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Unit outline_

COMP9001: Introduction to Programming

Semester 1, 2020 [Normal day] - Camperdown/Darlington, Sydney

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
? 
None
Assumed knowledge
? 

None

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator John Stavrakakis, john.stavrakakis@sydney.edu.au
Tutor(s) Gain Kim, gain.kim@sydney.edu.au
Michelle Wang, michelle.wang1@sydney.edu.au
Cindy Leong, cindy.leong@sydney.edu.au
Victor Kuo, victor.kuo1@sydney.edu.au
Andrew Xu, andrew.xu@sydney.edu.au
Patrick Hermawan, pher9239@uni.sydney.edu.au
Type Description Weight Due Length
Final exam Final Examination
Closed book. Paper examination
50% Formal exam period 2 hours
Outcomes assessed: LO1 LO11 LO10 LO9 LO8 LO7 LO6 LO5 LO4 LO3 LO2
Tutorial quiz Quiz 1
Paper quiz
5% Week 04 TBA: 30 ~ 60 minutes
Outcomes assessed: LO1 LO11 LO7 LO6 LO5 LO4 LO3 LO2
Tutorial quiz Quiz 2
Paper quiz
10% Week 08 TBA: 30 ~ 60 minutes
Outcomes assessed: LO1 LO11 LO10 LO9 LO7 LO6 LO5 LO4 LO3 LO2
Assignment Assignment Milestone
Programming. Automatic feedback.
5% Week 11
Due date: 17 May 2020 at 23:59
10 working days
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO9 LO11
Assignment Assignment
Programming
10% Week 13
Due date: 31 May 2020 at 23:59
15 working days
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO9 LO10 LO11
Small continuous assessment Weekly tasks
Weekly tasks to be completed and evaluated with a tutor
10% Weekly TBA: 10 ~ 60 minutes
Outcomes assessed: LO1 LO11 LO10 LO9 LO7 LO6 LO5 LO4 LO3 LO2
Small continuous assessment Evaluation session
Weekly oral examination
10% Weekly 4-5 minutes within the 1 hour allocated
Outcomes assessed: LO1 LO11 LO10 LO9 LO8 LO6 LO5

Assessment summary

  • Evaluation session: weekly oral examination of student by way of asking questions and receiving answers.
  • Weekly task: During the lab, the tutor will check and/or grade the students weekly task.
  • Assignments: Demonstrating programming ability from a given problem description. Produce a set of test cases for a given problem description
  • Quiz: Test both knowledge and skills of course materials in the semester thus far. Attendance during tutorial. Pen and paper, no computers to be used.
  • Final Exam: The final exam covers all aspects 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.

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

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.

Assignments. The tutors will provide further feedback to students about correctness, style and testing.

Quizzes. Tutors mark the quiz and provide annotations where needed.

Evaluation sessions give the student instant feedback as it is an oral assessment.

Weekly task may require online submission and checking by the tutor. It may also be another format as directed in the preceding week. Students will recieve feedback about their task from their tutor. Where it is an online computer task, it can be automatically graded and further feedback is provided by the grading software. 

 

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:

Late penalty for any online assessment is 25% per day. It is a cap based penalty: 1 day late, maximum attainable mark is 75%. 2 days late, maximum attainable mark is 50%. 3 days late, maximum attainable mark is 25%. Failure to attend for any assessment that is not an assignment will award zero marks, unless special consideration is granted. The pass requirement for this course is: at least 50% in the written examination to qualify for a pass in this course, AND at least 40% in all other assessments that are not the final examination, AND at least 50% final mark overall

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 LO7 LO8 LO9 LO10 LO11
Programming basics Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Week 02 1. Data types; 2. Expressions and variables; 3. The underlying memory model Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
1. Data types; 2. Variables, operators and expressions Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Week 03 Conditionals and loops Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Control flow: Branching and loops Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Week 04 1. Defining and iterating arrays; 2. Collections of objects Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
1. Addressable memory; 2. Arrays, collections, testing Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Week 05 Functions Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
1. Functions; 2. Basis of program design process; 3. Documentation and style Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Week 06 1. Working with file input and output; 2. Exceptions Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
1. Files and basic input/output; 2. Exception handling Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Week 07 1. Testing; 2. Software design process Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Writing tests and testing programs Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Week 08 Searching collections and error handling Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Programming idioms Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Week 09 Creating and working with aggregate data structures and their operations Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
1. Modular programming; 2. Defining datatypes using aggregate studctures Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Week 10 Test driven development and debugging Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
1. Idioms 2; 2. Testing and Debugging Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Week 11 Reading, writing and tracing recursive code Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Recursion Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Week 12 Defining and application of multidimensional arrays Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Data types and multidimensional arrays Lecture and tutorial (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
Week 13 Revision Computer laboratory (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11
1. Course review; 2. Final examination overview Lecture (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7 LO8 LO9 LO10 LO11

Attendance and class requirements

The course website on edstem.org will contain information, including important announcements. Teaching staff will be communicating to all students and it is considered part of the course. Students are expected to regularly visit this website to know these announcements and information concerning format and schedule of assessment.

Attendance requirements for assessments: Failure to attend the scheduled time and location will result in a grade of zero, unless special consideration is granted.

The pass requirement for this course is:

  • At least 50% in the written examination to qualify for a pass in this course, AND
  • At least 40% in all other assessments that are not the final examination, AND 
  • At least 50% final mark overall

About the seminar:

  • Attendance is not compulsory
  • It will not contain new content needed to complete this course
  • Seminar has value to those who need more help with reviewing material and programming exercises

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 knowledge 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 global's, 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 and 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

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

Students endorsed having weekly activities. They found them more rewarding for their learning and allowed them to keep up with the course. We have re-introduced them.

Every week students must:

  • 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)
  • Attend and answer questions in the weekly Evaluation session (as timetabled)
  • Complete the weekly Online task (for labs starting week 2)
  • Prepare for the Lab by reviewing reading, lecture and lab questions 
  • Attend and participate in weekly Lab with tutor(as timetabled)

Additionally:

  • Students should ask questions on edstem.org
  • Students are encouraged to attend and/or watch the OPTIONAL seminar (Tuesday morning)

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.