In a unit on the fundamentals of computer science, electrical engineering, discrete math, or symbolic logic, Phoenix Protocol would fit right in as a discovery-flavored advance organizer or as some extra at-home practice. If used for these specific learning goals, teachers should work to explicitly make the connections between the game's abstract circles and squares and the very concrete one/zero, true/false world or to engage students in discussion and debate to make these connections themselves.
The game could also make for great general problem-solving and design-thinking practice in almost any class or as supplemental practice for learners who struggle with binary numbers as they're traditionally taught.Continue reading Show less
In Phoenix Protocol, players must repair a ship marooned in deep space by making connections on a grid of flowing circles and squares using binary logic gates to transform input patterns into multiple outputs. The game introduces the concepts of links, splits, NOT gates, AND gates, and OR gates and simplifies binary numbers to brightly colored circles and squares. Solving each level of eight puzzles repairs part of the ship and unlocks more complex tasks, all on the same five-by-five grid.
The interface is all drag-and-drop in a crisply designed, pulsing, flashing, science-fiction wonderland with a peppy techno-music soundtrack. A kooky, irreverent robot assistant (quite reminiscent of Portal's iconic GLaDOS) adds hilarious encouragement and helpful hints and tutorials along the way.
Phoenix protocol uses a trial-and-error discovery learning approach that works extremely well for teaching otherwise tricky logical concepts. The possibility of multiple solutions for each puzzle encourages design thinking and engineering habits of mind, while gradual introduction of increasingly complex concepts and good progression through more difficult levels provides great scaffolding for the properties of boolean functions.
There aren't any ones or zeros, nor any mention of circuits, electronics, or discrete math -- and that's both this game's biggest strength and biggest weakness. By reinterpreting the content as shape puzzles, it makes the content extremely accessible, but it's at the cost of outside transfer. Making the jump to electrical engineering and computer science will be tricky. Teacher context would add a lot: Some gradual introduction to more common representations would make that transition a lot smoother.
Key Standards Supported
Define a simple design problem reflecting a need or a want that includes specified criteria for success and constraints on materials, time, or cost.
Generate and compare multiple possible solutions to a problem based on how well each is likely to meet the criteria and constraints of the problem.
Plan and carry out fair tests in which variables are controlled and failure points are considered to identify aspects of a model or prototype that can be improved.
Ask questions, make observations, and gather information about a situation people want to change to define a simple problem that can be solved through the development of a new or improved object or tool.
Develop a simple sketch, drawing, or physical model to illustrate how the shape of an object helps it function as needed to solve a given problem.
Analyze data from tests of two objects designed to solve the same problem to compare the strengths and weaknesses of how each performs.
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.
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.
Evaluate competing design solutions using a systematic process to determine how well they meet the criteria and constraints of the problem.
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.
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.
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