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Unit Synopsis
This unit provides an advanced exploration of web application architecture, focusing on integrating agentic systems and multi-agent orchestration into the modern development lifecycle. You will move beyond basic Generative AI (GenAI) assistance to design and deploy sophisticated, autonomous applications in web environments.
Details
| Level | Postgraduate |
|---|---|
| Unit Level | 9 |
| Credit Points | 6 |
| Student Contribution Band | SCA Band 2 |
| Fraction of Full-Time Student Load | 0.125 |
| Pre-requisites or Co-requisites |
Prerequisites: COIT20245 Introduction to Programming, COIT20248 Information Systems Analysis & Design.
Important note: Students enrolled in a subsequent unit who failed their pre-requisite unit, should drop the subsequent unit before the census date or within 10 working days of Fail grade notification. Students who do not drop the unit in this timeframe cannot later drop the unit without academic and financial liability. See details in the Assessment Policy and Procedure (Higher Education Coursework). |
| Class Timetable | View Unit Timetable |
| Residential School | No Residential School |
Unit Availabilities from Term 2 - 2027
Term 2 - 2027 Profile
Attendance Requirements
All on-campus students are expected to attend scheduled classes - in some units, these classes are identified as a mandatory (pass/fail) component and attendance is compulsory. International students, on a student visa, must maintain a full time study load and meet both attendance and academic progress requirements in each study period (satisfactory attendance for International students is defined as maintaining at least an 80% attendance record).
Recommended Student Time Commitment
Each 6-credit Postgraduate unit at CQUniversity requires an overall time commitment of an average of 12.5 hours of study per week, making a total of 150 hours for the unit.
Assessment Tasks
To see assessment details from an earlier availability, please search via a previous term.
This is a graded unit: your overall grade will be calculated from the marks or grades for each assessment task, based on the relative weightings shown in the table above. You must obtain an overall mark for the unit of at least 50%, or an overall grade of ‘pass’ in order to pass the unit. If any ‘pass/fail’ tasks are shown in the table above they must also be completed successfully (‘pass’ grade). You must also meet any minimum mark requirements specified for a particular assessment task, as detailed in the ‘assessment task’ section (note that in some instances, the minimum mark for a task may be greater than 50%).
Past Exams
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This list is not an exhaustive list of all University policies. The full list of policies are available on the Policy web site.
Feedback, Recommendations and Responses
Every unit is reviewed for enhancement each year. At the most recent review, the following staff and student feedback items were identified and recommendations were made.
Source: Student feedback
The unit could improve by introducing web design basics, such as HTML and CSS, alongside heuristics from the start, rather than focusing on theory for several weeks before practical lessons.
Based on student feedback, the tutorials should be restructured to introduce introductory HTML and CSS practical lessons alongside design heuristics in Weeks 1 and 2. This will ensure early hands-on engagement and a better balance between theoretical foundations and technical skills from the start of the term.
Tutorial materials were updated to integrate introductory HTML and CSS practical exercises alongside design heuristics in Weeks 1 and 2. A standardised set of reusable interactive coding modules and self-paced online exercises was implemented to provide immediate hands-on technical practice without requiring recurring content redesigns.
Source: Student Evaluation / Class Feedback
Students expressed strong interest in understanding how contemporary AI tools and features (e.g., AI-assisted layouts, dynamic personalisation, or embedding lightweight conversational interfaces) apply to responsive web development.
Introduce a supplementary lab activity that integrates basic AI components and adaptive design principles into responsive web applications.
In Progress
To see Learning Outcomes from an earlier availability, please search via a previous term.