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A practice of both science and engineering is to use and construct models as helpful tools for representing ideas and explanations. These tools include diagrams, drawings, physical replicas, mathematical representations, analogies, and computer simulations.

As part of the IVD Challenges, students complete the “Engineering Spiral”, requiring them to develop ideas, build prototypes and test performance.  In the process of developing ideas, they use mathematical models to predict vehicle performance and make design decisions.  As an example, in Full Scale IVD, teams may use mathematical modeling of their vehicle characteristics, and the competition track, to predict energy losses during a “heat” of the competition.  These mathematical models can be used to evaluate the impact of changing wheels & tires, adding aerodynamic bodies, or changing limiting acceleration rates.  The models also inform battery sizing, and enable teams to identify an appropriate battery pack for their needs.   These mathematical models are often built using spreadsheet applications, allowing students to quickly and easily recalculate impacts of various design decisions.  As the design evolves, physical models (prototypes) are constructed to conduct design validation testing.

Scientists and engineers plan and carry out investigations in the field or laboratory, working collaboratively as well as individually. Their investigations are systematic and require clarifying what counts as data and identifying variables or parameters.

Throughout the IVD Design process, students identify critical vehicle parameters and develop innovative methods of data collection to inform their design decisions.  As teams iterate the Engineering Spiral, they develop better and better solutions.  A critical component of this iterative process is to test and document the resulting changes in vehicle performance following design changes.  As with scientists who create “control groups” to isolate data streams, our student design teams must carefully design and carryout test protocols that isolate individual vehicle characteristics to accurately determine performance impacts.  Student teams archive their test data in Engineering Journals that are submitted as part of their final presentation.

Scientific investigations produce data that must be analyzed in order to derive meaning. Because data patterns and trends are not always obvious, scientists use a range of tools—including tabulation, graphical interpretation, visualization, and statistical analysis—to identify the significant features and patterns in the data. Scientists identify sources of error in the investigations and calculate the degree of certainty in the results. Modern technology makes the collection of large data sets much easier, providing secondary sources for analysis. 

Testing is a critical component of the Engineering Spiral, and data collection & analysis is obviously a critical component of testing.  This data collection and analysis is prevalent in all of the IVD Challenges as students build prototypes and test their performance to evaluate overall success of the vehicle and impacts of design decisions.  Specifically, Mini IVD places a large amount focus on the testing aspect of the engineering process.  Mini IVD students complete baseline testing on a stock vehicle, then design and execute testing protocols to determine performance impact of component modifications and maximize overall vehicle performance.  Through the Mini IVD Performance Missions, students investigate the impact of varying shock fluid density and viscosity, changing tire types, modifying gear ratios, altering battery types and capacities, and more.  With each change, students carefully document the performance data, analyze the results, and present their findings as part of their engineering presentation.

In both science and engineering, mathematics and computation are fundamental tools for representing physical variables and their relationships. They are used for a range of tasks such as constructing simulations; statistically analyzing data; and recognizing, expressing, and applying quantitative relationships.

Using mathematical modeling to simulate and predict IVD vehicle performance is a critical element of the IVD Design Challenges.  As an example, Full Scale IVD students calculate aerodynamic drag, rolling resistance, acceleration energy, combined with vehicle speed and acceleration predictions, coupled with track characteristics (curves, straights, hills, etc) to determine vehicle energy requirements per lap.  They also use torque curves and their vehicle performance characteristics to determine gear ratios and select an appropriate drive motor.  The use of mathematical modeling is a key element helping students to understand what engineering is, and what engineers do.

The products of science are explanations and the products of engineering are solutions.

Each of the Square One IVD Challenges is completely built around developing products (machines) to complete tasks.  Designing and building solutions is the predominant focus of our work with students.  In every one of the IVD challenges, students develop machines (solutions or products) to complete a variety of missions.   

• Full Scale IVD – students build electric go karts to maximize distance travelled in a limited time on two different tracks, focusing on energy efficiency and energy management
• Mini IVD – students “test and tweak” RC cars to maximize vehicle dynamics and performance, tailored to a variety of track conditions.  Team vehicles compete in a high speed challenge, off-road agility course, and a road course.
• Autonomous IVD – students design and build a vehicle to function autonomously (without any driver input), with capability to parallel park, avoid collisions, and follow lane lines.
• Underwater IVD – students design and build an underwater robot to pick up items off the bottom of the pool, complete underwater surveying, and completing a high speed “ROV drag race”

In all of these cases, students are provided project parameters (the problems) and work as teams to develop solutions (their vehicles).

Argumentation is the process by which explanations and solutions are reached.

Argument with evidence is a critical engineering skill and is tightly integrated into Square One IVD Challenges.  As members of engineering teams, students are inherently required to justify their ideas with evidence when evaluating design decisions in a collaborative space with other team members.  We encourage teams to embrace this process and even document their work using the “Claim, Evidence, Reasoning (CER) Framework”.  In Mini IVD, CER documentation is required as a component of each teams’ engineering presentation.  CER is taught in a variety of classroom settings and content areas, but IVD Challenges provide a uniquely relevant context in which to use CER, clearly demonstrating the value of evidence based argumentation to students, specifically in an engineering context.

Scientists and engineers must be able to communicate clearly and persuasively the ideas and methods they generate. Critiquing and communicating ideas individually and in groups is a critical professional activity. 

Communication is a critical skill for students and professionals alike.  Square One embraces the need for authentic, relevant technical communication as part of the IVD Challenges.  Each IVD Design Challenge includes requirements for a variety of communication elements within the judged awards (Innovation, Ambassadorship, Presentation, etc).  These award requirements compel students to demonstrate their skills in written and spoken communication via their Ambassadorship Outreach programs, their Engineering Presentations, their Marketing Assets, and their Engineering Journals.  Students must clearly articulate the design parameters, the products of their brainstorming, the design decisions they made, how they functioned as a team in a collaborative decision making space, the testing they completed and results of their data analysis, the outcomes of their outreach efforts, the unique challenges they faced and how they were resolved, and much more.

The NGSS Engineering Practices outline many of the key skills utilized by modern engineers, beyond just understanding engineering principles.  They represent the “how” and “why” of engineering, in addition to the “what”.  The Square One IVD Challenges are completely built around the premise of students designing machines to maximize performance in challenge missions – i.e. students ENGINEERING vehicles.  The IVD Challenges are therefore inherently suited to provide students the rich authentic context in which to learn these engineering skills and demonstrate their mastery.