February 16, 2016

This module introduces the concept of Algorithm Design in Computational Thinking. Examples of algorithm design are shown and resources for teaching algorithm design skills in the classroom are introduced.

- Computer Science > Coding
- Computer Science > Computational Thinking
- Computer Science > Computers in Society
- Computer Science > Human Computer Interaction

- Grade 6
- Grade 7
- Grade 8
- Grade 9
- Grade 10
- Professional Education & Development
- Vocational Training

Use addition and subtraction within 20 to solve word problems involving situations of adding to, taking from, putting together, taking apart, and comparing, with unknowns in all positions, e.g., by using objects, drawings, and equations with a symbol for the unknown number to represent the problem.

Solve word problems that call for addition of three whole numbers whose sum is less than or equal to 20, e.g., by using objects, drawings, and equations with a symbol for the unknown number to represent the problem.

Know the formulas for the area and circumference of a circle and use them to solve problems; give an informal derivation of the relationship between the circumference and area of a circle.

Use facts about supplementary, complementary, vertical, and adjacent angles in a multi-step problem to write and solve simple equations for an unknown angle in a figure.

Solve real-world and mathematical problems involving area, volume and surface area of two- and three-dimensional objects composed of triangles, quadrilaterals, polygons, cubes, and right prisms.

Understand the concept of a ratio and use ratio language to describe a ratio relationship between two quantities.

Understand solving an equation or inequality as a process of answering a question: which values from a specified set, if any, make the equation or inequality true? Use substitution to determine whether a given number in a specified set makes an equation or inequality true.

Solve real-world and mathematical problems by writing and solving equations of the form x + p = q and px = q for cases in which p, q and x are all nonnegative rational numbers.

Use variables to represent two quantities in a real-world problem that change in relationship to one another; write an equation to express one quantity, thought of as the dependent variable, in terms of the other quantity, thought of as the independent variable. Analyze the relationship between the dependent and independent variables using graphs and tables, and relate these to the equation.

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.

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.

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.

Analyze data from tests of an object or tool to determine if it works as intended.

Analyze and interpret data to make sense of phenomena using logical reasoning.

Analyze and interpret data to determine similarities and differences in findings.

Ask questions that arise from examining models or a theory to clarify relationships.

Analyze complex real-world problems by specifying criteria and constraints for successful solutions.

Undertake a design project, engaging in the design cycle, to construct and/or implement a solution that meets specific design criteria and constraints.

Apply scientific ideas or principles to design, construct, and test a design of an object, tool, process or system.

Design, evaluate, and/or refine a solution to a complex real-world problem, based on scientific knowledge, student-generated sources of evidence, prioritized criteria, and tradeoff considerations.

Make a claim about the merit of a solution to a problem by citing relevant evidence about how it meets the criteria and constraints of the problem.

Evaluate competing design solutions based on jointly developed and agreed-upon design criteria.

Evaluate competing design solutions to a real-world problem based on scientific ideas and principles, empirical evidence, and logical arguments regarding relevant factors (e.g. economic, societal, environmental, ethical considerations).

Make observations and/or measurements to produce data to serve as the basis for evidence for an explanation of a phenomenon or test a design solution.

Use mathematical representations of phenomena to support claims.

Use mathematical representations of phenomena to describe explanations.

Patterns can be used as evidence to support an explanation.

Different patterns may be observed at each of the scales at which a system is studied and can provide evidence for causality in explanations of phenomena.

Cause and effect relationships may be used to predict phenomena in natural or designed systems.

Relationships can be classified as causal or correlational, and correlation does not necessarily imply causation.

Systems can be designed to cause a desired effect.

When investigating or describing a system, the boundaries and initial conditions of the system need to be defined and their inputs and outputs analyzed and described using models.

Models can be used to predict the behavior of a system, but these predictions have limited precision and reliability due to the assumptions and approximations inherent in models.

Models (e.g., physical, mathematical, computer models) can be used to simulate systems and interactions—including energy, matter, and information flows—within and between systems at different scales.