The science behind Toku
Why each part of the practice is there.
Explore durable learning, reasoning, transfer, divergent thinking, executive control, feedback and performance. Each explainer connects the science to the way Toku asks children to think.
Retrieval practice
Actively bringing an answer back from memory instead of only re-reading, re-watching or copying a worked example.
Explore →Feedback and error correction
Giving the learner information about how an attempt went and what needs to change next.
Explore →Spacing and repeated practice
Returning to a skill across more than one attempt instead of relying on one concentrated block of practice.
Explore →Maths fluency and automaticity
Becoming faster and more reliable at foundational calculations so they require less deliberate reconstruction.
Explore →Working memory and cognitive load
Working memory is limited, so tasks become harder when too many unfamiliar elements have to be held and manipulated at once.
Explore →Adaptive difficulty
Changing the level of challenge in response to demonstrated performance rather than keeping every learner on the same fixed level.
Explore →Visible progress and metacognition
Helping learners notice what is secure, what is weak and whether their approach is working.
Explore →Interleaving and mixed practice
Mixing related problem types so the learner has to identify which method is appropriate instead of repeating one procedure in a block.
Explore →Mastery and secure foundations
Using evidence of secure performance before treating a skill as ready for more difficult work.
Explore →Useful challenge
Practice can feel more effortful in ways that improve later learning, provided the difficulty is productive rather than overwhelming.
Explore →Formative assessment and next-step decisions
Using evidence from practice to decide what should happen next, rather than collecting results only for reporting.
Explore →Personal bests and small goals
Turning progress into a short, specific target the learner can understand and act on.
Explore →Gamification and engagement
Using game-like elements such as points, streaks, progress and challenges to influence whether learners start and return to practice.
Explore →Timed practice without making speed the verdict
Using a short timer to measure fluency while avoiding the message that faster automatically means better at mathematics.
Explore →Flexible retrieval and transfer
Being able to access learned knowledge when the wording, context or surrounding problem changes.
Explore →What brain research says about arithmetic learning
Arithmetic learning has measurable neural correlates, and the pattern of brain engagement changes as children become more skilled at retrieving facts.
Explore →Divergent thinking
Generating several plausible ideas or approaches instead of stopping at the first answer that comes to mind.
Explore →Analogical and relational reasoning
Seeing the relationship underneath one example and using that structure to understand a different-looking problem.
Explore →Procedural flexibility
Choosing between methods and switching to a more efficient or more appropriate strategy when the problem allows it.
Explore →Productive struggle and learning from attempts
Trying to make sense of a new problem before immediately receiving the complete solution, then using instruction or feedback to refine what was tried.
Explore →Critical thinking and evidence evaluation
Checking claims, evidence and conclusions instead of accepting the first plausible explanation.
Explore →Executive functions for complex problems
The control processes used to hold goals in mind, resist distractions, update information and switch strategy.
Explore →Performance under challenge
Bringing knowledge, strategy and control together when the problem is unfamiliar, timed or high stakes.
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