In this unit, students will explore using computational tools to store massive amounts of data, manipulate and visualize data, find patterns in data, and draw conclusions from data. Students will consider how the modern wealth of data collection has impacted society in positive and negative ways. Students will work in teams to investigate a question of personal interest and use public data to present a data-driven insight to their peers. They will develop visualizations to communicate their findings, and embed their visualizations in their portfolio websites.
Visualizing and Interpreting Data
Lessons:
Getting Started with Data
Visualizing and Interpreting Data
DAT-2.A.1 DAT-2.D.5 DAT-2.A.2 DAT-2.D.6 DAT-2.C.1 DAT-2.E.1 DAT-2.D.1 DAT-2.E.2 DAT-2.D.2 DAT-2.E.3 DAT-2.D.3 DAT-2.E.5 DAT-2.D.4
Filtering and Cleaning Data
Patterns and Trends
Search Tools
Tables, Diagrams and Displays
Interactive Visualizations
Combining Data Sources
Collecting Data and Data Limitations
Lessons:
Data Collection and Limitations
DAT-2.A.3 DAT-2.C.2 DAT-2.A.4 DAT-2.C.3 DAT-2.B.1 DAT-2.C.4 DAT-2.B.2 DAT-2.C.5 DAT-2.B.3 DAT-2.C.6 DAT-2.B.4 DAT-2.D.6 DAT-2.B.5 CRD-2.F.3
Metadata
Correlation
Using a Variety of Sources
Incomplete or Invalid Data
Bias
Surveys, Testing, Interviews
Example Activities and Big Idea/Computational Thinking Practice
Importance of Metadata: Students consider how metadata can increase the effective use of data or data sets by providing additional information. They consider the importance of metadata and reflect on why metadata is important for a data set, how metadata help in finding specific data, and what metadata should reveal about the data.
[Big Idea DAT][Computational Thinking Practice 5]