In the world of STEM education, teaching theory is only half the equation. The real challenge? Developing a mindset that mirrors how engineers think. That means fostering analysis, experimentation, adaptability, and the ability to navigate uncertainty. Surprisingly, one of the most powerful tools for this isn’t in textbooks — it’s in simulation-based games. These aren’t just for fun. They’re shaping the way kids approach problems, manage constraints, assess risks, and achieve goals through structured trial and error.
What Is Engineering Thinking — In Simple Terms
Engineering thinking isn’t just about building things. It’s a mental process, a way of approaching any challenge logically and strategically. At its core, it involves three core abilities:
- Understanding the problem
- Developing and testing a solution
- Adjusting and implementing the best outcome
This cycle fits naturally into the structure of many games. Players are thrown into complex situations, handed a limited set of tools or resources, and expected to find a path forward. They build, fail, adapt, and try again. It’s hands-on learning without the fear of failure. The game becomes a living, breathing lab where students gain real insight by doing — not just listening.
How Simulations Teach the Engineering Approach
Games as Models of Real-World Challenges
Educational simulations are designed to mimic real-world engineering situations. Whether it’s about load-bearing design, energy distribution, or robotic systems, these games put players in the driver’s seat of intricate systems. Key learning areas include:
- Bridge building (e.g., Bridge Constructor): Students learn how weight, tension, and distribution impact structural integrity.
- Aerospace design (e.g., SimpleRockets, Kerbal Space Program): Crafting launch vehicles and calculating orbits builds spatial awareness and physics intuition.
- Redstone mechanics and logic circuits (e.g., Minecraft Education): Players engage in basic automation and system logic, which mirrors digital electronics and coding fundamentals.
- Energy and logistics simulators: These help players think in systems — balancing efficiency, resources, and constraints.
The gameplay might look simple, but behind every success lies a chain of calculations, assumptions, and smart design decisions — just like in real-world engineering.
Aviator: A Surprising Example of a Learning Simulation
Why Aviator Belongs in the STEM Conversation
At first glance, Aviator by Spribe might seem like an outlier. It’s fast-paced, data-light, and more commonly found in entertainment circles. Yet when you peel back its surface, it reveals a structure that aligns remarkably well with core engineering thinking.
Here’s how:
- Risk analysis: Players must decide when to cash out. Waiting too long risks losing it all, while exiting early might limit gains. This mirrors engineering trade-offs — balancing safety, cost, and reward.
- Trend visualization: The constantly rising curve is a form of real-time graph interpretation. Players read patterns and anticipate behavior, similar to analyzing test data.
- Uncertainty navigation: There are no guaranteed outcomes. Each decision must account for probability and timing — a perfect metaphor for scenario modeling in engineering design.
When framed correctly, Aviator becomes a case study in variable control. It invites learners to ask: “Where’s the optimal exit point?”, “How does the curve evolve?”, “What would happen if we pushed a little further?” These questions echo the very heart of scenario planning and design optimization.
What Simulations Give Young Learners Beyond STEM
The benefits of game-based simulations stretch well beyond equations and experiments. They build crucial soft skills that are just as important in the lab as in life.
| Skill Developed | How It’s Taught in Simulation Games |
|---|---|
| Systems thinking | By managing complex, interconnected elements |
| Decision-making | Through constant trade-offs between risk and reward |
| Collaboration | In multiplayer or role-based team simulations |
| Iterative problem-solving | Learning from failure: try → fail → adjust → retry |
| Resilience | No real penalties for mistakes — learning is the outcome |
Instead of fearing errors, players are encouraged to explore. Every failure is feedback. Every retry is a step forward. This mindset — fail fast, learn fast — is core to how real engineers work, and simulations help it feel natural from the start.