This learning video is designed to develop critical thinking in students by encouraging them to work from basic principles to solve a puzzling mathematics problem that contains uncertainty. Materials for in-class activities include: a yard stick, a meter stick or a straight branch of a tree; a saw or equivalent to cut the stick; and a blackboard or equivalent. In this video lesson, during in-class sessions between video segments, students will learn among other things: 1) how to generate random numbers; 2) how to deal with probability; and 3) how to construct and draw portions of the X-Y plane that satisfy linear inequalities.

This lesson teaches students how to make decisions in the face of uncertainty by using decision trees. It is aimed for high school kids with a minimal background in probability; the students only need to know how to calculate the probability of two uncorrelated events both occurring (ie flipping 2 heads in a row). Over the course of this lesson, students will learn about the role of uncertainty in decision making, how to make and use a decision tree, how to use limiting cases to develop an intuition, and how this applies to everyday life. The video portion is about fifteen minutes, and the whole lesson, including activities, should be completed in about forty-five minutes. Some of the activities call for students to work in pairs, but a larger group is also okay, especially for the discussion centered activities. The required materials for this lesson are envelopes, small prizes, and some things similar in size and shape to the prize.

When do photons, electrons, and atoms behave like particles and when do they behave like waves? Watch waves spread out and interfere as they pass through a double slit, then get detected on a screen as tiny dots. Use quantum detectors to explore how measurements change the waves and the patterns they produce on the screen.

Students learn about probability through a LEGO® MINDSTORMS® NTX-based activity that simulates a game of "rock-paper-scissors." The LEGO robot mimics the outcome of random game scenarios in order to help students gain a better understanding of events that follow real-life random phenomenon, such as bridge failures, weather forecasts and automobile accidents. Students learn to connect keywords such as certainty, probable, unlikely and impossibility to real-world engineering applications.

Students learn basic concepts of robotic logic and programming by working with Boe-Bot robots—a simple programmable robotic platform designed to illustrate basic robotic concepts. Under the guidance of the instructor and a provided lab manual, student groups build simple circuits and write codes to make their robots perform a variety of tasks, including obstacle and light detection, line following and other motion routines. Eight sub-activities focus on different sensors, including physical sensors, phototransistors and infrared headlights. Students test their newly acquired skills in the final activity, in which they program their robots to navigate an obstacle course.