Release

Specifications for the assignments will be released no later than

• Assignment 1 - 7th September.
• Assignment 2 - 19th October.

Requirements to Pass this Unit

To pass this unit you must achieve a total mark equal to or greater than 50%. There are no hurdle requirements for the unit.

LATE ASSESSMENT SUBMISSION PENALTY

Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark of the task) will be applied for each day a written report or presentation assessment is not submitted, up until the 7th day (including weekends). After the 7th day, a grade of ‘0’ will be awarded even if the assessment is submitted. The submission time for all uploaded assessments is 11:55 pm. A 1-hour grace period will be provided to students who experience a technical concern. For any late submission of time-sensitive tasks, such as scheduled tests/exams, performance assessments/presentations, and/or scheduled practical assessments/labs, please apply for Special Consideration. For example, if the assignment is worth 25 marks (of the entire unit) and your submission is late by 19 hours (or 23 hours 59 minutes 59 seconds), 1.25 marks (5% of 25 marks) will be deducted. If your submission is late by 24 hours (or 47 hours 59 minutes 59 seconds), 2.5 marks (10% of 25 marks) will be deducted, and so on.

ASSESSMENTS WHERE LATE SUBMISSIONS WILL BE ACCEPTED

• Assignment 1: YES, Standard Late Penalty applies 
• Assignment 2: YES, Standard Late Penalty applies 
• Exam: NO

Special Consideration

The Special Consideration Policy aims to support students who have been impacted by short-term circumstances or events that are serious, unavoidable and significantly disruptive, and which may affect their performance in assessment.

If you experience circumstances or events that affect your ability to complete either of the assignments in this unit on time, please inform the convenor and submit a Special Consideration request through ask.mq.edu.au.

Generative AI Usage

Assessments 1 (Programming Task) and 2 (Programming Task) are AI Open while Assessment 3 (Final Exam) is AI Observed. 

The university has taken a ‘two lane’ approach with GenAI: assessments can be AI Open (meaning students complete the assessment in their own time and may use GenAI) and Observed (students complete assessments in supervised environments, where use of AI is controlled or not permitted). More information on the use of GenAI in Assessment can be found here.

¹ If you need help with your assignment, please contact:

• the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
• Academic Success for academic skills support.

² Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation.

³ An automatic short extension is available for some assessments. Apply through the Service Connect Portal.

COMP3000 is taught via weekly 2-hour lectures and practical classes.

Each week you should participate in your scheduled two hour practical. For details of scheduled classes consult the timetables webpage.

Week1

Note that classes commence in week 1. The week-by-week details of the practical classes will be available from iLearn.

Students are expected to do significant preparatory work, readings and exercises before attending classes.

Textbook and Reading Materials

The required text for the unit is Crafting Interpreters by Robert Nystrom

Each week a set of notes, a Rapid Aptitude Test (RAT), an application exercise, and self-study material will be provided in a pdf file. This material will include a set of activities (including the RAT) which are to be done before class.

Communication Methods in COMP3000

We will communicate with you via your university email and through announcements on iLearn. Queries to convenors can either be placed on the iLearn discussion board or sent to the unit convenor via the contact email on iLearn.

The previous offering of this unit used videos provided via iLearn instead of lectures. In this offering, weekly lectures have been reinstated due to student feedback indicating this would be beneficial. In addition, more information about assessment tasks will be given earlier in the semester to allow student to better plan their time.

We value student feedback to be able to continually improve the way we offer our units. As such, we encourage students to provide constructive feedback via student surveys, to the teaching staff directly, or via the FSE Student Experience & Feedback link in the iLearn page.