Search the California Content Standards

Standard:
Refine computational models to better represent the relationships among different elements of data collected from a phenomenon or process.

Descriptive Statement:
Computational models are used to make predictions about processes or phenomena based on selected data and features. They allow people to investigate the relationships among different variables to understand a system. Predictions are tested to validate models. Students evaluate these models against real-world observations. For example, students could use a population model that allows them to speculate about interactions among different species, evaluate the model based on data gathered from nature, and then refine the model to reflect more complex and realistic interactions.

Standard:
Use collaboration tools and methods to increase connectivity with people of different cultures and careers.

Descriptive Statement:
Increased digital connectivity and communication between people across a variety of cultures and in differing professions has changed the collaborative nature of personal and professional interaction. Students identify, explain, and use appropriate collaborative tools. For example, students could compare ways that various technological collaboration tools could help a team become more cohesive and then choose one of these tools to manage their teamwork. Alternatively, students could use different collaborative tools and methods to solicit input from not only team members and classmates but also others, such as participants in online forums or local communities.

Standard:
Compare and contrast fundamental data structures and their uses.

Descriptive Statement:
Data structures are designed to provide different ways of storing and manipulating data sets to optimize various aspects of storage or runtime performance. Choice of data structures is made based on expected data characteristics and expected program functions. Students = compare and contrast how basic functions (e.g.., insertion, deletion, and modification) would differ for common data structures including lists, arrays, stacks, and queues. For example, students could draw a diagram of how different data structures change when items are added, deleted, or modified. They could explain tradeoffs in storage and efficiency issues. Alternatively, when presented with a description of a program and the functions it would be most likely to be running, students could list pros and cons for a specific data structure use in that scenario.

Standard:
Evaluate the ability of models and simulations to test and support the refinement of hypotheses.

Descriptive Statement:
A model could be implemented as a diagram or a program that represents key properties of a physical or other system. A simulation is based on a model, and enables observation of the system as key properties change. Students explore, explain, and evaluate existing models and simulations, in order to support the refinement of hypotheses about how the systems work. At this level, the ability to accurately and completely model and simulate complex systems is not expected. For example, a computer model of ants following a path created by other ants who found food explains the trail-like travel patterns of the insect. Students could evaluate if the output of the model fits well with their hypothesis that ants navigate the world through the use of pheromones. They could explain how the computer model supports this hypothesis and how it might leave out certain aspects of ant behavior and whether these are important to understanding ant travel behavior. Alternatively, students could hypothesize how different ground characteristics (e.g., soil type, thickness of sediment above bedrock) relate to the severity of shaking at the surface during an earthquake. They could add or modify input about ground characteristics into an earthquake simulator, observe the changed simulation output, and then evaluate their hypotheses.