Lesson Structure

These lessons are slide driven, so that facilitating challenges and showing sample code is easy fluid as possible. The lessons are broken into classes (2 or 3) and last between 90-120 minutes in total. Times will of course fairly greatly depending on whether or not this is the first mBot lesson students have encountered, and many other factors. Beneath the each slide visual in the PowerPoint are instruction cues, and even some example phrases "in quotations" as a resource for your instructions.

The classes are further broken up into mini challenges, which guide students through the coding and curriculum proficiency need to achieve the culminating challenge at the end. Sample code for each challenge is given (remembering that there is more than one correct coding solution).


Lessons Overview - Ontario

Grade Lesson Curriculum Objectives Coding Objectives
5 Math - Geometry and Spatial Sense

5 Math- Patterning and Algebra
Pattern Recognition



  • Regular Polygons
  • Internal and External Angles
  • Term Numbers
  • Extrapolating Patterns
  • Loops
  • Precise Motor Control
  • RGB LED's
  • Tones
5 Math - Patterning and Algebra Robot Curling
  • Variables (math)
  • Patterns
  • General Terms
  • Multipliers
  • Variables (coding)
  • Loops
  • Tracing/Predicting Code Output
6 Science - Geometry and Special Sense Coordinate Race
  • Coordinates
  • Ordered Pairs
  • Motor Commands
  • Calibration
  • Reading Code
6 Science - Electricity and Electrical Devices Electric Presentation
  • Electricity
  • Circuit Diagrams
  • Resistance
  • Sequencing
  • Loops
  • If Statements
  • Line Following
7 Math - Probability and Data Management Probability of Escape
  • Probability
  • Sequencing
  • If Statements
  • Loops
  • Variables
  • Random Number Generation
7 Science - Forces Acting on Structures and Mechanisms Robot Soccer
  • Form and Function
  • Material Selection
  • External and Internal Forces
  • Event Blocks
  • Loops
  • If Statements
  • UI Design
8 Math - Data Management and Probability Graphing with Sensors
  • Scatter Plots
  • Distance Time Graphs
  • Variables (coding)
  • Loops
  • If Statements
8 Math - Data Management and Probability Discrete Guitar
  • Discrete and Continuous Data
  • Loops
  • Nested If Statements
  • Sensor Inputs
  • Intro to Syntactical Programming