How to plan your Monash timetable in 2026

Monash runs a hybrid enrolment model that combines two approaches most other universities use separately. Understanding the difference between the two phases is the single most useful thing you can know before enrolment opens.

The preference roundcomes first. During this phase, you rank your preferred class times for each activity - lectures, tutorials, labs, and any other contact types. The system processes everyone's rankings after the window closes and allocates based on preferences across the whole cohort. Speed does not matter here. What matters is ranking thoroughly - including your acceptable fallbacks, not just your top choice. A student who ranks only their favourite tutorial and gets bumped will receive a random assignment from whatever is left.

The adjustment round(FIFS) opens after preference results are released. This is where students can swap into different class times, and popular swaps fill fast. If you missed a preferred class in the preference round, or if your results came back worse than expected, the adjustment round is your chance to fix it - but only if you're ready to act immediately when it opens.

The practical implication: you need two plans. Your preference-round plan is about ranking thoughtfully. Your adjustment-round plan is about acting fast on pre-identified targets. Both plans require knowing which class combinations actually work for your week as a whole.

A common point of confusion for Monash students is the relationship between MonPlan and timetable optimisation tools. They solve different problems, and conflating them leads to using neither properly.

MonPlanis Monash's degree planning tool. It helps you work out which units to take each semester across your entire degree - sequencing prerequisites correctly, meeting course requirements, and mapping out a multi-year plan. If you need to know whether you can take Advanced Econometrics before completing Intermediate Econometrics, that's a MonPlan question.

Smoovsolves a different problem: once you know which units you're enrolling in this semester, which specific class times should you pick? This is a combinatorial optimisation problem that gets surprisingly complex with four or five subjects, each offering multiple tutorial and lab groups. Smoov evaluates every valid combination across all your subjects simultaneously and ranks them by how well they match your preferences - fewer campus days, no 8am starts, protected work shifts, and so on.

See the full comparison of Smoov vs MonPlan if you want the detailed breakdown. The short version: use MonPlan to decide what you're taking. Use Smoov to decide when you're going.

Monash uses Allocate+, which supports JSON data export. That means you can import your subject data directly into Smoov rather than entering class times by hand - a process that is both slower and more prone to missed options. Read the full importing guide for step-by-step instructions, but the process is straightforward:

This is particularly useful at Monash because the combination of lectures, tutorials, and labs across four or five subjects can produce hundreds of valid schedules. Manually cross-referencing them in a spreadsheet is how students end up with a mediocre timetable that technically has no clashes but is still unpleasant to live with every week.

A recurring question in Monash student forums goes something like: "Can Allocate+ put all my classes after 10am across just three days?" The answer is that Allocate+ itself has no preference optimisation - it gives you options, not recommendations. That's exactly what Smoov does.

If you work retail shifts on Thursday evenings and Saturday mornings, those blocks are constraints that should be set before you build your timetable plan - not something to negotiate around after the fact. Enter your work shifts as hard constraints in Smoov, and the solver will only return schedule combinations that leave those blocks free. No manual checking, no accidentally booking yourself into a Thursday 5pm tutorial.

Beyond work shifts, you can set preferences for:

The solver finds valid combinations that meet all your hard constraints and then ranks them by how well they satisfy your preferences. You get the best realistic option, not just any option that technically fits. For more on the work-study scheduling approach, see balancing work shifts and uni classes.

When your preference round results arrive, check them immediately. Do not wait until the next morning. Here is why: the adjustment round typically opens shortly after results are released, and the most desirable class times fill fast. Students who check results the following day are often left with whatever the early movers did not want.

Before results even arrive, prepare your swap targets. Look at your ranked preferences from the preference round and identify which classes, if you did not get your top choice, you would want to swap into during FIFS. Then re-run Smoov with your likely allocation to see whether a swap is actually worth pursuing - sometimes what looked like a second-choice tutorial fits into a better overall week than the one you originally wanted.

If you miss out on a preferred swap during the adjustment round, set a reminder to check back in the first two weeks of semester. Spots open regularly as students change their enrolment after classes begin.

If you're trying to coordinate class times with friends - to share tutorials, protect shared lunch breaks, or align free days for group study - the individual scheduling approach breaks down fast. What works for your schedule may clash with theirs in ways that are not obvious until you compare them side by side.

SmoovSync lets a group of students share their constraints and preferences and find schedule combinations that work across the whole group, not just for each person in isolation. Once allocation results are out and everyone's actual timetable is confirmed, you can use SmoovSync to identify shared free windows and plan around them.

Read the SmoovSync guide for the full walkthrough on group timetable coordination.