|Address||P.O. Box 219 Batavia, IL 60510|
Student access for one year to a standards-based, web-based virtual modeling STEM application. Students are guided through an engaging, realistic design development process resulting in virtual simulations and competitions with other students throughout their class or district. The software even provides instructions on how to build a real model, allowing students to go one step further by creating actual physical representations of their virtual designs. Includes a fully integrated teacher LMS control center.
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Using the custom, built-in CAD system of WhiteBox Learning, students develop 3D models in minutes. The simplicity of the modeling process puts focus where it belongs—on learning the critically important science, technology, engineering and math (STEM) concepts that live just below the surface. After designing and analyzing in the web-based design software, student connect the virtual to the physical by printing custom templates that can be used to build physical representations of their designs.
The WhiteBox Learning Process
Begins with Research! In the research section, students begin by exploring all the theory and concept background they will need to proceed with the activity. This section includes background text with plenty of interactive activities, tools and tutorials to ensure students are well prepared for the remaining sections. Next, students move on to the Design section. Engineers combine scientific concepts and theories with reality using tools to visualize their designs in 3D. In this section, students use the custom, built-in CAD system to create 3D models on screen and quickly choose between a variety of components to improve their designs. Then, in the Analysis section, students work with a number of built-in tools to see how well their designs stand up to the scientific principles explored in the Research section. Creating the models is fun and exciting, but won’t mean much if not supported by science.
Then it’s finally time to compete in the Air Show Competition! In this competition portion of the activity, students see how their designs measure up against each other. After completing their design and applying any improvements, the Outputs section creates a drawing for a physical build of the gliders. Drawings, a design specifications report and templates can be found in this section. Now that students have conquered the virtual world, it’s time to Build and Test the gliders in the physical world. Using the included materials, students use the instructions and tips in this section to build a physical representation of their design.
The Benefits of WhiteBox Learning
Free software trial available! Contact Flinn Scientific for details.
MS-PS2-2. Plan an investigation to provide evidence that the change in an object’s motion depends on the sum of the forces on the object and the mass of the object
MS-ETS1-1. Define the criteria and constraints of a design problem with sufficient precision to ensure a successful solution, taking into account relevant scientific principles and potential impacts on people and the natural environment that may limit possible solutions.
MS-ETS1-3. Analyze data from tests to determine similarities and differences among several design solutions to identify the best characteristics of each that can be combined into a new solution to better meet the criteria for success.
MS-ETS1-4. Develop a model to generate data for iterative testing and modification of a proposed object, tool, or process such that an optimal design can be achieved.
HS-PS2-3. Apply scientific and engineering ideas to design, evaluate, and refine a device that minimizes the force on a macroscopic object during a collision.
HS-ETS1-1. Analyze a major global challenge to specify qualitative and quantitative criteria and constraints for solutions that account for societal needs and wants.
HS-ETS1-2. Design a solution to a complex real-world problem by breaking it down into smaller, more manageable problems that can be solved through engineering.
HS-ETS1-4. Use a computer simulation to model the impact of proposed solutions to a complex real-world problem with numerous criteria and constraints on interactions within and between systems relevant to the problem.