In the previous unit, students learned how data is stored on the computer in binary format. They learned about storage and file compression. In Unit 5, students will learn what we can do with the data. This unit digs into the concept of Big Data. From the APCSP course description...Students can use the data to solve problems such as raising awareness for a cause, using census data to determine which state will gain seats in the House of Representatives, or using traffic and cost data to determine the ideal location for prom. In this big idea, students will gain a deep understanding of how information is stored on a computer in binary and seamlessly translated into what is seen on the screen or heard through speakers. Students will also learn how data are processed to learn something new.
It is critically important that students learn to manage, interpret and use the data in an ethical manner. Bias does exist in algorithms and in this unit, students will not only be researching examples of algorithmic bias and analyzing the impacts of those biases, they will be developing protocols and standards to prevent that from happening in their own projects.
The ARC Challenge for this unit is the continuation of ARC Challenge #4, a data analysis project. A Big Data Analytics firms has hired the students to investigate & analyze an industry concern. Students will determine the concern, write questions that need to be answered, identify needed data points, design & collect real life data and then analyze the results. Students will visually present findings and interpretations of the data as well as address concerns that arise with the collection of their data ( privacy, storage, security). The project will combine designing, collecting, filtering, cleaning and analyzing the collected data. It should be started early in unit 4 and will be completed at the end of the semester for the semester showcase.
This challenge has four parts:
Part A: Class Data Analysis: This will use the data your class has supplied over the past week. You will be using this data to practice making predictions, identify patterns and summarize results in a visualization. This portion was completed in Sprint 1 during the previous unit.
Part B: Design a citizen science project. Your team will use a design thinking approach to create a crowdsourced research project relating to your topic/innovation.
Part C: Collect Data. The team will implement the citizen science project to collect data from a wide variety of stakeholders.
Part D: Analyze the data and make recommendations. The team will clean, filter, sort and analyze the data to make research based recommendations.
Sprints 2 & 3 will focus on Parts B, C & D. Sprints 2 and 3 will be completed in Unit 5.