DCSDesign Computational Solutions
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Design Computational Solutions (DCS) is the ability to identify a design issue(s) and describe in words what inputs, a set of instructions, and outputs, are needed to address the design issue.

Abbreviated description used in reports
Design Computational Solutions (DCS) is the ability to identify a design issue(s) and describe in words what inputs, a set of instructions, and outputs, are needed to address the design issue.
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Highest level
DCS6 Strategic/Step Beyond (DCS6): Makes a convincing argument for the best solution to achieve a given purpose through articulating trade-offs among multiple approaches/ competing goals Fluidly generates multiple (novel/divergent) solutions using multiple evaluation criteria (e.g., accuracy, efficiency, reusability) Does not prematurely foreclose on known solutions (i.e., avoids rote-application of algorithms), seeking novel/innovative solution(s)
  • Makes a convincing argument for the best solution to achieve a given purpose through articulating trade-offs among multiple approaches/ competing goals
  • Fluidly generates multiple (novel/divergent) solutions using multiple evaluation criteria (e.g., accuracy, efficiency, reusability)
  • Does not prematurely foreclose on known solutions (i.e., avoids rote-application of algorithms), seeking novel/innovative solution(s)
Student makes a convincing argument for the best solution to achieve a given purpose through articulating trade-offs among multiple approaches/ competing goals; fluidly generates multiple (novel/divergent) solutions using multiple evaluation criteria (e.g., accuracy, efficiency, reusability); and does not prematurely foreclose on known solutions (i.e., avoids rote-application of algorithms), seeking novel/innovative solution(s).

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DCS5 Integrated Relational - Complex (DCS5): Generates multiple solutions or approaches to a problem using complex operations that require relational understanding among a set of operations Attends to special situations such as boundary conditions or edge cases; explains under what condition a particular solution would work (generalization; e.g., input values have to be sorted) (Re)frames a problem into a familiar task type, by foregrounding certain key aspects while backgrounding less important aspects
  • Generates multiple solutions or approaches to a problem using complex operations that require relational understanding among a set of operations
  • Attends to special situations such as boundary conditions or edge cases; explains under what condition a particular solution would work (generalization; e.g., input values have to be sorted)
  • (Re)frames a problem into a familiar task type, by foregrounding certain key aspects while backgrounding less important aspects
Student generates multiple solutions or approaches to a problem using complex operations that require relational understanding among a set of operations; attends to special situations such as boundary conditions or edge cases; explains under what condition a particular solution would work (generalization; e.g., input values have to be sorted); and (re)frames a problem into a familiar task type, by foregrounding certain key aspects while backgrounding less important aspects.

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DCS4 Integrated Relational - Simple (DCS4): Designs a solution or approach to a more complex problem that requires relational understanding of a few subparts that constitute a more complex system or process Solution includes one or more complex operations or features (e.g., if-then-else, looping, nesting) Decomposes a complex problem into several related subparts
  • Designs a solution or approach to a more complex problem that requires relational understanding of a few subparts that constitute a more complex system or process
  • Solution includes one or more complex operations or features (e.g., if-then-else, looping, nesting)
  • Decomposes a complex problem into several related subparts
Student designs a solution or approach to a more complex problem that requires relational understanding of a few subparts that constitute a more complex system or process; solution includes one or more complex operations or features (e.g., if-then-else, looping, nesting); and decomposes a complex problem into several related subparts.

Identifies the key inputs and goal of the computational problem and relating them to the constraints of the problem

  • The most important considerations when loading the elevator is trying to get as close as you can to the maximum capacity of 2,000 lbs with 3 boxes. You want to do these things so you can make the least amount of rounds trips. [sample response]
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DCS3 Multi-Step Solution (DCS3): Designs a solution or approach that requires a sequence of a few subparts through a step-by-step (line-by-line) approach, including necessary input(s) and output(s) Solution may include at least one complex operation or feature (loop, conditional statement, nesting, etc.) Decomposes a simple problem into a few, discrete subparts
  • Designs a solution or approach that requires a sequence of a few subparts through a step-by-step (line-by-line) approach, including necessary input(s) and output(s)
  • Solution may include at least one complex operation or feature (loop, conditional statement, nesting, etc.)
  • Decomposes a simple problem into a few, discrete subparts
Student designs a solution or approach that requires a sequence of a few subparts through a step-by-step (line-by-line) approach, including necessary input(s) and output(s); solution may include at least one complex operation or feature (loop, conditional statement, nesting, etc.); and decomposes a simple problem into a few, discrete subparts.

Identifies the inputs and goal of a computational problem with a few discrete subparts

  • The weight and number of boxes in the elevator are the most important considerations when designing the loading process. They are important to maximize the efficiency in moving the boxes while not making it too heavy on the elevator in case it will break. [sample response]
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DCS2 One-Step Solution (DCS2): Identifies a part of a sequence that can be automated (simple pattern recognition) Identifies a goal, input(s), set of instructions, and/or output(s) in a given context

  • Identifies a part of a sequence that can be automated (simple pattern recognition)
  • Identifies a goal, input(s), set of instructions, and/or output(s) in a given context
Student identifies a part of a sequence that can be automated (simple pattern recognition); and identifies a goal, input(s), set of instructions, and/or output(s) in a given context.

Identifies the goal, input, process and/or output of a computational problem

  • The most important considerations to keep in mind are not going over the weight limit and to have the least number of round trips. [sample response]
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DCS1 Attempting/Partial (DCS1): Attempts to design a solution, and uses recognisably appropriate vocabulary, but cannot provide a meaningful or relevant response
  • Attempts to design a solution, and uses recognisably appropriate vocabulary, but cannot provide a meaningful or relevant response
Student attempts to design a solution, and uses recognisably appropriate vocabulary, but cannot provide a meaningful or relevant response.

Identifies an alternative input and/or goal for a computational problem

  • We need to start loading the boxes from the lightest to the heaviest so that the elevator will not break. [sample response]
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DCS0 Not Evident (DCS0): Attempts to design a solution but response does not relate to the problem....
  • Attempts to design a solution but response does not relate to the problem.
  • No attempt to design a solution.
Student attempts to design a solution but response does not relate to the problem, or makes no attempt to design a solution.

Does not provide a relevant or meaningful response

  • I don't know. [sample response]
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Lowest level