ahandrewh teaches IAT-339web design & development

Andrew Hawryshkewich (lecturer)

• On-campus office: Room 2816, Podium 2, SFU Surrey
• Virtual office: Linked through Canvas
• Email: ac.ufs@h_werdna
• Website: https://andrewh.ca/teaches

Alfredo Sherman (TA)

• Email: ac.ufs@namrehs_oderfla
• TA for labs D101, D102.

Email rules

Please allow up to 2 business days for responses though we will typically reply much sooner. We may be able to answer questions about software or code via email or course chat depending on the complexity. We do not provide design critique via email or course chat. Please arrange a meeting or attend office hours for design critique or complex software or code questions.

To make our responses faster, please include the following in your email:

• Your full name.
• The course number (IAT-339).
• Your lab number.
• A clear question.

Conduct rules

We will be offering an online chat service for students to make use of as part of the course. Sign-up for the service is available through the course Canvas site.

Please treat our online interactions the same way you would in-person interactions. As a teaching team we are dedicated to providing a harassment-free experience for everyone in this class, regardless of gender, sexual orientation, disability, physical appearance, body size, race, or religion. Harassment of any form is not tolerated. Sexual language and imagery is not appropriate in this class.

If you have concerns with anyone's conduct either in-person or online, please direct message or email Andrew. If you do not feel comfortable reaching out to Andrew, please contact SIAT's advisors.

SFU's complete student conduct policy is available online.

You (the student) is feeling ill

Please stay home. No doctor's note is needed for short term (5-day) absences from class. To keep up with course materials:

• Contact your instructor or TA to arrange an alternative time to receive lab feedback.
• Check-in with a friend or your instructor to find out what was missed.
• Check-in on the course chat to pose follow-up questions on the lecture or labs as needed.

If you will be missing class for more than a week or will be missing a major deadline please email Andrew to discuss accommodations.

If Andrew or your TA is ill

If one of the teaching team is feeling ill you can expect a notification on Canvas and course chat by 8:30am on the day of the lecture or lab. Information on how content or materials will be offered will be included in the announcement.

IAT-339 lectures are held:

• Thursdays, 4:30 - 8:20pm
• SRYC 2740, in-person
• Lecturer: Andrew Hawryshkewich (ac.ufs@h_werdna)

Readings

All readings in this course are provided as online readings or as PDFs through Canvas or the SFU Library. A listing of readings is also available on the course website.

Equipment

For this term you will need access to:

• A laptop or tablet
• Headphones
• A code editor (we will use Visual Studio Code)
• A web browser (we will use Chrome at the start of the term)
• An FTP client (we will use Cyberduck)
• A git client (we will use GitHub Desktop)

If you have a preference for another type of software you are welcome to use it as long as it allows you to complete project requirements.

Projects

1. Process — 10% (Individual)
2. Company — 30% (Group)
3. Portfolio — 30% (Individual)

Projects use knowledge learnt from all parts of the course — readings, lectures, tutorials, etc.

Exercises

Short code or practice exercises meant to help get feedback early and quickly on coding and design practice.

Reflections

Instead of in-lecture quizzes on the readings, reading reflections are used in this course to allow for more flexible completion.

Coding quiz

The coding quiz is completed in-lecture late in the term. More details on the coding quiz is provided closer to the time of the quiz.

Teamwork

You will be allowed to select your groups for any teamwork in this course. Reflections are used to establish clear expectations between team members as well as provide a means of leaving the team (if needed). Consider your group member options carefully.

Workload

This course is worth three units. This means you can expect to spend 6-9 hours per week on coursework — for example readings, projects, assignments, etc. — including time in lecture or labs.

Please remember that other three-unit courses share a similar workload. No one course should take time away from your other courses. If you find this course is requiring work above 9 hours per week please email Andrew.

Late submissions

Items submitted late receive 10% per day late starting when the deliverable is due. Please allow yourself sufficient time to submit deliverables without incurring late penalties.

Problematic submissions

Submitting files that cannot be opened or are not in the specified form is considered problematic. Penalties are as follows:

• A penalty of 20% is applied immediately to problematic submissions and students are notified via email about the problem with their submission.
• For every day after being notified about the problematic submission with no reply from the student an additional 15% penalty is applied.
• For example: if the file is not resubmitted until two days after being notified the penalty will be 50%

Artificial intelligence (AI) tools

In this course you are welcome to make use of generative AI tools — unless specified in a project, quiz or exercise brief — with the following conditions:

• You must state how you generated the result you are working with in the comments on your Canvas submission. This will include:
  • the name of the tool;
  • the parameters or prompt used; and,
  • a copy of the generated material linked.
• You must develop the idea further — an AI generated result cannot be your final submission.
• You must be able to make an effective case for why the AI tool enhanced or improved your work if requested by the instructor.

Please include the information above with any project submissions that involve the use of an AI tool. No formal teaching of AI tools is provided in this course.

Plagiarism

Please note that according to SFU policy 4.1.2, the following constitutes plagiarism:

1. Submitting or presenting the work of another person, including artistic imagery, as that of the student without full and appropriate accreditation;
2. Copying all or part of an essay or other assignment from an author or other person, including a tutor or student mentor, and presenting the material as the student's original work;
3. Failing to acknowledge the phrases, sentences or ideas of the author of published and unpublished material that is incorporated into an essay or other assignment.

Plagiarism will result in a grade reduction or school disciplinary action at the instructor's discretion. In this course a zero will be applied to the complete grade of a project that plagiarizes. For further reference and clarification, please see SFU's academic honesty policy or ask Andrew for clarification.

Undeclared use of AI tools will be considered plagiarism in this course. Please refer to the AI tool rules to avoid your project being flagged for plagiarism.

Concerns with grades

Any concerns with grades or grading should be brought up with Andrew. Please email Andrew to start a grade review. Reconsideration of grades may result in a grade being raised, lowered, or remining unchanged.

Concerns should be emailed to Andrew within 10 days of the release of the grade as described in SFU's policy on Grading and the Reconsideration of Grades (T20.01 section 2.4).

Grading scale

All the grades in this course tally to 100% to make it easier to track progress through the term.

This course uses the SIAT standard grading scale for final letter grades: