The Science of Learning: 11 Ideas You Can Use This Week

This article is for secondary teachers in Australia and New Zealand who want the research behind the teaching moves that actually work, not another list of untested classroom hacks. You’re not after theory for its own sake. You want to know which ideas are backed by solid evidence, and a quick way to try each one in your next lesson.

Learning science can sound like something for a research lab, not a classroom. It isn’t. Decades of research into how people learn have produced a set of principles that hold up consistently across subjects, year levels and countries. The hard part isn’t believing the research. It’s turning it into what you actually do on Monday morning.

11 evidence-based ideas for the classroom

Each idea below works the same way: a clear mechanism from cognitive science, and a quick way to put it into practice this week.

1. Build on what students already know

Best for: Introducing any topic that depends on earlier content, from historical context to prerequisite maths skills.

Why it works: New learning anchors onto what’s already stored in long-term memory. Without that anchor, working memory is left trying to hold a new idea with nothing to attach it to (Willingham, 2009).

Classroom example: Before starting cellular respiration with a Year 10 Science class, a teacher runs three quick questions on the photosynthesis unit taught weeks earlier, not just last lesson.

Watch out for: If the quick check reveals patchy prior knowledge, the gap itself needs addressing before the new content gets taught, not just a faster recap.

Cognitive scientist Daniel Willingham puts it bluntly: “Thinking well requires knowing a lot.” (Willingham, 2009). Critical thinking isn’t a separate skill bolted on afterwards. It runs on the knowledge already sitting in a student’s head.

2. Manage cognitive load before adding more content

Best for: Any lesson introducing a multi-step process, a diagram-heavy concept, or unfamiliar technical vocabulary.

Why it works: Working memory can only hold so much new information at once (Sweller, 1988). Presenting material in a way that matches how the brain processes words and images, rather than working against it, frees up capacity for understanding rather than decoding.

Classroom example: A Year 9 Science teacher replaces a text-heavy slide on the electron transport chain with a single labelled diagram, teaching the process one step at a time instead of all at once.

Watch out for: It’s tempting to add more support when students look confused, but extra text, animation or spoken explanation on top of an already busy slide usually makes the load worse, not better.

Dr Nidhi Sachdeva, a science of learning researcher at the University of Toronto’s OISE, points to dual coding as one reason presentation matters as much as pace:

“A picture aligned with the text works because that’s how our brain works.”
Source: Dr Nidhi Sachdeva, Well-MeasurED

3. Make retrieval part of the lesson, not just the test

Best for: Warm-ups, exit tickets and anywhere a teacher wants to check what’s actually stuck, not just what was covered.

Why it works: Pulling information back out of memory, rather than re-reading it, is one of the most consistently backed strategies in the literature (Rosenshine, 2012). The struggle to recall strengthens the memory trace in a way re-reading never does.

Classroom example: A Year 11 English class closes their books and writes down everything they remember about last week’s poem analysis before checking their notes.

Watch out for: Retrieval only does its job when it’s genuinely effortful. If every answer comes easily and instantly, it isn’t testing memory, it’s testing how recently something was said out loud.

Education Perfect co-founder Shane Smith built this “science of learning” approach into the platform’s very first version:

“When you’re asked to recall information, your future recall of that same information improves, no matter how you did on that first attempt.”
Source: Shane Smith, Well-MeasurED

4. Space learning out instead of concentrating it

Best for: Any content students will be assessed on weeks or months after it’s first taught, which in practice is almost everything.

Why it works: A concept taught once and never revisited is a concept most students will forget. Rosenshine’s principles of instruction close on exactly this point: build weekly and monthly review into the routine, rather than leaving it to chance before the exam (Rosenshine, 2012).

Classroom example: A Year 8 Maths teacher adds one or two questions from a topic finished three weeks ago into today’s warm-up, alongside the current unit’s content.

Watch out for: One revisit weeks later is better than nothing, but the real payoff comes from a genuine routine of review, not an occasional one.

5. Interleave related topics rather than blocking them

Best for: Practice sets and revision sessions covering several related skills or concepts that students tend to mix up.

Why it works: Mixing related concepts or problem types forces students to work out which one actually applies, rather than running the same procedure 15 times in a row. The extra effort this creates, a desirable difficulty, produces stronger long-term learning even though performance can dip at the time (Bjork & Bjork, 2011).

Classroom example: A Year 10 Maths teacher swaps a block of 15 identical trigonometry questions for a shorter mixed set covering three previously taught question types.

Watch out for: Interleaving before basic fluency exists just creates confusion. Mixing problem types works once students can already do each one on its own.

6. Use worked examples before independent problem-solving

Best for: Teaching a new procedure or problem type for the first time, especially in maths, science and other sequential subjects.

Why it works: A student new to a skill who’s asked to solve a problem alone spends most of their working memory just figuring out where to start. A worked example removes that load by showing what a complete, successful solution actually looks like (Sweller, 1988).

Classroom example: A Year 9 Science teacher solves one stoichiometry problem as a class, talking through why each step works, before setting a similar problem for students to attempt alone.

Watch out for: Never letting go of the worked example. As skill develops, and students get more confident, support is gradually withdrawn. Left in place indefinitely, worked examples get in the way of the independent practice students actually need.

7. Ask “why” and “how”, not just “what”

Best for: Deepening understanding once students can already recall the basic facts of a topic.

Why it works: A quick recall question checks whether a fact is stored somewhere. It doesn’t check whether students understand it. Elaborative interrogation, asking students to explain why something is true or how it connects to something they already know, pushes them to build connected understanding rather than a list of disconnected facts (Dunlosky et al., 2013).

Classroom example: After a Year 12 Biology short-answer question on enzyme function, the teacher follows up with “why does temperature affect that rate?” before moving on.

Watch out for: “Why” questions can turn into guessing games if students don’t yet have the underlying facts to reason from. Get the basics retrievable first.

8. Teach new material explicitly before releasing students to discover it

Best for: Introducing any concept, skill or process students haven’t encountered before, particularly in foundational literacy, numeracy and technical subjects.

Why it works: Clear explanation, modelling, guided practice and feedback give students the scaffolding to build new knowledge safely. Sachdeva argues teaching should be treated as a design science, built around how the brain actually processes information rather than personal preference or whatever’s trending.

Classroom example: A Year 7 English teacher runs a new grammar concept as explain, model, practise together, then practise independently, in that order, rather than setting it as a discovery task.

Watch out for: Swinging too far the other way into pure lecture removes the guided-practice step that makes explicit instruction actually work. Explanation without practice is still incomplete.

Professor Pamela Snow makes a related case from a literacy and numeracy angle, and puts the stakes plainly: instructional time “ethically belongs to students.” Here’s how she explains what that looks like in the sequence of a lesson:

“So ‘forward to fundamentals’ is about us recognizing as adults that just because something looks basic to us, it’s not basic to a novice. But when we teach explicitly and sequentially, we’re building knowledge and skills that are secure, and allow students to add more complex, more elaborate knowledge and skills over time.”
Source: Professor Pamela Snow, Well-MeasurED

9. Build metacognition into the routine

Best for: Helping students move from relying on the teacher to judge their progress, to judging it themselves, useful ahead of exams and major assessments.

Why it works: Busy isn’t the same as learning, and telling the difference is a skill of its own. Sachdeva warns that plenty of student interaction can still be “a false proxy for learning” if it isn’t backed by a real, lasting change in what a student knows.

Classroom example: Before handing back a Year 10 History quiz, the teacher asks students to predict their score and name one topic they’re still unsure about, then compares the prediction with the result together.

Watch out for: Metacognition prompts can turn into a tick-box exercise if students aren’t given class time to actually act on what they notice.

Her own test for whether learning actually happened: “Learning is the long-term change we’re looking for: stable change in long-term memory.” Helping students notice their own understanding, not just their own activity, is what eventually lets them manage their own learning.

10. Make feedback something students can act on

Best for: Marking and returning any piece of assessed work, from a quiz to an extended essay.

Why it works: “Good work” feels nice. It doesn’t tell a student what to do next. Feedback research from John Hattie and Helen Timperley frames useful feedback around three questions: “Where am I going? How am I going? Where to next?” (Hattie & Timperley, 2007).

Classroom example: Instead of marking every error on a Year 11 essay, the teacher identifies the single biggest misconception and gives class time to act on that one piece of feedback.

Watch out for: Feedback that isn’t followed by class time to actually act on it rarely changes anything. Comments without a chance to apply them are just a record of what went wrong.

11. Don’t mistake engagement for learning

Best for: Evaluating whether a lesson, activity or resource is actually working, not just whether students enjoyed it.

Why it works: A lesson can be busy, fun and full of talk without producing much learning at all. Some of the most effective learning activities, retrieval, deliberate practice, wrestling with a misconception, feel effortful rather than fun while they’re happening.

Classroom example: At the end of a Year 9 lesson, the teacher swaps the usual “how did that go?” for “what’s the evidence that learning happened today?”

Watch out for: A quiet, focused class wrestling with a hard retrieval task can look less “engaged” than a noisy one, and be learning far more. Engagement is not a reliable proxy either way.

Shane Smith names the tension directly:

“There is sometimes a disjunct between the things that feel good to the learner and the things that really move the dial.”
Source: Shane Smith, Well-MeasurED

The question isn’t whether students enjoyed the lesson. It’s what they can now remember, explain or do that they couldn’t before it started.

What this looks like in one lesson

Picture a Year 10 Science class revising cellular respiration before a topic test. The lesson opens with three retrieval questions from the photosynthesis unit taught weeks earlier, not last lesson’s content. A single diagram of the electron transport chain replaces a text-heavy slide, with labels placed directly on the diagram instead of a separate key. One worked example of a typical exam question gets talked through as a class, with each step explained, before students attempt a similar question alone. The exit task mixes one question on cellular respiration with one on photosynthesis, so students have to work out which process is actually being asked about. None of this needs new resources. It just needs the same lesson sequenced differently.

Common mistakes to watch for

• Treating this as a checklist, not an approach. Professor Pamela Snow calls out the risk of “window dressing”: using the language of evidence-informed practice without changing what actually happens in the room.
• Picking one idea and ignoring the rest. These principles reinforce each other. Retrieval without spacing fades. Explicit instruction without feedback stalls.

The science is only useful once it changes Monday

Learning science isn’t a script to follow. It’s a way of understanding what’s actually happening when students learn, and using that to make better calls about sequencing, feedback and practice. The strongest ideas here are remarkably consistent: build on what students know, manage what they’re holding in their heads, teach new things explicitly, give real chances to retrieve and space that practice out, and judge success by evidence of learning, not evidence of activity.

The question worth asking isn’t which flashy new strategy to try next. It’s what the evidence says about how this class is likely to learn this topic, and what that means for tomorrow’s lesson.

For a look at how one EdTech company has tried to hold itself to this same evidence standard, Education Perfect co-founder Shane Smith discusses what an evidence-first approach actually demands of a product.

FAQs

What does “the science of learning” actually mean?

The science of learning is what cognitive psychology and educational research reveal about how people actually take in, store and recall information. It covers ideas like cognitive load, retrieval practice and explicit instruction, and helps explain why some teaching methods stick better than others.

Is cognitive load theory the same as differentiation?

No. Differentiation adjusts task difficulty for different students. Cognitive Load Theory says everyone’s working memory can only hold so much new information at once. Direct Instruction takes that seriously: careful sequencing and modelling so students aren’t overwhelmed, then gradually handing the thinking over to them. See how this plays out across a full lesson.

Why does retrieval practice work better than re-reading notes?

Re-reading feels productive because the material seems familiar, but familiarity isn’t the same as knowing it. Retrieval practice makes the brain reconstruct information from memory, which strengthens the ability to recall it later, including in an exam.

Is student engagement a bad thing?

No, but engagement isn’t the same as learning. A lesson can be fun and interactive without producing much lasting change in what students know or can do. Engagement is worth having alongside effortful thinking, not as a substitute for it.

How is spaced practice different from cramming?

Cramming concentrates study into one session and produces short-term recall that fades quickly. Spaced practice deliberately revisits material after a delay, such as a few days and then a few weeks, and that gap is what makes the knowledge stick.

What is metacognition, and why does it matter in class?

Metacognition is a student noticing their own thinking: what they actually know, what they don’t, and which study strategies genuinely help them. Students who can monitor their own understanding are better placed to direct their own learning.

Related reading

• After NAPLAN: The Conversation Worth Having
• Education Perfect’s Pedagogical Approach

References

• Bjork, E.L., & Bjork, R.A. (2011). Making Things Hard on Yourself, But in a Good Way: Creating Desirable Difficulties to Enhance Learning. In Psychology and the Real World: Essays Illustrating Fundamental Contributions to Society. Worth Publishers.
• Dunlosky, J., Rawson, K.A., Marsh, E.J., Nathan, M.J., & Willingham, D.T. (2013). Improving Students’ Learning With Effective Learning Techniques. Psychological Science in the Public Interest.
• Hattie, J., & Timperley, H. (2007). The Power of Feedback. Review of Educational Research, 77(1), 81–112. https://doi.org/10.3102/003465430298487
• Rosenshine, B. (2012). Principles of Instruction: Research-Based Strategies That All Teachers Should Know. American Educator.
• Sweller, J. (1988). Cognitive Load During Problem Solving: Effects on Learning. Cognitive Science, 12(2), 257–285.
• Willingham, D.T. (2009). Why Don’t Students Like School? A Cognitive Scientist Answers Questions About How the Mind Works and What It Means for the Classroom. Jossey-Bass.
• Sachdeva, N. Well-MeasurED: Equity, EdTech & the Science of Learning. Education Perfect. https://www.educationperfect.com/well-measured/equity-and-the-science-of-learning/
• Snow, P. Well-MeasurED: The Evidence We Ignored: Not Back to Basics, Forward to Fundamentals. Education Perfect.
• Smith, S. Well-MeasurED: Founded for Impact: Evidence First from Day One, More Urgent Than Ever. Education Perfect. https://www.educationperfect.com/article/what-does-it-actually-take-to-build-an-evidence-first-digital-approach/

Author: Rachel Ellis, MA Applied Linguistics – Last updated: 10 September 2026