How to Take Study Notes With AI (Without Letting It Do the Thinking for You)

How do you use AI to take study notes for VCE?

The honest answer: don’t let AI write your notes, let it work on the notes you wrote yourself. Making notes is the part where you actually learn — your brain has to decide what matters, put it in your own words, and connect it to what you already know. Outsource that to AI and you skip the learning, even though it feels productive. So the workflow that works is: you write and organise your notes (in something like Obsidian or Notion), AI helps you use them (summarise, quiz you, find gaps, connect topics), and a VCAA-aligned tool checks whether those notes would actually get you the marks in a SAC.

Why AI-generated notes let students down

The problem isn’t usually that AI-generated notes are wrong. It’s more specific than that.

They’re full of small formatting errors that don’t matter to a machine but do to a student trying to actually use them under time pressure. They’re missing the diagrams and images that make a maths concept click — an AI summary of a topic tends to be text-heavy in a subject that often needs a picture. And critically, they don’t know the curriculum-specific traps: the exact places students lose marks on SACs and exams, the trick areas a real study design tests for. A general AI has no idea what those are, so it can’t flag them. What you get instead is a note that’s padded with unnecessary text — it reads as thorough, but it isn’t targeted at where the marks actually get lost.

That’s the trap nobody warns you about. AI-generated notes are the most productive-feeling way to waste a study session. You end up with a folder full of confident-looking summaries and nothing that’s actually built for how you think or where you’re weak.

Why making notes is the whole point

Here’s the bit that changes how you use AI. The value of a note isn’t the note. It’s what your brain does while you make it.

When you write a summary yourself, you’re forced to:

• decide what actually matters and what’s filler
• put it in your own words, which means you have to understand it first
• connect it to something you already know
• notice the gaps where you can’t explain it

That’s encoding. It’s the same reason active recall and writing things from memory beat highlighting and re-reading. The struggle is the feature, not a bug to optimise away.

When AI writes the note, all four of those steps happen inside the AI, not inside you. You get the artefact without the learning. So the rule is simple: AI should never do the part where the thinking happens. It should do everything around it.

Here’s how I put it to students: notes are only useful to you because they’re written the way you think and targeted at your specific weaknesses. The creation of the note is where the learning is — not using it afterwards. Writing something, summarising it and explaining it in a way you actually understand is the consolidation that makes it stick. The one caveat I’d add: once your notes exist, don’t keep rewriting them from scratch every time. Just add to them.

The honest AI note-taking workflow (3 layers)

Think of it as three layers, and AI only touches the second one.

Layer 1 — You encode (this part is non-negotiable)

Write and organise your own notes. The tool matters less than the fact that you are doing it. A lot of VCE students use:

• Obsidian — plain-text notes you own, with links between topics so your subjects turn into a connected map instead of a pile of files. Great if you like building a “second brain” over two years.
• Notion — more visual, database-style, good if you like everything (notes, to-dos, trackers) in one organised workspace.

Either works. Handwriting works too. The only wrong answer is letting AI do this layer for you. For what it’s worth, I personally use Obsidian — though that’s partly because I’ve got it wired up directly to the coding tools I use for work, not a typical student setup. For a VCE student, I don’t think the app matters much: Notion or even Google Docs work just as well, as long as you’re the one doing the writing.

Layer 2 — AI helps you use what you made

This is where AI earns its place. Once you’ve made the notes, point AI at them to:

• Summarise a long topic into a one-page revision sheet (from your notes, so it’s in your words, just tightened)
• Quiz you — “ask me ten questions on this topic and don’t show me the answers until I’ve tried” turns a passive note into active recall
• Find the gaps — “what’s missing or unclear in these notes?” surfaces the things you didn’t realise you didn’t know
• Connect ideas — “how does this topic link to [other topic]?” builds the web that makes recall easier under exam pressure
• Tidy the mess — turn a wall of dot points from class into clean, structured revision material

A tool worth a specific mention here is NotebookLM, because it answers only from the sources you give it. That grounding means far less of the confident-but-wrong problem you get when a general AI fills gaps with invention. Feed it your notes and the textbook, and it stays on your material. The thing that actually surprised me the first time I fed it real VCE notes: ask it a question and it references exactly where in your notes the answer came from, so you can check it’s not making anything up. (There’s a full how-to on that in the spoke linked below.)

Layer 3 — Check it would actually get the marks

This is the layer the note apps and general AI can’t do, and it’s the one that decides your score.

The way I actually use this with students: talk to the AI live while you’re doing questions. If you don’t understand why multiplying two negative numbers gives a positive, ask it to explain with an example, and keep going back and forth until it clicks. Then ask it to give you a few questions to test yourself on the same idea. Log every question you get wrong as you go — that running list of your actual mistakes becomes more useful for retesting yourself later than the notes themselves.

The catch: AI is great at organising notes, terrible at judging them

Notice what every tool in Layer 2 has in common. They’re brilliant at shaping information you already have. None of them know VCAA, and all of them will state a wrong maths result with total confidence.

That matters more in VCE than almost anywhere, because VCAA marks to a specific study design. A general AI has no idea what that is. So it’ll happily:

• summarise a method that’s almost right but loses marks the way VCAA marks it
• tidy up working that’s confidently, invisibly wrong
• tell you your notes “look comprehensive” when they’re missing the exact thing a SAC will test

A tool that’s confidently wrong is worse than no tool, because you don’t know to doubt it. Your notes can be beautifully organised, perfectly summarised by AI, and still walk you into a SAC with a method that drops marks.

So the workflow has to end with a layer that actually knows what you’re being marked against.

Where EquateIt fits (and yes, it’s ours)

I’m not going to pretend EquateIt is your note-taking app. It isn’t. You should absolutely make your notes in Obsidian, Notion, on paper, wherever — and use AI to help you work with them. That’s Layer 1 and 2, and the general tools are genuinely good at it.

EquateIt is Layer 3. Once you think you know a topic from your notes, EquateIt is where you find out if you actually do — every VCE Maths Methods and Specialist topic broken into practice questions, marked the way VCAA marks, with worked solutions you can trust. It’s the thing ChatGPT can’t be: VCAA-specific, and right about the maths.

That’s the part your notes can’t tell you. Notes feel like knowing. Getting a question marked the way VCAA marks it is the only way to prove you know it.

It’s also not just another app to stack on top of ten others. The whole point is one place to practise and get marked properly, instead of bouncing between five note tools, three AI chatbots and the open internet.

I’ll be honest about the limit here too: AI is genuinely useful for flagging that a gap exists, but it’s not reliable at pinpointing the specific gap a specific student has — a generic “here’s what might be missing” isn’t the same as “here’s what you personally don’t understand.” That’s on the student, not the tool: use AI’s gap-check as a prompt to go back and actively work through the material, not as the answer itself. The most common failure I see isn’t AI missing something — it’s a student treating the gap-check as the end of the process instead of the start of one.

Use Obsidian or Notion to make your notes. Use AI to work with them. Use EquateIt to know they’d hold up. Try it free →

The single biggest mistake I see

Overreliance — not on AI generally, but on using it to produce large amounts of text instead of asking it to help with specific problems. The students who get the most out of this write all their own notes first, then use AI narrowly: to quiz them on the content, or to flag anything that looks like a clear gap worth adding. The moment AI starts generating volume instead of answering a specific question, it’s stopped helping.

The one-page version

The students who get the most out of AI aren’t the ones who let it write their notes. They’re the ones who make the notes themselves, use AI to work them harder, and never trust a general AI to tell them they’re ready.