You don’t need to remember how to do it. Every question comes with a worked method, and most name the common mistake kids make. Free practice worksheets for Years 3–10, Australian Curriculum.
Choose your school year to view topics and practice sheets matching your level.
Requires an open-ended mathematical modelling cycle (formulate, choose representations, discuss solutions in context).
Requires designing and following interactive branching flowcharts or floor-robotics movement sequences.
Requires dynamic digital graphing software or spreadsheet tools to create and compare alternative displays.
Requires conducting live peer surveys and primary data gathering in the classroom.
Requires physical repeated chance trials (spinners, coin tosses, dice rolls) observing empirical variation across trials.
A limited run of repeat-free worksheets. Questions can repeat on later worksheets.
Requires an open-ended mathematical modelling cycle formulating problems and choosing calculation tools.
Requires designing and executing interactive branching algorithms and decision sequences.
Requires hands-on visual approximation and manipulation of physical objects and 3D shapes in the local environment.
Requires collaborative oral and written critique of data visualisations and distribution shapes with peers.
Requires collecting survey responses from respondents and recording/displaying data using digital spreadsheet tools.
Requires conducting physical repeated chance trials and tracking empirical frequency variations.
A limited run of repeat-free worksheets. Questions can repeat on later worksheets.
Requires open-ended mathematical modelling with operations and financial planning.
Requires dynamic digital tools and exploratory algorithm experimentation to explore factor and divisibility patterns.
Requires physical protractor manipulation and hands-on angle construction on physical paper.
Requires multi-stage inquiry: posing questions, gathering primary data, and presenting findings.
Requires conducting physical and simulated repeated chance trials comparing observed to theoretical frequencies.
A limited run of repeat-free worksheets. Questions can repeat on later worksheets.
Requires open-ended mathematical modelling cycle, financial enterprise planning, and written justification.
Requires designing, coding, and testing algorithms in visual or text-based programming environments.
Requires dynamic geometry software (e.g. GeoGebra) or physical tile manipulation to create tessellations.
Requires researching, discussing, and evaluating real-world digital and print media reports for bias.
Requires multi-stage primary data collection, statistical inquiry, and peer presentation.
Requires digital computer simulation software to run large trial batches demonstrating the law of large numbers.
A limited run of repeat-free worksheets. Questions can repeat on later worksheets.
Requires open-ended financial modelling and authentic problem formulation with digital calculation tools.
Requires digital spreadsheet or CAS tools to systematically vary parameters and observe formula responses.
Requires an open-ended mathematical modelling cycle formulating real-world ratio situations and evaluating representations.
Requires designing, coding, and testing computational sorting algorithms in software.
Requires empirical data collection for discrete/continuous variables and reporting distributions.
Requires running computer simulations with large trial counts to compare observed vs expected probabilities.
A limited run of repeat-free worksheets. Questions can repeat on later worksheets.
Practises sharing an amount in a given ratio; omits formulating a ratio or rate model from a situation, interpreting and evaluating it.
Requires authentic multi-stage financial modelling and evaluating model assumptions.
Requires an open-ended mathematical modelling cycle formulating problems with linear functions and evaluating the model. A swap to another question was considered: no linear-relations generator on the paper models a financial or applied scenario (the paper's questions expand, factorise and solve graphically), so nothing can be re-mapped.
Requires dynamic digital graphing software (e.g. Desmos) to test conjectures on linear relations.
Requires designing and coding geometric verification algorithms in software.
Requires qualitative investigation and classroom discussion of data-collection methods (census, sampling, experiment, observation) and practicalities. A swap to another question was considered: no generator produces a census-vs-sampling comparison question (the paper's data questions report on already-collected distributions, not on how the data was gathered), so nothing can be re-mapped.
Requires generating and comparing dynamic random samples of varying sizes from large populations.
Requires planning and executing sample surveys with ethical considerations and fieldwork.
Requires digital simulation software to simulate compound multi-stage chance experiments.
A limited run of repeat-free worksheets. Questions can repeat on later worksheets.
Practises finding a value under direct proportion; omits formulating a proportion model, interpreting and evaluating it.
Requires open-ended mathematical modelling cycle choosing linear vs quadratic functions.
Requires dynamic graphing software sliders to observe parameter variations on function graphs.
Requires coding, testing, and refining geometric construction algorithms in software.
Requires researching and auditing real-world media reports and external survey methodologies.
Requires critical evaluation of external sampling methods and media data visualisations.
Requires authentic end-to-end data collection, multivariate analysis, and written reporting.
Requires digital simulation software to compare experimental and theoretical compound probabilities.
A limited run of repeat-free worksheets. Questions can repeat on later worksheets.
Practises calculating compound growth or decay; omits choosing between linear, quadratic and exponential models; interpreting and evaluating.
Practises multi-step direct and inverse proportion; omits scaling of objects; formulating, evaluating and modifying a model.
Requires open digital exploration and conjecture testing with dynamic function graphing tools.
Requires algorithmic coding, debugging, and computational spatial modelling.
Requires critical evaluation of public media statistics, ethical issues, and source data audits.
Requires planning and executing an authentic bivariate data statistical investigation with fieldwork.
Requires computer programming and digital simulations to model conditional probability distributions.
A limited run of repeat-free worksheets. Questions can repeat on later worksheets.