UX · CONTENT · PERFORMANCE · AI

Course Planning with AI

Product-led UX strategy

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Overview
My Role
The Problem
Process & Research
The Insight
The Solution
Key Experience Features
Impact on Students & the Institution
Post-Launch Outcomes
Future Concept: Extending the Ecosystem with AI

Overview

Course planning had become one of the most complex journeys in the student lifecycle.

Students were bouncing between pages, PDFs, prerequisites, fees and policies — stitching together plans that made sense academically and personally.

The issue wasn’t information. The issue was the cognitive effort required to interpret it.

This work reimagined course planning as a clearer, calmer and more supportive experience.

My Role

UX and content lead
Behavioural insights and student-research synthesis
Planning-experience redesign and interaction flows
Information architecture and progression logic
Content patterns for clarity and workload understanding
Stakeholder workshops
Product direction for a scalable planning ecosystem
Exploration of AI-enabled extensions (search, pathways, guidance)

The Problem

The planning experience didn’t reflect how students actually made decisions.

Support-centre conversations and behavioural patterns showed that students weren’t planning in a neat sequence — they were planning around life.

Workload, lifestyle, timing, job goals and pathway options all shaped choices. The ecosystem wasn’t supporting this level of personal complexity.

Visual summary of student behaviour insights, showing that course choices are shaped by workload, lifestyle, timing, job goals and personal circumstances.

How students actually plan subjects - shaped by life, not linear rules.

Process & Research

To understand where the experience was breaking down, I reviewed:

course-planning queries received by support teams
insights from student services and enrolment
examples of student-created plans (notes, spreadsheets, screenshots)
faculty guidance, rules and progression logic
internal feedback on progression and retention challenges

Two themes became clear:

Students wanted clarity and reassurance, not more content.
Most effort went into connecting fragments — not making decisions.

These insights shaped both the interaction design and the content strategy.

The Insight

Static pages and heavy PDFs couldn’t adapt to students’ shifting needs.

The experience needed to respond intelligently at each choice-point, offering clarity without overwhelming detail.

Comparison graphic showing the shift from static information sources to an interactive, adaptive planning experience.

From static information to an adaptive, student-centred planning experience.

The Solution - A Single Interactive Planner

We redesigned course planning as one adaptive environment — a space that supported clarity from the first choice to the final study plan.

The planner brought together:

visual course pathways
workload and duration indicators
prerequisite awareness
study-mode comparison
recommended plan templates
a flexible build-your-own workspace
save and download options

High-level concept diagram of the Course Planner ecosystem, showing pathways, workload indicators, prerequisites and personalisation elements.

High-level concept of the interactive planning ecosystem.

Key Experience Features

The experience balanced structure with autonomy — guiding students without limiting their choices.

Key features included:

a clear empty state to help students get started
an intuitive elective-selection flow
real-time visibility of workload and total duration
clean, mobile-first UI patterns
simple save, revisit and download options

Screens and icons representing main planner features, including empty state, elective modal, workload visibility, duration summary and download options.

Core interface patterns supporting clarity and autonomy.

Impact on Students and the Institution

The redesigned planner created meaningful improvements across both the student and organisational experience.

For Students

Students described the new experience as clearer, calmer and more supportive.

They felt more confident choosing subjects, better understood their options, and found decisions easier to make.

Planning became achievable rather than overwhelming.

For the Institution

Clarity and structure improved outcomes for support teams and academic staff.

Teams reported fewer course-planning queries, advisers noted stronger student preparedness, and early retention indicators showed positive shifts linked to clearer pathways.

Across the board, the planner strengthened both the student journey and the staff experience.

Benefits for the institution including fewer support queries, clearer academic communication, improved decision quality and better retention.

Positive impact across student confidence and organisational clarity.

Post-Launch Outcomes

After launch, the planner delivered measurable improvements across the student journey and internal operations:

stronger student confidence in decision-making
clear understanding of progression and workload
fewer planning-related enquiries for support teams
improved student preparedness during advisory sessions
early retention gains linked to pathway clarity

These shifts aligned planning clarity with broader organisational goals.

Future Concept: Extending the Ecosystem with AI

As part of my RMIT work, I explored how AI could responsibly extend the planner — enhancing, not replacing, student decision-making.

Capabilities included:

natural-language subject search
automated pathway suggestions
prerequisite explanations in plain language
job-market aligned recommendations
conversational support for “what should I do next?” moments

These concepts showed how intelligent support could make planning even clearer and more adaptive.

Conceptual diagram showing possible future AI enhancements such as natural-language search, pathway recommendations and conversational guidance.

Concept: AI-supported decision clarity and personalised guidance.

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