VEX GO - Data Detectives: Bridge Challenge - Unit Overview

Grades

3+ (Ages 8+)

Time

40 minutes per lab

Unit Essential Question(s)

What is a sensor?
What is data?
How can we use data to help us solve problems?

Unit Understandings

The following concepts will be covered throughout this Unit:

A sensor produces data about the real world
How to effectively use the Eye Sensor to collect data
How to understand the data provided by the Eye Sensor
How to make a hypothesis and test it using data

Lab Summary

Click on the following tabs for a summary of what the students will do and learn in each lab.

Lab 1 - Understanding Data

Main Focus Question: What is the Eye Sensor, and what data does it report?

Students will build the Code Base - Eye Down.
They will be introduced to the Eye Sensor, how it works, and how it reports data as hue value.
Students will move the Code Base over the cracked surface of a bridge with the eye light off, and observe and record the data reported by the Eye Sensor in the VEXcode GO Monitor.
Students will predict if turning on the eye light will affect the reported sensor data.
Students will then move the Code Base over the bridge surface with the eye light on, and observe and record the data reported by the Eye Sensor in the VEXcode GO Monitor.
They will compare their data sets to confirm or refute their predictions, and discuss how and why the data sets differ.

Lab 2 - Collecting Data

Main Focus Question: How can I collect data with a sensor?

Students will be told that a citizen has reported that there may be an unsafe bridge in their city. They will act as bridge inspectors, and learn the criteria for safe, at-risk, and dangerous bridges in order to investigate this claim.
Students will use the Eye Sensor on the Code Base to collect data about the bottom of the bridge.
They will record the distance and hue value data reported at regular intervals on their bridge inspection reports.
Students will then use the data to graph the hue value and distance the robot has traveled.

Lab 3 - Analyzing Data

Main Focus Question: How can I analyze data from a sensor?

Students will continue their investigation from Lab 2 in order to determine if a crack is present on the bottom of the bridge.
Students calculate the size of any cracks using the data collected in Lab 2.
They will analyze their collected data based on the criteria to determine if their bridge is safe, at-risk, or dangerous.

Lab 4 - Making a Hypothesis

Main Focus Question: How can I use data to solve an authentic problem?

Students will learn about the factors that can affect the structure of bridges and cause them to crack, including the climate, the span of the bridge, and the amount of bridge traffic.
Students will be given data sets about several bridges and will use the data to determine which bridges should be prioritized for inspection and repair.
Since there are so many bridges, not all of them can be inspected at once. Students will collaboratively decide which bridge is most likely to be cracked, and needs to be inspected, based on what they have learned.
Students will make a hypothesis about which bridge is 'dangerous', and they will test that hypothesis in Lab 5.

Lab 5 - Testing a Hypothesis

Main Focus Question: How can I use data to test a hypothesis?

Based on the hypothesis students made in Lab 4, they will use the Eye Sensor on the Code Base to collect data about their chosen bridge in regular intervals.
They will record and analyze their data in order to test the hypothesis they formed in Lab 4.
Students will create a bridge inspection report summarizing their findings and how the data supports or refutes their hypothesis. They will share the reports with the class.

Unit Standards

Unit Standards will be addressed in every Lab within the Unit.

Computer Science Teachers Association (CSTA)

1B-DA-06 : Organize and present collected data visually to highlight relationships and support a claim.

How Standard is Achieved: In Lab 1, students predict whether using the eye light affects the way the Eye Sensor reports data. They collect Eye Sensor data about the colors on the bridge, both with and without the eye light. They organize the data in a table, and use it to support or refute the prediction they made. In Lab 2, students test a claim that a bridge in their city is unsafe. They record distance intervals and hue values reported by the Eye Sensor in a table. Students use this data and present it in a graph to see the location of the potential crack. In Lab 3, students use their collected data to show the relationship between the hue value and the location and size of cracks in their bridge, to determine the veracity of their claim.

In Lab 4, students are given a data set about various bridges, and analyze the data to make a hypothesis for which bridge is the most dangerous, and needs to be inspected. In Lab 5, they test their hypothesis from the previous Lab, by collecting data about their chosen bridge. Students organize and present their data and how the data supports their hypothesis in their bridge inspection reports.

Computer Science Teachers Association (CSTA)

1B-DA-07: Use data to highlight or propose cause-and-effect relationships, predict outcomes, or communicate an idea.

How Standard is Achieved: In Lab 1, students use collected data to highlight the cause and effect relationship between the eye light and how hue value is reported by the Eye Sensor. In Lab 2, students collect data by scanning the bridge using the Eye Sensor on the Code Base. They then use that data to communicate patterns in the data through a graph. In Lab 3, students use the collected data to communicate the size and location of crack(s) on the bridge.

In Lab 4, students use data to form and propose a hypothesis for which bridge is dangerous and in need of inspection. In Lab 5, they test their hypothesis, by collecting data about their chosen bridge, and using data to communicate their ideas about the safety of the bridge in their bridge inspection report.

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