess programs through debugging with the ability to write a set of tests for a small program or function
LO10. explain compilation process and debugging mechanism
LO11. use standard library functions

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

Alignment with Competency standards

Outcomes	Competency standards
	Engineers Australia Curriculum Performance Indicators - 1.2. Tackling technically challenging problems from first principles. 2.2. Application of enabling skills and knowledge to problem solution in these technical domains.
	Engineers Australia Curriculum Performance Indicators - 1.2. Tackling technically challenging problems from first principles. 2.2. Application of enabling skills and knowledge to problem solution in these technical domains. 3.3. Creativity and innovation.
	Engineers Australia Curriculum Performance Indicators - 1.1. Developing underpinning capabilities in mathematics, physical, life and information sciences and engineering sciences, as appropriate to the designated field of practice. 1.2. Tackling technically challenging problems from first principles. 2.2. Application of enabling skills and knowledge to problem solution in these technical domains. 2.4. Advanced knowledge and capability development in one or more specialist areas through engagement with: (a) specific body of knowledge and emerging developments and (b) problems and situations of significant technical complexity. 3.3. Creativity and innovation. 4.1. Advanced level skills in the structured solution of complex and often ill defined problems.
	Engineers Australia Curriculum Performance Indicators - 1.1. Developing underpinning capabilities in mathematics, physical, life and information sciences and engineering sciences, as appropriate to the designated field of practice. 2.1. Appropriate range and depth of learning in the technical domains comprising the field of practice informed by national and international benchmarks.
	Engineers Australia Curriculum Performance Indicators - 1.1. Developing underpinning capabilities in mathematics, physical, life and information sciences and engineering sciences, as appropriate to the designated field of practice. 1.2. Tackling technically challenging problems from first principles. 2.2. Application of enabling skills and knowledge to problem solution in these technical domains.
	Engineers Australia Curriculum Performance Indicators - 1.1. Developing underpinning capabilities in mathematics, physical, life and information sciences and engineering sciences, as appropriate to the designated field of practice. 1.2. Tackling technically challenging problems from first principles. 2.2. Application of enabling skills and knowledge to problem solution in these technical domains. 3.1. An ability to communicate with the engineering team and the community at large.
	Engineers Australia Curriculum Performance Indicators - 1.1. Developing underpinning capabilities in mathematics, physical, life and information sciences and engineering sciences, as appropriate to the designated field of practice. 1.2. Tackling technically challenging problems from first principles. 2.2. Application of enabling skills and knowledge to problem solution in these technical domains. 3.3. Creativity and innovation.
	Engineers Australia Curriculum Performance Indicators - 1.1. Developing underpinning capabilities in mathematics, physical, life and information sciences and engineering sciences, as appropriate to the designated field of practice. 1.2. Tackling technically challenging problems from first principles. 2.1. Appropriate range and depth of learning in the technical domains comprising the field of practice informed by national and international benchmarks. 2.2. Application of enabling skills and knowledge to problem solution in these technical domains. 3.1. An ability to communicate with the engineering team and the community at large. 3.2. Information literacy and the ability to manage information and documentation. 5.4. Skills in the selection and application of appropriate engineering resources tools and techniques, appreciation of accuracy and limitations;. 5.7. Proficiency in appropriate laboratory procedures; the use of test rigs, instrumentation and test equipment. 5.8. Skills in recognising unsuccessful outcomes, sources of error, diagnosis, fault-finding and re-engineering.
	Engineers Australia Curriculum Performance Indicators - 1.1. Developing underpinning capabilities in mathematics, physical, life and information sciences and engineering sciences, as appropriate to the designated field of practice. 3.1. An ability to communicate with the engineering team and the community at large.
	Engineers Australia Curriculum Performance Indicators - 1.1. Developing underpinning capabilities in mathematics, physical, life and information sciences and engineering sciences, as appropriate to the designated field of practice. 2.2. Application of enabling skills and knowledge to problem solution in these technical domains. 3.1. An ability to communicate with the engineering team and the community at large.

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

This section outlines changes made to this unit following staff and student reviews. This unit has been significantly re-designed during S1C 2024 to be different to most units in response to student feedback. The re-design included rescoping the concepts covered and their ordering, changing the assessment tasks (both type and scope) and adapting the mode of delivery. The re-design has aimed to better support the diversity of student experience with programming (both at the novice and experienced end of the spectrum) and allow for re-submission attempts at most assessments to focus on student learning and continuous feedback.

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

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

Alignment with Competency standards

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect

Current students

INFO1110: Introduction to Programming

Semester 2, 2024 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Early feedback task

Assessment summary

Assessment criteria

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

Alignment with Competency standards

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect