Lesson 14: Problem Solving with Big Data

Prompt: In the last lesson, we saw how data could be collected through questions and used to make a recommendation. There are other ways our data can be collected that are happening all around us every day. What are some ways that apps, companies, or governments could be collecting data about you?

Discuss: Have students journal individually, then share with a neighbor, and finally discuss as a whole class. You can record their ideas on the board to refer back to later in the class.

Discussion Goal: This is primarily a brainstorm. Some students may bring a lot more prior knowledge than others to the class and at this point, they haven’t been explicitly taught anything about data collection outside of surveys. Aim primarily just to get ideas out and set the stage for the lesson. You’re aiming to change focus from surveys that 10-20 people take to the vast amounts of data they might know is collected by modern technological tools.

Great work. Today we’re going to look at some real-world examples of how data is collected to solve problems. Keep an eye out for these ideas and think about whether you’re seeing any new ones.

Question of the Day: How is our data collected and why is it useful?

Group: Students may complete this activity individually or in pairs.

Distribute: Give students copies of activity guide

Data in the Real World

Web Pix: Read the introduction to Web Pix on the first page. Give students a few minutes to write down their ideas and/or share them with a partner. Let students know that they will not be able to answer the question about Netflix yet. If students finish early, ask them to think of other types of data and how they could be collected.

Share Out: Allow students to quickly share out some ideas, then introduce the Netflix video.

Many companies, such as YouTube, Facebook and Netflix, recommend videos and posts to users based on the data that they have collected about them. We're going to watch a short video about how Netflix does this. Pay attention to Netflix collects data to help it recommend good videos.

Video: Show students the Netflix and Data video in the slides.

To encourage active engagement and reflection, use one or more of the strategies discussed in the Guide to Curriculum Videos.

Discuss: Have students answer the third question about Netflix. Allow students to share with a partner, then discuss with a group the types of data that Netflix collects to help it make recommendations.

Discussion Goal: Students should understand that Netflix bases its suggestions not only on the survey data that users create, but also on the behavior of users as they use the site, such as what they watch and the ratings they give various videos.

Routz: Ask students to move on to the Routz problem. Again, they should take a few minutes to work individually or in pairs on the first two problems.

Share Out: Allow students to quickly share out some ideas, then introduce the Waze video.

Video: Show students the Waze and Data video in the slides.

Discuss: Allow students to share with a partner, then lead a short discussion on the types of data that Waze collects to help it find the best route.

Discussion Goal: Students should note that while some data is being intentionally added by the users, Waze also collects GPS/location data on each user without the user's active input. Sensor data, such as time, temperature, and location, are automatically collected by computers without a user actively adding them.

Nyle: Ask students to move on to the Nyle problem. Again, they should take a few minutes to work individually or in pairs on the first two problems.

Share Out: Allow students to quickly share out some ideas, then introduce the Amazon video.

Video: Show students the Amazon and Data video in the slides.

Discuss: Allow students to share with a partner, then lead a short discussion on the types of data that Amazon collects to help it find the best products to suggest.

Discussion Goal: There are a few different aspects of the Amazon video that may be of interest.

• Just looking at something online produces data that can be used by advertisers or others.
• Amazon decides what you might buy by looking at similar users and using their behavior to predict yours
• Different types of data, such as "clicks", "likes" and "purchases", may be weighted differently
• The user's needs are not the priority. The advertiser's needs are.

Any of these topics are relevant to the lesson, but the most important thing for students to realize is that they are not always aware when they are producing data.

We've found lots of different ways that the computer can collect data. In general, data can be collected automatically from sensors, as the Waze app collects GPS data; it can be collected from users who are intending to produce data, as when people rate Netflix videos; and it can be collected from users who are not intended to produce data, as when Amazon records which products you look at.

Reflection: Ask students to fill out the chart at the bottom of the page that categorizes the different types of data. Allow students to compare their answers with a partner.

On each page, students should have reasonable descriptions of relevant data and how it could be collected. These do not need to be the same as the data actually collected by the companies but should be relevant to the given problem and possible to collect.

Students should have multiple examples of data that has been actively and passively collected in the first and second columns on page 2.

Students should have multiple examples of tracking user behavior and sensor data in the second and third columns of the chart on page 2.

Prompt: Today we looked at three companies that collect data to solve problems. Brainstorm some other websites, apps, or companies you use or know about. What data are they collecting? How are they using it to solve a problem?

Discuss: Ask students to share their ideas with their classmates.

Discussion Goal: This prompt is meant to help students make connections between their personal experiences with data-collecting services and what they have learned in this lesson. The goal here is to connect the examples students saw in today’s lesson to other apps, websites, or services that they may be aware of. If you need to prompt students you might suggest they think of social media websites, media websites, useful apps they or their family uses, etc.

Today we saw some examples of different sources of data that real-world apps and websites use to solve problems. This also means these websites are collecting lots and lots of data - usually this is too much for a human to analyze! In the next lesson, we’ll look at how we can help computers make decisions and learn from all of this data.