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Communities and Opportunities

How can data be used to generate public will and inform local action for community improvements?

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Creative Artifact

Students use a set of metrics determined to be predictive of social mobility to identify an aspect of community life to prioritize for improvement. Students will use their research to craft a “data story” in which they communicate their analysis, ideas for continued exploration, and the questions their process has prompted. Data stories can take the form of a written brief, slide presentation, or poster and should combine data visualization, analysis and storytelling techniques to make complex information both accessible and meaningful.

Written Commentary

In order to rigorously apply a set of mobility predictors and aligned metrics to a selected geography, students will need to prepare, process, and analyze a series of data sets. As they engage in these phases of the data science process, students will be required to summarize their analysis, insights, outstanding questions and recommendations in writing. This process is designed to support students in crafting the “data story” that they will present in the exhibition at the end of the unit.

Exhibition

The class will hold a data walk convening in which a range of stakeholders engage in the “data story stations” student groups have prepared. Data walks are a collaborative approach that encourages discussion, analysis, and interpretation of data. As participants visit each station, students will not only share their process and analysis, but also facilitate a brief discussion in which participants have the opportunity to share additional context, insight, and engage in some of the questions the student research has prompted.

Implementation Notes

Credit Eligibility:

  • A person with a halo of humanities subjects around their head

    Humanities

  • nth root symbol

    Math

Prerequisites Needed:

Proficiency in Grade 8 CCSS Probability and Statistics standards

Modular Suggestions

A unit within a course tied to Social Sciences, Statistics or Data Science courses.  This could also be taught as an application-based unit following the AP Probability and Statistics exam.

TLE-Based Semester/Full-Year Course Suggestions

Contemporary Critiques:
Communities and Opportunities, Gentrification Photo Essay

Data Science or Statistics:
If you are interested in implementing additional TLEs into a Data Science or Statistics course, please let us know.

Standards Addressed

This unit helps build toward proficiency in the following College Board Statistics Skills:

Skill Category 1: Selecting Statistical Methods – Select methods for collecting and/or analyzing data for statistical inference.

  • 1.A – Identify the question to be answered or problem to be solved.
  • 1.B – Identify key and relevant information to answer a question or solve a problem.
  • 1.C– Describe an appropriate method for gathering and representing the data.

Skill Category 2: Data Analysis – Describe patterns, trends, associations and relationships in data.

  • 2.A – Describe data presented numerically or graphically.
  • 2.B – Construct numerical or graphical representations of distributions.

Skill Category 4: Statistical Argumentation – Develop an explanation or justify a conclusion using evidence from data, definitions, or statistical inference.

  • 4.A – Make an appropriate claim or draw an appropriate conclusion.
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