Implementing VEX GO STEM Labs
STEM Labs are designed to be the online teacher’s manual for VEX GO. Like a printed teacher’s manual, the teacher-facing content of the STEM Labs provides all of the resources, materials, and information needed to be able to plan, teach, and assess with VEX GO. The Lab Image Slideshows are the student-facing companion to this material. For more detailed information about how to implement a STEM Lab in your classroom, see the Implementing VEX GO STEM Labs article.
Goals and Standards
Goals
Students will apply
- How to monitor and record Eye Sensor data while a project is running.
- How to use the Hue Chart to determine the color associated with a particular hue value.
- How to use sensor data as evidence to support a prediction.
Students will make meaning of
- How to effectively implement the Eye Sensor and analyze sensor data to determine the reported color variations along the surface of a bridge.
- How a sensor can produce and report data about the real world, like the hue value of a detected object.
- How to use collected data to support a prediction.
Students will be skilled at
- Following Build Instructions to build the Code Base 2.0 - Eye Down VEX GO build.
- Adding a block to the Monitor to view sensor data in real time in VEXcode GO.
- Using a Data Collection Sheet to record data about each section of the bridge.
- Moving the Code Base - Eye Down along the bridge so the sensor can report data effectively.
- Using the Hue Chart with reported hue values to determine the aligned color for each value.
Students will know
- That hue value is a numerical representation of a color.
- That the Eye Sensor reports hue value data about objects it detects.
- That the eye light on the sensor can add light to a detectable object.
- That changing the amount of light around the Eye Sensor changes the reported hue values.
- That the Monitor in VEXcode GO can be used to view sensor data in real time while a project is running.
Objective(s)
Objective
- Students will effectively use the Eye Sensor on the Code Base to view, record, and report sensor data to analyze sections of the bridge.
- Students will use the hue chart with collected hue value data to determine the color associated with each numerical value.
- Students will make a prediction about whether using the eye light will affect the reported sensor data, and will use their recorded data as evidence to support or refute their prediction.
Activity
- Students will view Eye Sensor data using the Monitor in VEXcode GO as they manually move the Code Base along the sections of the bridge. For each of the five bridge sections, students will record the numerical hue value data on the Data Collection Sheet.
- Students will interpret data by using the Hue Chart to identify the associated colors of the numerical hue values; students will add the color data to the Data Collection Sheet.
- In Play Part 1, students collect hue value data about each section of the bridge using the Eye Sensor with the eye light off. In the Mid Play Break, they discuss how light affects the data reported by the Eye Sensor and make a prediction about whether or not the hue value data will change if they turn the eye light on. In Play Part 2, students collect hue value and color data for each section of the bridge with the eye light on, and use the data to either confirm or refute their prediction.
Assessment
- Students will share and discuss their collected data during the Mid Play Break to compare the hue values they recorded to others in the class. During the Share section, students will share their data collected in both Play Parts 1 and 2 and compare the difference in the recorded hue values with the eye light off and on.
- During the Mid Play Break and Share sections, students share the data collected, and compare and contrast the hue values and recorded colors with others in the class. They will discuss why the hue values recorded by individual groups may be variable, but the associated colors are more consistent from group to group.
- In the Share section, students share their predictions and how their collected data either supports or refutes their prediction. They compare the data collected with the eye light on to that with the light off to determine if the reported values are affected by additional light.