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Unit outline_

INFO1110: Introduction to Programming

Semester 2, 2021 [Normal day] - Remote

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 John Stavrakakis, john.stavrakakis@sydney.edu.au
Tutor(s) Xinwei Luo, xinwei.luo@sydney.edu.au
Andrew Xu, andrew.xu@sydney.edu.au
Type Description Weight Due Length
Final exam (Take-home short release) Type D final exam Final Examination
3 hours computer exam
50% Formal exam period 3 hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Assignment Assignment 1
Write a complete program from problem description
10% Week 04
Due date: 05 Sep 2021 at 23:59
14 days
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO10 LO11
Skills-based evaluation Quiz 1
Explain, trace, write about programming problems.
10% Week 07
Due date: 20 Sep 2021 at 16:00
30 minutes
Outcomes assessed: LO1 LO11 LO10 LO6 LO5 LO3 LO2
Skills-based evaluation Quiz 2
Explain, trace, write about programming problems.
10% Week 10
Due date: 18 Oct 2021 at 16:00
30 minutes
Outcomes assessed: LO1 LO11 LO10 LO7 LO6 LO5 LO4 LO3 LO2
Assignment Assignment 2
Write a complete program from problem description
20% Week 12
Due date: 07 Nov 2021 at 23:59
14 days
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO9 LO10 LO11
Type D final exam = Type D final exam ?

Assessment summary

Assignments: 
To be completed individually throughout the semester.  Assignments may require submission of code, flowcharts, tests, reports, or oral presentations. Format and submission details of assignments to be provided on release.

Quizzes:

Testing knowledge of course contents. Scheduled for a specific time in semester.

Final examination:
The final exam can cover any aspect of the course. Demonstrate knowledge in procedural programming. Reading and tracing through short programs. Writing short programs. Writing test cases and debugging with existing test cases. The final exam is a computer examination held during the examination period.  

Detailed information for each assessment can be found on the course website: edstem.org

Special consideration
Approved special consideration will be granted an extension to complete the assignment and may additionally be examined in an oral assessment, based on the assignment contents, that will contribute to the grade of the assignment.

Conditions for the pass in this course:
- At least 40% in the assessment grade
- At least 40% in the computer examination
- At least 50% total

In order to pass this unit, 40% in the final exam. A student must also achieve an overall final mark of 50 or more. Any student not meeting these requirements may be given a maximum final mark of no more than 45 regardless of their average. 

Use of language translation tools for all online assessments is forbidden. All answers must be provided in the English language, including code comments.

Additionally, for this course, students may be asked for further development of their assessments if they fail to attend at least 80% of their tutorials.

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.

The tutor will provide feedback for the weekly tutorial and will provide further feedback to students about correctness, style and testing of their assignments.

Automatic testing provides further feedback.

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 1. Introduction to the unit; 2. Fundamental concepts; 3. First program. Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO10 LO11
1. Programming basics; 2. Online face to face. Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO10 LO11
Week 02 1. Data types; 2. Variables, operators and expressions; 3. Branching Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO10 LO11
1. Data types; 2. Expressions and variables; 3. The underlying memory model. Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO10 LO11
Week 03 1. Control Flow: Branching and loops Lecture (2 hr) LO1 LO3 LO4 LO5 LO6 LO10 LO11
1. Control Flow: Branching and loops Computer laboratory (2 hr) LO1 LO3 LO4 LO5 LO6 LO7 LO10 LO11
Week 04 1. Array concept of addressable memory; 2. Lists and loops; 3. Further flow control Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO10 LO11
1. Defining and iterating arrays; 2. Collections of objects. Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO10 LO11
Week 05 1. Basis of program design process; 2. Documentation and style Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO10 LO11
1. Writing small programs; 2. Documentation and style Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO10 LO11
Week 06 1. Functions; 2. Testing Lecture (2 hr) LO1 LO2 LO3 LO5 LO6 LO9 LO10 LO11
1. Functions; 2. Testing Computer laboratory (2 hr) LO1 LO2 LO3 LO5 LO6 LO9 LO10 LO11
Week 07 1. Files and basic input/output; 2. Exception handling Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO10 LO11
1. Working with file input and output; 2. Exceptions. Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO9 LO10 LO11
Week 08 1. More list and for loop; 2. Programming idioms Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO9 LO10 LO11
1. Searching collections; 2. Error handling; 3. Further idioms Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO9 LO10 LO11
Week 09 1. Testing; 2. Software design process Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO9 LO10 LO11
1. Writing tests; 2. Testing programs Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO9 LO10 LO11
Week 10 1. Modular programming; 2. Defining datatypes using aggregate structures Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO9 LO10 LO11
1. Creating and working with aggregate data structures and their operations. Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO9 LO10 LO11
Week 11 1. Recursion Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
1. Reading, writing and tracing recursive code. Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Week 12 1. Multidimensional arrays Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO9 LO10 LO11
1. Problems with 2D structures Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO9 LO10 LO11
Week 13 1. Course review; 2. Final examination overview Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
1. Revision. Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11

Attendance and class requirements

Course websites:

Canvas and Ed are both used in this course for separate purposes. Students are encouraged to engage with the discussions and support on Ed for their learning.

Students are expected to regularly visit these websites to learn of announcements and information concerning format and schedule of assessment. Canvas is a website that will be used to disseminate the lecture recordings and for publishing of results.

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

All readings for this unit can be accessed through the Library eReserve, available on Canvas.

  • Robert Sedgewick, Kevin Wayne, Robert Dondero  – Introduction to Programming in Python: An Interdisciplinary Approach. Pearson Higher Ed USA, 2015. 9780134076430

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
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

Alignment with Competency standards

Outcomes Competency standards
LO2
Engineers Australia Curriculum Performance Indicators - EAPI
1.2. Tackling technically challenging problems from first principles.
2.2. Application of enabling skills and knowledge to problem solution in these technical domains.
LO3
Engineers Australia Curriculum Performance Indicators - EAPI
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.
LO4
Engineers Australia Curriculum Performance Indicators - EAPI
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.
LO5
Engineers Australia Curriculum Performance Indicators - EAPI
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.
LO6
Engineers Australia Curriculum Performance Indicators - EAPI
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.
LO7
Engineers Australia Curriculum Performance Indicators - EAPI
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.
LO8
Engineers Australia Curriculum Performance Indicators - EAPI
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.
LO9
Engineers Australia Curriculum Performance Indicators - EAPI
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 - EAPI
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 - EAPI
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.

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

There is a slower uptake of functions section where students felt the course ramp up quickly.

Every week students should:

  • Read the required sections of literature
  • Attend and take notes for the Live lecture (Mondays)
  • Watch and take notes for the Online lecture (via Canvas website)
  • Complete the weekly Lesson for Lecture
  • Prepare for the Tutorial by reviewing reading, lecture and tutorial questions 
  • Complete the weekly Tutorial before it commences (starting week 2)
  • Attend and participate in weekly Tutorial with tutor (as timetabled)

Additionally:

  • Students should ask questions on Ed
  • Students should engage with their teacher for feedback in their tutorial

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.