Learning Resource Type

Classroom Resource

Computer Science Principles Unit 4 Chapter 1 Lesson 3: Check Your Assumptions

Subject Area

Digital Literacy and Computer Science

Grade(s)

9, 10, 11, 12

Overview

This lesson asks students to consider carefully the assumptions they make when interpreting data and data visualizations. The class begins by examining how the Google Flu Trends project tried and failed to use search trends to predict flu outbreaks. They will then read a report on the Digital Divide which highlights how access to technology differs widely by personal characteristics like race and income. This report challenges the widespread assumption that data collected online is representative of the population at large. To practice identifying assumptions in data analysis, students are provided with a series of scenarios in which data-driven decisions are made based on flawed assumptions. They will need to identify the assumptions being made (most notably those related to the digital divide) and explain why these assumptions lead to incorrect conclusions.

Students will be able to:
- define the digital divide as the variation in access or use of technology by various demographic characteristics.
- identify assumptions made when drawing conclusions from data and data visualizations.

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    Digital Literacy and Computer Science (2018) Grade(s): 09-12

    DLCS18.HS.32

    Use data analysis tools and techniques to identify patterns in data representing complex systems.

    Unpacked Content

    UP:DLCS18.HS.32

    Vocabulary

    • datamining

    Knowledge

    Students know:
    • how to identify patterns in data.
    • how to select and apply data analysis tools and techniques.
    • use data analysis tools and techniques to identify patterns in data representing complex systems.

    Skills

    Students are able to:
    • evaluate data sets.
    • select and apply data analysis tools and techniques.
    • use technology to mine data.

    Understanding

    Students understand that:
    • data can be important in a problem
    • solving process.
    • tools exists to aid in the processing of complex data sets.
    • it can be more efficient to allow a program to identify patterns in a complex data set.
    Digital Literacy and Computer Science (2018) Grade(s): 09-12

    DLCS18.HS.37

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

    Unpacked Content

    UP:DLCS18.HS.37

    Vocabulary

    • model
    • simulations
    • hypotheses
    • phenomena
    • target system

    Knowledge

    Students know:
    • how to explain the use of models and simulations to generate new knowledge and understanding related to the phenomena or target system that is being studied.
    • how to explain the ability of models and simulations to test and support the refinement of hypotheses related to phenomena under consideration.
    a.
    • that modeling and simulations are way to extrapolate and interpolate unrest situation and scenarios to help formulate, test and refine hypotheses.
    b.
    • how to form a hypothesis.
    • how to test a hypothesis.
    • how to create a model or simulation.
    c.
    • that simulations or models can be created to test a hypothesis but not provide the information expected or intended.
    • that it is vital to verify the data being generated by a model or simulation.

    Skills

    Students are able to:
    • use a diagram or program to represent a model to express key properties of a phenomena or target system.
    • research existing models and simulations and how they are used to test and refine hypotheses.
    • explain how existing models and simulations are used to test and support the refinement of hypotheses.
    a.
    • create a model or simulation to formulate, test, and refine a hypothesis.
    • utilize a model or simulation to formulate, test, and refine a hypothesis.
    b.
    • form a model of a hypothesis.
    • test the hypothesis by collecting and analyzing data from a simulation.
    c.
    • examine a model or simulation to determine the correctness of the generated data.
    • examine a flawed model or simulation and identify areas in which it is providing incorrect data.

    Understanding

    Students understand that:
    • a simulation is based on a model and enables observation of the system as key properties change.
    • the accuracy of models and simulations are limited by the level of detail and quality of information used and the software and hardware used.
    • models and simulations are an effective and cost efficient way to understand phenomena and test and refine hypotheses.
    a.
    • models and simulations are way to extrapolate and interpolate unrest situation and scenarios to help formulate, test and refine hypotheses.
    • models and simulations can be the only cost- ot time-effective way to test a hypothesis.
    b.
    • Models and simulations can save money, are safer, usually requires less time, and do not have the environmental impact that a full experiment or operational test may induce.
    c.
    • while a process may operate without errors, that does not guarantee that the process is providing accurate data to meet your needs.
    Link to Resource

    CR Resource Type

    Lesson/Unit Plan

    Resource Provider

    Code.org
    Accessibility
    License

    License Type

    Custom
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