Project 2: Data Focused Piece

How can I create a use data to create a data-focused piece of computational work?

Timeline

~25 Days (5 Weeks)

• 1 Week Ideation/Planning

• 3 Weeks Project Mode

• 1 Week Presentations/Wrap Up

NYS Computing Standards

Due to the open-ended nature of projects in this course, they have the chance to cover all of the NYS Computational Thinking Standards. This project may especially highlight:

• 9-12.CT.1 Create a simple digital model that makes predictions of outcomes.

• 9-12.CT.2 Collect and evaluate data from multiple sources for use in a computational artifact.

• 9-12.CT.3 Refine and visualize complex data sets showing how to tell different stories with the same data set.

Project Focus Narrative

In Project 2, students will use data - from a large pre-existing or self-collected data set - to create a data-focused piece of computational work. Similarly to Project 1, the final output may vary based on the language students are working in. JavaScript may create a data visualization or interactive dashboard; Python may be more report focused. Students must use data, but they should lean into the strengths of the language they are working in.

This project is an excellent time to integrate a live API for the data, but it is not required.

The ultimate outcome of this project is more persuasive. The final piece should use the data to tell a story to the viewer, or convince them of a certain point of view. The data itself may focus on something in the real world/serious or something that is more fun/whimsical - that part is up to student interest.

Texts/Resources

[TBD]

Showcase Skills

• Data Analysis: Demonstrating proficiency in analyzing large datasets to extract meaningful insights.

• Data Visualization: Creating visually compelling and informative data visualizations, potentially by using tools such as D3.js, Matplotlib, Plotly, or similar. Students may utilize any skills/tools that make sense for their data visualization.

• Report/Narrative Writing: Crafting clear and concise reports or narratives based on the findings from the data analysis.

• API Integration (Optional): Utilizing live APIs to enhance the data analysis or visualization process, if applicable/available.

• Persuasive Communication: Effectively communicating the insights and conclusions derived from the data to persuade or inform the viewer.

• Research Skills: Conducting thorough research to gather relevant data and background information for the project.

• Critical Thinking: Applying critical thinking skills to analyze data and draw meaningful conclusions or insights.

Project Requirements

• Data Collection: Students must use a large pre-existing dataset or collect their own data for analysis.

• Data Analysis: Perform comprehensive data analysis to uncover patterns, trends, or correlations within the dataset.

• Data Visualization: Create visually engaging and informative data visualizations, such as charts, graphs, maps, or interactive dashboards.

• Report or Narrative: Develop a persuasive report or narrative that tells a compelling story using the data insights to convey a particular viewpoint or message.

• API Integration (Optional): If feasible, integrate live APIs to supplement the dataset or enhance the analysis process.

• Storytelling: Use the data to craft a compelling narrative or storyline that engages the viewer and effectively communicates the key insights or conclusions.

• Ethical Considerations: Ensure ethical and responsible use of data, respecting privacy and confidentiality if working with sensitive information. Students should strive for unbiased data sources and should be able to cite from reliable sources.

• Peer Review: Participate in peer review sessions to provide and receive feedback on project progress and final deliverables.

• Presentation: Prepare a presentation or demonstration showcasing the data analysis, visualization, and persuasive narrative to effectively communicate the project's findings and message.

Check-Ins and Deliverables

[TBD]