Contents

• Course Details
• Course Summary
• Assumed Knowledge
• Student Learning Outcomes
• Teaching Strategies
• Teaching Rationale
• Student Conduct
• Assessment
• Course Schedule
• Resources for Students
• How to Succeed in this Course
• Course Evaluation and Development

Course Details

Course Code	COMP1010
Course Title	The Art of Computing
Convenor	Sim Mautner cs1010@cse.unsw.edu.au
Admin	Miguel Guthridge Rani Jiang
Classes	Lectures : Monday 10am-12pm and Wednesday 10-12pm online Timetable for all classes
Consultations	See consultations timetable. See forum for general questions.
Units of Credit	6
Course Website	http://cse.unsw.edu.au/~cs1010/23T1/
Handbook Entry	http://www.handbook.unsw.edu.au/undergraduate/courses/current/COMP1010.html

Course Summary

This course aims to provide a grounding in computational thinking for anyone who wants one. It assumes no previous programming background, but does assume that all incoming students have used digital devices, such as tablets and smart phones, for a range of tasks (e.g. social networking, reading, essay writing, etc.). The course will use Python as the programming medium and use real world examples from a variety of domains to motivate understanding.

Assumed Knowledge

Before commencing this course, students should have basic computer skills (using a mouse and keyboard, browsing the web, etc).These are assumed to have been acquired in the courses ...

Student Learning Outcomes

After completing this course, students will:

1. Be able to use a spreadsheet for simple data management tasks.
2. Be able to write Python programs to solve simple computational problems.
3. Be able to solve problems via computer systems.
4. Be able to build simple human-centered interfaces to computers.

This course contributes to the development of the following graduate capabilities:

Graduate Capability	Acquired in
Scholars capable of independent and collaborative enquiry, rigorous in their analysis, critique and reflection, and able to innovate by applying their knowledge and skills to the solution of novel as well as routine problems	Labs & Project
Entrepreneurial leaders capable of initiating and embracing innovation and change, as well as engaging and enabling others to contribute to change	Project
Professionals capable of ethical, self- directed practice and independent lifelong learning	Labs & Project
Global citizens who are culturally adept and capable of respecting diversity and acting in a socially just and responsible way	All work

Teaching Strategies

• Lectures ... introduce concepts, show examples
• Tutorials ... reinforce concepts and provide additional examples
• Lab Work ... provide essential practice in programming
• Project .. allow students to solve a significant problem which matters to them

Teaching Rationale

• Online: Allows for flexibility of student location and timetable. In person tutorial(s) will be available for students who prefer this mode of learning, but will remain subject to UNSW's COVID-19 policies as the situation changes.
• Lectures recorded: We endeavour to record all lectures to allow students to view them at their own pace and easily review, and catch up on missed content.
• Learn by example: Following a small amount of explanation/overview, the content will be predominantly taught through the use of examples in which the concepts and skills of the course are applied.
• Learn by doing: Much like swimming, maths, or playing a musical instrument, computer programming cannot be learnt by solely reading books or watching others do it. It requires hands-on practice. Throughout the course we will offer many opportunities to practice the content taught in class including through the tutorial work and lab work.
• Choose your own project: This course targets a wide variety of students with varying interests and additional skills. To maximise the relevance of this course to this diverse student population and thereby maximise student engagement, students choose their own topic/purpose about which to build their project application.
• Project demonstrations: At the end of term, students informally demonstrate their final product to a small group of their peers. This allows the students to:
  • Demonstrate the full scope of functionality of their projects.
  • Experience what other students have created.
  • Evaluate their peers work and thereby contribute to their critical evaluation of their own work.

Student Conduct

The Student Code of Conduct ( Information , Policy ) sets out what the University expects from students as members of the UNSW community. As well as the learning, teaching and research environment, the University aims to provide an environment that enables students to achieve their full potential and to provide an experience consistent with the University's values and guiding principles. A condition of enrolment is that students inform themselves of the University's rules and policies affecting them, and conduct themselves accordingly.

In particular, students have the responsibility to observe standards of equity and respect in dealing with every member of the University community. This applies to all activities on UNSW premises and all external activities related to study and research. This includes behaviour in person as well as behaviour on social media, for example Facebook groups set up for the purpose of discussing UNSW courses or course work. Behaviour that is considered in breach of the Student Code Policy as discriminatory, sexually inappropriate, bullying, harassing, invading another's privacy or causing any person to fear for their personal safety is serious misconduct and can lead to severe penalties, including suspension or exclusion from UNSW.

If you have any concerns, you may raise them with your lecturer, or approach the School Ethics Officer , Grievance Officer , or one of the student representatives.

Plagiarism is defined as using the words or ideas of others and presenting them as your own. UNSW and CSE treat plagiarism as academic misconduct, which means that it carries penalties as severe as being excluded from further study at UNSW. There are several on-line sources to help you understand what plagiarism is and how it is dealt with at UNSW:

• Plagiarism and Academic Integrity
• UNSW Plagiarism Procedure

Make sure that you read and understand these. Ignorance is not accepted as an excuse for plagiarism. In particular, you are also responsible that your assignment files are not accessible by anyone but you by setting the correct permissions in your CSE directory and code repository, if using. Note also that plagiarism includes paying or asking another person to do a piece of work for you and then submitting it as your own work.

UNSW has an ongoing commitment to fostering a culture of learning informed by academic integrity. All UNSW staff and students have a responsibility to adhere to this principle of academic integrity. Plagiarism undermines academic integrity and is not tolerated at UNSW. Plagiarism at UNSW is defined as using the words or ideas of others and passing them off as your own.

If you haven't done so yet, please take the time to read the full text of

• UNSW's policy regarding academic honesty and plagiarism

The pages below describe the policies and procedures in more detail:

• Student Code Policy
• Student Misconduct Procedure
• Plagiarism Policy Statement
• Plagiarism Procedure

You should also read the following page which describes your rights and responsibilities in the CSE context:

• Essential Advice for CSE Students

Assessment

Item	Topics	Due	Marks	Contributes to
Labs	All topics	Week 1-5, 7-10	20%	1,2,3,4
Project - Proposal		Week 5	10%	2,3,4
Project - Implementation	HCI, Python Programming	Week 10	20%	2,3,4
Project - Demo		Week 10	0%**
Project - Feedback	HCI, Python Programming	Week 10	5%	2,3,4
Final Exam	All topics	Exam period	45%	1,2,3,4

** While the project demonstration is not assessed in itself, failure to attend, demonstrate and respond to questions about one's project may impact the mark awarded for the implementation.

Lab Exercises

In weeks 1-5 and 7-10 you will need to complete a series of lab exercises. These will typically be programming exercises asking you to solve a particular problem in python. To receive marks for these labs you will need to get them marked by your lab coordinator in your allocated lab time in the week after the lab is released. For example, you will need to get the week 1 lab exercises marked in your week 2 lab. If you finish your exercises early, you can, of course, get them marked in the week they were assigned.

Note: It is likely that the total number of marks for labs for the term will be somewhere between 20 and 30. This will only be confirmed in week 10. You can expect each lab mark to be worth between 0.66% of your course grade and 1% of your course grade.

Project

In the project, you will implement an application in Python solving a problem of your choice. You will be assessed on how well you were able to write the code for this app as well as the design of its interface. While available time and skills are limitations that will need to be taken into account, the problem you choose to solve is up to you. Your project idea will need to be approved by your tutor. You are encouraged to work with a partner on your project, especially if you're new to programming, but you are not required to and can complete the project on your own if you wish.

Exam

The final exam will be open book and online. You will have 3 hours to complete it. It will involve programming exercises, but may also include multiple choice and short answer. You will NOT be remotely monitored while taking the exam.

The final exam will be held in person on the CSE lab machines. You will have 3 hours to complete it. It will involve programming exercises, but may also include multiple choice and short answer.

The exam mark is subject to scaling.

Competency Requirement

There is a competency requirement for COMP1010. You must score 50% in the final exam to pass this course. Students with good attempts at other coursework who do not achieve competency on the final exam may be offered an additional opportunity to demonstrate competency.

Course Schedule

Week	Lectures	Labs	Assignments
1	🍓 Course Intro, 🐍 Python: I/O, data types, conditionals, loops	PPF	-
2	🐍 Python: more loops, functions, collections	PPF	-
3	🍓 Project Release 🐍 Python: nested structures, setting up VsCode (tutes), Git	PPF	-
4	📮 HTML 📚 Full Stack: Flask, PyHTML	PPF	-
5	📚 Full Stack: Flask, PyHTML 🐍 Python: modules and libraries (datetime and random) 📚 Full Stack: APIs	Web Apps	Project - Proposal Due (10%)
6	Flexibility Week 🐍 Python: Revision videos	-	-
7	🐍 Python: modules and libraries 🐍 Python: Datastores 📚 Full Stack: Cookies, Serialization	Web Apps	-
8	📮 CSS 🐍 Python: Testing	Web Apps	-
9	📚 App examples based on student questions	Practise Exam	-
10	🐍 Python: extras	Project Reflection	Project - Implementation Due (20%) Project - Feedback Due (5%)

Resources for Students

There are no formal textbooks for this course, but students may find the following FREE book helpful for learning and practicing python programming

• Think Python 2nd Edition by Allen B. Downey, available at https://greenteapress.com/wp/think-python-2e/

Other FREE resources which have been discovered and recommended by past students of this course include:

• An app (free version available on Android and iOS): https://getmimo.com/
• An interactive website: https://www.w3schools.com/python/
• Tutorial-style articles with accompanying exercises: https://pythonbasics.org/

How to Succeed in this Course

Some students find learning to program challenging, at least at first. Here are some guidelines

Primary approach:

• Watch the lectures.
• Attempt the examples demonstrated in the lectures, on your own.
• Attempt the tutorial questions before your tutorial class for the week.
• Complete the lab work each week.
• (And of course, do the project and final exam.)

Not-So-Secondary requirements:

• Ask questions. During lectures. During tutorials. During labs. On the forum. ( https://edstem.org/ )
• Support each other. Answer questions asked by other students on the forum. This will assist them in their learning, as well as increase your understanding of the concept in the process of explaining it.
• Ask questions.
• Find and share resources:
  • Whenever you're stuck, try Google your question first, and also search for your problem on the course forum. If you find your answer, share the problem you had as well as the solution you found, on the course forum. This will both help you to not make the same mistake again as well as provide a resource for other students who may come across the same problem.
  • Everyone learns differently. We encourage you to search out tutorials, articles, youtube videos, books, apps, games, basically anything that supports you in your journey to learning to write computer programs. When you find things which are particularly useful for you, share them on the forum.
  Notes on communicating on the forum:
  • Before asking questions on the forum, do a quick search to see if someone has already asked (and maybe even has an answer to) what you're about to ask.
  • When responding to another's question on the forum, review your response and check the following aspects ( THINK ):
    • Is it T rue?
    • Is it H elpful?
    • Is it I nspiring?
    • Is it N ecessary?
    • Is it K ind?
• Keep a journal. As time goes on, you'll find more and more of the questions you have, will have the answers in your journal. Include the following things:
  • When you learn something. Write what you learnt.
  • When you see a new keyword. Write the keyword, and maybe an example of its use.
  • When you have a problem. Write out what your problem is.
  • When you solve the problem. Write what the solution was.
• Ask questions.

Course Evaluation and Development

This course is evaluated each session using the myExperience system as well as feedback from students and tutors throughout each term.

• Maintenance of Current Practices (22T3)
  Feedback from tutors, and students when asked, reflect that the demonstrations and lab books (introduced in 21T3 and 22T1 respectively) are fulfilling their intended goals. The insertion of a specific lecture outlining the purpose and use of consultations resulted in a reduction (from 3 in 22T1 to 0 in 22T2) of students reaching the end of the course without completing at least a minimal project.
• More Practice and More Gradual Learning Curve (22T3)
  To continue to address feedback about the pace of the course being too fast, while wanting to keep the amount of content, we will be adding more resources to aid students in doing more practice and building familiarity with concepts. We will also consider removing the spreadsheets topic for future terms. Additional consultations will also be added in the early weeks of the course to assist in the development of fundamental programming and Python skills.
• More Student Support (22T2)
  In 2022 T1 some students indicated that although consultations were available, they were reluctant to use them because they didn't know what to expect in them. In response to this we will include specific, scheduled, targeted consultations throughout the term to support students with common problems. This includes helping students set up their computers (around week 4 and week 5) and helping students overcome obstacles they're facing in developing their project (weeks 7,8,9 and 10).
• Slower Pace and More Tutorial and Lab Questions (21T3)
  Students in 2021 T2 indicated that in some areas the pace of the course was too fast. In response to this we have:
  • Reduced the number of topics (removing databases, recursion) (in order to spend more time on introducing earlier topics more slowly).
  • Created more tutorial and lab questions on certain topics to help students gain more competence in key areas.
• Introduction of Project Demonstrations (21T3)
  In 2021 T3 we trialled the process of students demonstrating their projects as part of the assessment process. Feedback from both students and staff deemed this a success and so will continue into 22T1.
• Introduction of Lab Books (22T1)
  In 2021 T3, after increasing the number of lab questions, they were disproportionately distributed over the labs (particularly at the end of the Python and Programming Fundamentals topic). To improve the distribution of work, the following changes will be made:
  • At the start of each core topic (spreadsheets, Python and programming fundamentals, web apps) a lab book containing all the lab work for that topic will be released. This is intended to increase the transparency about the workload involved in each topic and allow students more control over the distribution of their workload.
  • Due dates will be assigned to lab questions at the end of each lecture. This is intended to communicate to the students at what point in the content they should be capable of completing certain questions in the lab book.
  This combination we hope will allow students to do their lab work as early as possible (and thereby avoid "bunching up" of topics at the end of each topic) while only attempting work which has already been taught in lectures.
• Structure of Examples Provided in Lectures (Ongoing)
  Mixed feedback was provided throughout 21T2 and 21T3 in response to the structure of examples provided in lectures. Some students prefer a single file with small increments made to develop a single comprehensive sample code. Other students prefer many small isolated examples of each item being taught. We will continue to seek feedback throughout the term and try to cater to as many students as possible, within the current cohort, at the same time.

Students are also encouraged to provide informal feedback during the session, and to let course staff know of any problems as soon as they arise. Suggestions will be listened to openly, positively, constructively, and thankfully, and every reasonable effort will be made to address them.