reSolve: Algorithmic thinking – simulation

This unit shows why and how simulation complements more traditional mathematical methods of investigation and investigates the comparative advantages and disadvantages of simulation-based approaches. Students work hands-on with interactive simulations and learn the role of virtual experiments, gaining exposure to computational methods. They learn the basics of some fundamental simulation methods, including Monte-Carlo simulations, agent-based simulation, individual-based simulation and population-based simulation.

Additional details
Year level(s)	Year 10
Audience	Teacher
Purpose	Teaching resource
Format	Downloadable resources
Teaching strategies and pedagogical approaches	Mathematics investigation
Keywords	data representation, data analysis, modelling, simulations, chance experiments, Monte-Carlo simulation
Curriculum alignment
Curriculum connections	Technologies, STEM/STEAM, Numeracy
Strand and focus	Statistics, Probability, Build understanding, Apply understanding
Topics	Data representation and interpretation, Chance and probability
AC: Mathematics (V9.0) content descriptions	AC9M10P02 Design and conduct repeated chance experiments and simulations using digital tools to model conditional probability and interpret results AC9M10P01 Use the language of “if .... then”, “given”, “of”, “knowing that” to describe and interpret situations involving conditional probability AC9M10ST03 Construct scatterplots and comment on the association between the 2 numerical variables in terms of strength, direction and linearity AC9M10ST04 Construct two-way tables and discuss possible relationship between categorical variables
Numeracy progression	Understanding chance (P6)
Copyright details
Organisation	ReSolve: Maths by Inquiry
Copyright	© Australian Government Department of Education, Skills and Employment 2021. Creative Commons BY-NC-SA 4.0.